(International Tables) Crystallography of biological macromolecules

International Tables for Crystallography
Volume F: Crystallography of biological macromolecules

Second online edition (2012) ISBN: 978-0-470-66078-2 doi: 10.1107/97809553602060000111 | 1 | 2 |

Edited by E. Arnold, D. M. Himmel and M. G. Rossmann

Preface to the second edition (p. xxix) | html | pdf |
E. Arnold, D. M. Himmel and M. G. Rossmann

Introduction
- 1.1. Overview (pp. 1-4) | html | pdf | chapter contents |
  E. Arnold, D. M. Himmel and M. G. Rossmann
- 1.2. Historical background (pp. 5-12) | html | pdf | chapter contents |
  M. G. Rossmann
  - 1.2.1. Introduction (p. 5) | html | pdf |
  - 1.2.2. 1912 to the 1950s (pp. 5-6) | html | pdf |
  - 1.2.3. The first investigations of biological macromolecules (pp. 6-7) | html | pdf |
  - 1.2.4. Globular proteins in the 1950s (pp. 7-8) | html | pdf |
  - 1.2.5. The first protein structures (1957 to the 1970s) (pp. 8-9) | html | pdf |
  - 1.2.6. Technological developments (1958 to the 1980s) (pp. 9-10) | html | pdf |
  - 1.2.7. Meetings (p. 10) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 1.2.4.1. Change of structure amplitude for horse haemoglobin as a function of salt concentration in the suspension medium of the low-order h0l reflections at various lattice shrinkage stages (C, C′, D, E, F, G, H, J) (p. 7) | html | pdf |
    - Fig. 1.2.5.1. A model of the myoglobin molecule at 6 Å resolution (p. 8) | html | pdf |
    - Fig. 1.2.5.2. Cylindrical sections through a helical segment of a myoglobin polypeptide chain (p. 8) | html | pdf |
    - Fig. 1.2.6.1. The 2 Å-resolution map of sperm-whale myoglobin was represented by coloured Meccano-set clips on a forest of vertical rods (p. 10) | html | pdf |
- 1.3. Macromolecular crystallography and medicine (pp. 13-38) | html | pdf | chapter contents |
  W. G. J. Hol and C. L. M. J. Verlinde
  - 1.3.1. Introduction (p. 13) | html | pdf |
  - 1.3.2. Crystallography and medicine (pp. 13-14) | html | pdf |
  - 1.3.3. Crystallography and genetic diseases (pp. 14-15) | html | pdf |
  - 1.3.4. Crystallography and development of novel pharmaceuticals (pp. 15-26) | html | pdf |
    - 1.3.4.1. Infectious diseases (pp. 16-18) | html | pdf |
      - 1.3.4.1.1. Viral diseases (p. 16) | html | pdf |
      - 1.3.4.1.2. Bacterial diseases (p. 16) | html | pdf |
      - 1.3.4.1.3. Protozoan infections (pp. 16-17) | html | pdf |
      - 1.3.4.1.4. Fungi (pp. 17-18) | html | pdf |
      - 1.3.4.1.5. Helminths (p. 18) | html | pdf |
    - 1.3.4.2. Resistance (pp. 18-22) | html | pdf |
    - 1.3.4.3. Non-communicable diseases (pp. 22-25) | html | pdf |
      - 1.3.4.3.1. Cancers (pp. 22-23) | html | pdf |
      - 1.3.4.3.2. Diabetes (p. 23) | html | pdf |
      - 1.3.4.3.3. Blindness (p. 23) | html | pdf |
      - 1.3.4.3.4. Cardiovascular disorders (p. 23) | html | pdf |
      - 1.3.4.3.5. Neurological disorders (pp. 23-25) | html | pdf |
    - 1.3.4.4. Drug metabolism and crystallography (p. 25) | html | pdf |
    - 1.3.4.5. Drug manufacturing and crystallography (pp. 25-26) | html | pdf |
  - 1.3.5. Vaccines, immunology and crystallography (p. 26) | html | pdf |
  - 1.3.6. Outlook and dreams (pp. 26-27) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 1.3.4.1. The structure-based drug design cycle (p. 16) | html | pdf |
  - Tables
    - Table 1.3.3.1. Crystal structures and genetic diseases (p. 14) | html | pdf |
    - Table 1.3.4.1. Important human pathogenic viruses and their proteins (pp. 17-18) | html | pdf |
    - Table 1.3.4.2. Protein structures of important human pathogenic bacteria (pp. 19-20) | html | pdf |
    - Table 1.3.4.3. Protein structures of important human pathogenic protozoa, fungi and helminths (pp. 21-22) | html | pdf |
    - Table 1.3.4.4. Mechanisms of resistance (p. 23) | html | pdf |
    - Table 1.3.4.5. Important human protein structures in drug design (pp. 24-25) | html | pdf |
- 1.4. Perspectives for the future (pp. 39-44) | html | pdf | chapter contents |
  E. Arnold, M. G. Rossmann, D. M. Himmel, J. C. H. Spence and S. Sun
  - 1.4.1. Gazing into the crystal ball (E. Arnold) (pp. 39-40) | html | pdf |
    - 1.4.1.1. What can we expect to see in the future of science and technology in general? (p. 39) | html | pdf |
    - 1.4.1.2. How will crystallography change in the future? (pp. 39-40) | html | pdf |
  - 1.4.2. Brief comments on Gazing into the crystal ball (M. G. Rossmann) (p. 40) | html | pdf |
  - 1.4.3. Additional comments on Gazing into the crystal ball (D. M. Himmel) (p. 41) | html | pdf |
  - 1.4.4. Gazing into the crystal ball – the X-ray free-electron laser (J. C. H. Spence) (pp. 41-42) | html | pdf |
  - 1.4.5. Electron microscopy's impact on structural biology (S. Sun) (pp. 42-43) | html | pdf |
  - References | html | pdf |

Basic crystallography
- 2.1. Introduction to basic crystallography (pp. 45-63) | html | pdf | chapter contents |
  J. Drenth
  - 2.1.1. Crystals (pp. 45-46) | html | pdf |
  - 2.1.2. Symmetry (pp. 46-47) | html | pdf |
  - 2.1.3. Point groups and crystal systems (pp. 47-52) | html | pdf |
  - 2.1.4. Basic diffraction physics (pp. 52-57) | html | pdf |
    - 2.1.4.1. Diffraction by one electron (pp. 52-53) | html | pdf |
    - 2.1.4.2. Scattering by a system of two electrons (pp. 53-54) | html | pdf |
    - 2.1.4.3. Scattering by atoms (pp. 54-55) | html | pdf |
      - 2.1.4.3.1. Scattering by one atom (p. 54) | html | pdf |
      - 2.1.4.3.2. Scattering by a plane of atoms (pp. 54-55) | html | pdf |
    - 2.1.4.4. Anomalous dispersion (p. 55) | html | pdf |
    - 2.1.4.5. Scattering by a crystal (pp. 55-56) | html | pdf |
    - 2.1.4.6. The structure factor (pp. 56-57) | html | pdf |
  - 2.1.5. Reciprocal space and the Ewald sphere (pp. 57-58) | html | pdf |
  - 2.1.6. Mosaicity and integrated reflection intensity (pp. 58-60) | html | pdf |
  - 2.1.7. Calculation of electron density (p. 60) | html | pdf |
  - 2.1.8. Symmetry in the diffraction pattern (pp. 60-61) | html | pdf |
  - 2.1.9. The Patterson function (pp. 62-63) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 2.1.1.1. One unit cell with axes a, b and c (p. 45) | html | pdf |
    - Fig. 2.1.1.2. A set of $[5 \times 3 \times 3]$ unit cells (p. 45) | html | pdf |
    - Fig. 2.1.1.3. A two-dimensional lattice with $[3 \times 3]$ unit cells (p. 46) | html | pdf |
    - Fig. 2.1.1.4. Non-centred and centred unit cells (p. 46) | html | pdf |
    - Fig. 2.1.3.1. How to construct a stereographic projection (p. 47) | html | pdf |
    - Fig. 2.1.3.2. A rhombohedral unit cell (p. 47) | html | pdf |
    - Fig. 2.1.3.3. The 14 Bravais lattices (p. 52) | html | pdf |
    - Fig. 2.1.4.1. The electric vector of a monochromatic and polarized X-ray beam is in the plane (p. 53) | html | pdf |
    - Fig. 2.1.4.2. The black dots are electrons (p. 53) | html | pdf |
    - Fig. 2.1.4.3. The direction of the incident wave is indicated by $[{\bf s}_{o}]$ and that of the scattered wave by s (p. 53) | html | pdf |
    - Fig. 2.1.4.4. An Argand diagram for the scattering by two electrons (p. 54) | html | pdf |
    - Fig. 2.1.4.5. The atomic scattering factor f for carbon as a function of $[\sin \theta /\lambda]$ , expressed in units of the scattering by one electron (p. 54) | html | pdf |
    - Fig. 2.1.4.6. S is the X-ray source and D is the detector (p. 55) | html | pdf |
    - Fig. 2.1.4.7. Schematic picture of the Argand diagram for the scattering by atoms in a plane (p. 55) | html | pdf |
    - Fig. 2.1.4.8. The atomic scattering factor as a vector in the Argand diagram (p. 55) | html | pdf |
    - Fig. 2.1.4.9. X-ray diffraction by a crystal is, in Bragg's conception, reflection by lattice planes (p. 56) | html | pdf |
    - Fig. 2.1.4.10. The Wilson plot for phospholipase A₂ with data to 1.7 Å resolution (p. 57) | html | pdf |
    - Fig. 2.1.5.1. A two-dimensional real unit cell is drawn together with its reciprocal unit cell (p. 58) | html | pdf |
    - Fig. 2.1.5.2. The circle is, in fact, a sphere with radius $[1/\lambda]$ (p. 59) | html | pdf |
    - Fig. 2.1.7.1. An Argand diagram for the structure factors of the two members of a Friedel pair (p. 61) | html | pdf |
    - Fig. 2.1.9.1. (a) A two-dimensional unit cell with two atoms (p. 62) | html | pdf |
  - Tables
    - Table 2.1.2.1. The most common space groups for protein crystals (p. 47) | html | pdf |
    - Table 2.1.3.1. The 11 enantiomorphic point groups (pp. 48-49) | html | pdf |
    - Table 2.1.3.2. The 11 point groups with a centre of symmetry (pp. 50-51) | html | pdf |
    - Table 2.1.3.3. The icosahedral point group 532 (p. 52) | html | pdf |
    - Table 2.1.3.4. The seven crystal systems (p. 52) | html | pdf |
    - Table 2.1.4.1. The position of the Kα edge of different elements (p. 54) | html | pdf |
- 2.2. Quality indicators in macromolecular crystallography: definitions and applications (pp. 64-74) | html | pdf | chapter contents |
  H. M. Einspahr and M. S. Weiss
  - 2.2.1. Introduction (pp. 64-65) | html | pdf |
  - 2.2.2. Quality indicators for diffraction data (pp. 65-68) | html | pdf |
  - 2.2.3. Comparing different diffraction data sets (p. 68) | html | pdf |
  - 2.2.4. Quality indicators for substructure determination (pp. 68-69) | html | pdf |
  - 2.2.5. Quality indicators for phase determination (p. 69) | html | pdf |
  - 2.2.6. Quality indicators for density modification and phase improvement (pp. 69-70) | html | pdf |
  - 2.2.7. Quality indicators for molecular replacement (pp. 70-71) | html | pdf |
  - 2.2.8. Quality indicators for refinement (p. 71) | html | pdf |
  - 2.2.9. Quality indicators for the refined model (pp. 71-73) | html | pdf |
  - 2.2.10. Error estimation for the refined model (p. 73) | html | pdf |
  - 2.2.11. The most commonly used quality indicators (p. 73) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 2.2.11.1. Definitions of the most commonly used quality indicators (p. 72) | html | pdf |

Techniques of molecular biology
- 3.1. Preparing recombinant proteins for X-ray crystallography (pp. 75-91) | html | pdf | chapter contents |
  S. H. Hughes and A. M. Stock
  - 3.1.1. Introduction (p. 75) | html | pdf |
  - 3.1.2. Overview (pp. 75-76) | html | pdf |
  - 3.1.3. Engineering an expression construct (pp. 76-77) | html | pdf |
    - 3.1.3.1. Choosing an expression system (p. 76) | html | pdf |
    - 3.1.3.2. Creating an expression construct (pp. 76-77) | html | pdf |
    - 3.1.3.3. Addition of tags or domains (p. 77) | html | pdf |
  - 3.1.4. Expression systems (pp. 77-85) | html | pdf |
    - 3.1.4.1. E. coli (pp. 77-82) | html | pdf |
    - 3.1.4.2. Yeast (pp. 82-83) | html | pdf |
    - 3.1.4.3. Baculoviruses and insect cells (pp. 83-84) | html | pdf |
    - 3.1.4.4. Mammalian cells (pp. 84-85) | html | pdf |
  - 3.1.5. Protein purification (pp. 85-88) | html | pdf |
    - 3.1.5.1. Conventional protein purification (pp. 85-87) | html | pdf |
    - 3.1.5.2. Affinity purification (p. 87) | html | pdf |
    - 3.1.5.3. Purifying and refolding denatured proteins (pp. 87-88) | html | pdf |
  - 3.1.6. Characterization of the purified product (pp. 88-89) | html | pdf |
    - 3.1.6.1. Assessment of sample homogeneity (pp. 88-89) | html | pdf |
    - 3.1.6.2. Protein storage (p. 89) | html | pdf |
  - 3.1.7. Reprise (pp. 89-90) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 3.1.3.1. Creating an expression construct (p. 77) | html | pdf |
    - Fig. 3.1.5.1. Protein purification strategy (p. 86) | html | pdf |
  - Tables
    - Table 3.1.4.1. Strategies for improving expression in E. coli (p. 79) | html | pdf |
- 3.2. Expression and purification of membrane proteins for structural studies (pp. 92-98) | html | pdf | chapter contents |
  J. A. Ernst, D. G. Yansura and C. M. Koth
  - 3.2.1. Introduction (p. 92) | html | pdf |
  - 3.2.2. A consensus strategy for membrane-protein expression (pp. 92-93) | html | pdf |
    - 3.2.2.1. Choosing the expression system and affinity tags (p. 92) | html | pdf |
    - 3.2.2.2. Strategies for improving membrane-protein expression (p. 93) | html | pdf |
  - 3.2.3. A consensus strategy for membrane-protein purification (pp. 93-96) | html | pdf |
    - 3.2.3.1. General principles (pp. 93-94) | html | pdf |
    - 3.2.3.2. Cell lysis and membrane isolation (p. 94) | html | pdf |
    - 3.2.3.3. Detergent extraction of membrane proteins (pp. 94-95) | html | pdf |
    - 3.2.3.4. General considerations for monitoring membrane-protein activity (p. 95) | html | pdf |
    - 3.2.3.5. Primary purification: affinity chromatography (p. 95) | html | pdf |
    - 3.2.3.6. Secondary purification: size-exclusion and ion-exchange chromatography (p. 95) | html | pdf |
    - 3.2.3.7. Concentrating membrane-protein samples for crystallography (pp. 95-96) | html | pdf |
  - 3.2.4. Common purification pitfalls and prioritized alternative strategies (p. 96) | html | pdf |
    - 3.2.4.1. Poor solubility of the target protein (p. 96) | html | pdf |
    - 3.2.4.2. The isolated target protein does not crystallize (p. 96) | html | pdf |
  - 3.2.5. Summary (p. 96) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 3.2.3.1. Flow diagram of the membrane-protein purification strategy (p. 94) | html | pdf |
  - Tables
    - Table 3.2.2.1. Strategies for improving recombinant membrane-protein expression in E. coli (p. 93) | html | pdf |

Crystallization
- 4.1. General methods (pp. 99-121) | html | pdf | chapter contents |
  C. Sauter, B. Lorber, A. McPherson and R. Giegé
  - 4.1.1. Introduction (pp. 99-100) | html | pdf |
    - 4.1.1.1. Prologue (p. 99) | html | pdf |
    - 4.1.1.2. Crystallization principles (pp. 99-100) | html | pdf |
  - 4.1.2. Main parameters that affect crystallization of macromolecules (pp. 100-104) | html | pdf |
    - 4.1.2.1. Crystallizing agents (pp. 100-101) | html | pdf |
    - 4.1.2.2. Physical, physical–chemical and biochemical variables (pp. 101-102) | html | pdf |
    - 4.1.2.3. Additives (pp. 102-103) | html | pdf |
    - 4.1.2.4. Purity and homogeneity (pp. 103-104) | html | pdf |
  - 4.1.3. Crystallization arrangements and classical methodologies (pp. 104-107) | html | pdf |
    - 4.1.3.1. Historical development of methods (pp. 104-105) | html | pdf |
    - 4.1.3.2. Batch crystallizations (p. 105) | html | pdf |
    - 4.1.3.3. Dialysis methods (p. 105) | html | pdf |
    - 4.1.3.4. Vapour-diffusion methods (p. 106) | html | pdf |
    - 4.1.3.5. Free-interface and counter-diffusion methods (p. 107) | html | pdf |
    - 4.1.3.6. Miniaturization, automation and robotics (p. 107) | html | pdf |
  - 4.1.4. Advanced crystallization methodologies (pp. 107-111) | html | pdf |
    - 4.1.4.1. Crystallization in convection-free media (pp. 107-110) | html | pdf |
    - 4.1.4.2. Methods making use of temperature and pressure (p. 110) | html | pdf |
    - 4.1.4.3. Methods making use of crystallization chaperones (p. 110) | html | pdf |
    - 4.1.4.4. Seeding (pp. 110-111) | html | pdf |
  - 4.1.5. From the macromolecule to perfect crystals: the physics view (pp. 111-113) | html | pdf |
    - 4.1.5.1. Prenucleation and nucleation (p. 111) | html | pdf |
    - 4.1.5.2. Growth and cessation of growth (pp. 111-112) | html | pdf |
    - 4.1.5.3. Uncoupling nucleation and growth, and the constant-growth regime (p. 112) | html | pdf |
    - 4.1.5.4. Crystal perfection (pp. 112-113) | html | pdf |
  - 4.1.6. How to crystallize a new macromolecule: the structural biology view (pp. 113-115) | html | pdf |
    - 4.1.6.1. How to start and how to choose what screening kits to start with (p. 113) | html | pdf |
    - 4.1.6.2. Rules and general principles (p. 114) | html | pdf |
    - 4.1.6.3. Database mining and statistics (pp. 114-115) | html | pdf |
    - 4.1.6.4. Strategic concerns: a summary (p. 115) | html | pdf |
  - 4.1.7. The future of protein crystal growth (p. 115) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 4.1.1.1. Crystallization is a multiparametric process under the control of a great variety of biochemical, chemical and physical parameters (p. 100) | html | pdf |
    - Fig. 4.1.3.1. Principles of major methods used to crystallize biological macromolecules (p. 104) | html | pdf |
    - Fig. 4.1.3.2. The evolution of crystallization plates from hand-made assays to the high-throughput era (p. 105) | html | pdf |
    - Fig. 4.1.4.1. Examples of microfluidic devices designed for biocrystallization (p. 109) | html | pdf |
    - Fig. 4.1.5.1. Growth mechanisms and visualization of protein crystal surfaces by AFM (p. 112) | html | pdf |
    - Fig. 4.1.6.1. From the target molecule to its three-dimensional structure: a flowchart for a structure detemination (p. 113) | html | pdf |
- 4.2. Crystallization of membrane proteins (pp. 122-128) | html | pdf | chapter contents |
  H. Michel
  - 4.2.1. Introduction (p. 122) | html | pdf |
  - 4.2.2. Principles of membrane-protein crystallization (pp. 122-123) | html | pdf |
  - 4.2.3. General properties of detergents relevant to membrane-protein crystallization (pp. 123-125) | html | pdf |
  - 4.2.4. The `small amphiphile concept' (pp. 125-126) | html | pdf |
  - 4.2.5. Membrane-protein crystallization with the help of antibody Fv fragments (p. 126) | html | pdf |
  - 4.2.6. Membrane-protein crystallization using cubic bicontinuous lipidic phases (p. 126) | html | pdf |
  - 4.2.7. General recommendations (pp. 126-127) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 4.2.1.1. Compilation of membrane proteins with known structures, including crystallization conditions and key references for the structure determinations (pp. 123-124) | html | pdf |
    - Table 4.2.2.1. Potentially useful detergents for membrane-protein crystallizations with molecular weights and CMCs [in water, from Michel (1991) or as provided by the vendor] (p. 125) | html | pdf |
    - Table 4.2.3.1. Summary of the results of attempts to crystallize the two-subunit cytochrome c oxidase from the soil bacterium Paracoccus denitrificans using different detergents (after Ostermeier et al., 1997) (p. 126) | html | pdf |
- 4.3. Application of protein engineering to enhance crystallizability and improve crystal properties (pp. 129-139) | html | pdf | chapter contents |
  Z. S. Derewenda
  - 4.3.1. Introduction (p. 129) | html | pdf |
  - 4.3.2. Microscopic aspects of protein crystallization (pp. 129-130) | html | pdf |
  - 4.3.3. Engineering proteins with enhanced solubility (pp. 130-131) | html | pdf |
  - 4.3.4. Optimization of target constructs (p. 131) | html | pdf |
  - 4.3.5. The use of fusion proteins for crystallization (pp. 131-132) | html | pdf |
  - 4.3.6. Noncovalent crystallization chaperones (pp. 132-133) | html | pdf |
  - 4.3.7. Removal of post-translational modifications (pp. 133-134) | html | pdf |
  - 4.3.8. Stabilization of protein targets (p. 134) | html | pdf |
  - 4.3.9. Surface-entropy reduction (SER) (pp. 134-135) | html | pdf |
  - 4.3.10. Improvement of crystal quality (p. 135) | html | pdf |
  - 4.3.11. Conclusions (pp. 135-136) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 4.3.4.1. A domain-trapping strategy to engineer soluble variants of a protein of interest (POI) for crystallization using the split-GFP complementation methodology (p. 131) | html | pdf |
    - Fig. 4.3.5.1. An example of the use of a fused carrier protein in crystallization: the crystal structure of the RACK1 protein (green) crystallized in fusion with an engineered variant of the maltose-binding protein (MBP; red); the major crystal contacts are mediated by MBP (p. 132) | html | pdf |
    - Fig. 4.3.6.1. Phage-display-generated Fab fragments as crystallization chaperones: the structure of the KcsA channel in the closed conformation in complex with a synthetic Fab (p. 133) | html | pdf |
    - Fig. 4.3.9.1. Two examples of proteins crystallized by the surface-entropy reduction (SER) method (p. 135) | html | pdf |
- 4.4. High-throughput X-ray crystallography (pp. 140-144) | html | pdf | chapter contents |
  K. H. Choi
  - 4.4.1. Introduction (p. 140) | html | pdf |
  - 4.4.2. Design of multiple constructs: bioinformatics analysis of genome sequences (p. 140) | html | pdf |
  - 4.4.3. Cloning (pp. 140-142) | html | pdf |
    - 4.4.3.1. Ligation-independent and recombination cloning (pp. 140-141) | html | pdf |
    - 4.4.3.2. Practical application (pp. 141-142) | html | pdf |
  - 4.4.4. Protein expression and purification (p. 142) | html | pdf |
    - 4.4.4.1. Autoinduction (p. 142) | html | pdf |
    - 4.4.4.2. Expression and solubility test: dot blot (p. 142) | html | pdf |
    - 4.4.4.3. Small-scale purification (p. 142) | html | pdf |
  - 4.4.5. Crystallization (pp. 142-143) | html | pdf |
  - 4.4.6. Synchrotron data collection (p. 143) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 4.4.3.1. Diagram of HT cloning, expression and purification (p. 141) | html | pdf |

Crystal properties and handling
- 5.1. Crystal morphology, optical properties of crystals and crystal mounting (pp. 145-151) | html | pdf | chapter contents |
  H. L. Carrell and J. P. Glusker
  - 5.1.1. Crystal morphology and optical properties (pp. 145-148) | html | pdf |
    - 5.1.1.1. Crystal growth habits (pp. 145-146) | html | pdf |
      - 5.1.1.1.1. The shape of a crystal – growth habits (p. 145) | html | pdf |
      - 5.1.1.1.2. Quality of protein crystals (p. 145) | html | pdf |
      - 5.1.1.1.3. Polymorphism (p. 146) | html | pdf |
      - 5.1.1.1.4. Twinning (p. 146) | html | pdf |
    - 5.1.1.2. Properties of crystal faces (p. 146) | html | pdf |
      - 5.1.1.2.1. Indexing crystal faces (p. 146) | html | pdf |
      - 5.1.1.2.2. Measurement of crystal habit (p. 146) | html | pdf |
    - 5.1.1.3. Optical properties (pp. 146-148) | html | pdf |
      - 5.1.1.3.1. Crystals between crossed polarizers (pp. 147-148) | html | pdf |
      - 5.1.1.3.2. Refractive indices and what they tell us about structure (p. 148) | html | pdf |
    - 5.1.1.4. Packing of molecules in crystals (p. 148) | html | pdf |
  - 5.1.2. Crystal mounting (pp. 148-150) | html | pdf |
    - 5.1.2.1. Introduction to crystal mounting (p. 148) | html | pdf |
    - 5.1.2.2. Tools for crystal mounting (pp. 148-149) | html | pdf |
      - 5.1.2.2.1. Microscope (p. 149) | html | pdf |
      - 5.1.2.2.2. Capillaries (p. 149) | html | pdf |
      - 5.1.2.2.3. Thumb pump (p. 149) | html | pdf |
      - 5.1.2.2.4. Heater (p. 149) | html | pdf |
    - 5.1.2.3. Capillary mounting (pp. 149-150) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 5.1.1.1. Crystal faces (p. 147) | html | pdf |
    - Fig. 5.1.2.1. Tools commonly used for mounting crystals (p. 148) | html | pdf |
    - Fig. 5.1.2.2. Mounting a crystal in a capillary (p. 150) | html | pdf |
- 5.2. Crystal-density measurements (pp. 152-157) | html | pdf | chapter contents |
  E. M. Westbrook
  - 5.2.1. Introduction (p. 152) | html | pdf |
  - 5.2.2. Solvent in macromolecular crystals (p. 152) | html | pdf |
  - 5.2.3. Matthews number (p. 152) | html | pdf |
  - 5.2.4. Algebraic concepts (pp. 152-153) | html | pdf |
  - 5.2.5. Experimental estimation of hydration (p. 153) | html | pdf |
  - 5.2.6. Methods for measuring crystal density (pp. 153-156) | html | pdf |
    - 5.2.6.1. Pycnometry (p. 154) | html | pdf |
    - 5.2.6.2. Volumenometry (p. 154) | html | pdf |
    - 5.2.6.3. The method of Archimedes (p. 154) | html | pdf |
    - 5.2.6.4. Immersion microbalance (p. 154) | html | pdf |
    - 5.2.6.5. Flotation (pp. 154-155) | html | pdf |
    - 5.2.6.6. Tomographic crystal-volume measurement (p. 155) | html | pdf |
    - 5.2.6.7. Gradient-tube method (pp. 155-156) | html | pdf |
  - 5.2.7. How to handle the solvent density (p. 156) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 5.2.6.1. Organic liquids for density determinations (p. 155) | html | pdf |
    - Table 5.2.6.2. Inorganic salts for density determinations (p. 155) | html | pdf |

Radiation sources and optics
- 6.1. X-ray sources (pp. 159-167) | html | pdf | chapter contents |
  U. W. Arndt
  - 6.1.1. Overview (p. 159) | html | pdf |
  - 6.1.2. Generation of X-rays (pp. 159-162) | html | pdf |
    - 6.1.2.1. Stationary-target X-ray tubes (p. 159) | html | pdf |
    - 6.1.2.2. Rotating-anode X-ray tubes (pp. 159-160) | html | pdf |
    - 6.1.2.3. Microfocus X-ray tubes (p. 160) | html | pdf |
    - 6.1.2.4. Synchrotron-radiation sources (pp. 160-162) | html | pdf |
  - 6.1.3. Properties of the X-ray beam (pp. 162-164) | html | pdf |
    - 6.1.3.1. Beam size (p. 162) | html | pdf |
    - 6.1.3.2. X-ray wavelength (p. 162) | html | pdf |
    - 6.1.3.3. Spectral composition (pp. 162-163) | html | pdf |
    - 6.1.3.4. Intensity (p. 163) | html | pdf |
    - 6.1.3.5. Cross fire (p. 163) | html | pdf |
    - 6.1.3.6. Beam stability (pp. 163-164) | html | pdf |
  - 6.1.4. Beam conditioning (pp. 164-166) | html | pdf |
    - 6.1.4.1. X-ray mirrors (pp. 164-165) | html | pdf |
    - 6.1.4.2. Focusing collimators for microfocus sources (p. 165) | html | pdf |
    - 6.1.4.3. Other focusing collimators (pp. 165-166) | html | pdf |
    - 6.1.4.4. Crystal monochromators (p. 166) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 6.1.2.1. Section through a sealed X-ray tube (p. 159) | html | pdf |
    - Fig. 6.1.2.2. Synchrotron radiation emitted by a relativistic electron travelling in a curved trajectory (p. 160) | html | pdf |
    - Fig. 6.1.2.3. Comparison of the spectra from the storage ring SPEAR (p. 161) | html | pdf |
    - Fig. 6.1.2.4. Main components of a dedicated electron storage-ring synchrotron-radiation source (p. 161) | html | pdf |
    - Fig. 6.1.2.5. Electron trajectory within a multipole wiggler or undulator (p. 161) | html | pdf |
    - Fig. 6.1.2.6. Spectral distribution and critical wavelengths for (a) a dipole magnet, (b) a wavelength shifter and (c) a multipole wiggler at the ESRF (p. 162) | html | pdf |
    - Fig. 6.1.4.1. Production of a point focus by successive reflections at two orthogonal curved mirrors (p. 164) | html | pdf |
    - Fig. 6.1.4.2. The `catamegonic' arrangement of Montel (1957), in which two confocal mirrors with orthogonal curvatures lie side-by-side (p. 164) | html | pdf |
    - Fig. 6.1.4.3. Mirror bender (after Franks, 1955) (p. 164) | html | pdf |
    - Fig. 6.1.4.4. Triangular mirror bender as described by Lemonnier et al (p. 164) | html | pdf |
    - Fig. 6.1.4.5. Mirror holder with machined slots for two orthogonal pairs of curved mirrors (p. 165) | html | pdf |
    - Fig. 6.1.4.6. Ellipsoidal mirror for use with a microfocus X-ray tube, where x₁ is ∼15 mm (p. 165) | html | pdf |
    - Fig. 6.1.4.7. A polycapillary collimator (after Bly & Gibson, 1996) (p. 165) | html | pdf |
  - Tables
    - Table 6.1.2.1. Standard X-ray tube inserts (p. 159) | html | pdf |
- 6.2. Neutron sources (pp. 168-176) | html | pdf | chapter contents |
  B. P. Schoenborn and R. Knott
  - 6.2.1. Reactors (pp. 168-172) | html | pdf |
    - 6.2.1.1. Basic reactor physics (p. 168) | html | pdf |
    - 6.2.1.2. Moderators for neutron scattering (p. 169) | html | pdf |
      - 6.2.1.2.1. Thermal moderators (p. 169) | html | pdf |
      - 6.2.1.2.2. Cold moderators (p. 169) | html | pdf |
    - 6.2.1.3. Beamline components (pp. 169-171) | html | pdf |
      - 6.2.1.3.1. Collimators and filters (pp. 169-170) | html | pdf |
      - 6.2.1.3.2. Crystal monochromators (p. 170) | html | pdf |
      - 6.2.1.3.3. Multilayer monochromators and supermirrors (pp. 170-171) | html | pdf |
      - 6.2.1.3.4. Velocity selectors (p. 171) | html | pdf |
      - 6.2.1.3.5. Neutron guides (p. 171) | html | pdf |
    - 6.2.1.4. Detectors (pp. 171-172) | html | pdf |
      - 6.2.1.4.1. Multiwire proportional counters (pp. 171-172) | html | pdf |
      - 6.2.1.4.2. Image plates (p. 172) | html | pdf |
    - 6.2.1.5. Instrument resolution functions (p. 172) | html | pdf |
  - 6.2.2. Spallation neutron sources (pp. 172-174) | html | pdf |
    - 6.2.2.1. Spallation neutron production (p. 173) | html | pdf |
    - 6.2.2.2. Moderators (p. 173) | html | pdf |
    - 6.2.2.3. Beamline optics (pp. 173-174) | html | pdf |
    - 6.2.2.4. Time-of-flight techniques (p. 174) | html | pdf |
    - 6.2.2.5. Data-collection considerations (p. 174) | html | pdf |
  - 6.2.3. Summary (p. 175) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 6.2.1.1. Schematic of the High Flux Beam Reactor at the Brookhaven National Laboratory (USA) (p. 168) | html | pdf |
    - Fig. 6.2.1.2. Neutron wavelength distributions for a thermal (310 K) and a cold (30 K) neutron moderator in a `typical' dedicated beam reactor (p. 169) | html | pdf |
    - Fig. 6.2.1.3. (a) Schematic vector diagram for an elastic neutron-scattering event (p. 170) | html | pdf |
    - Fig. 6.2.1.4. A generic neutron-scattering instrument illustrating the classes of facilities and operators important to instrument design and assessment (p. 170) | html | pdf |
    - Fig. 6.2.2.1. Schematic presentation of the various nuclear processes encountered in spallation (p. 172) | html | pdf |
    - Fig. 6.2.2.2. Schematic diagram of a spallation target module depicting the inner Be and outer Pb reflector (p. 173) | html | pdf |
    - Fig. 6.2.2.3. Neutron flux given as a time–wavelength spectrum for (a) a fully decoupled system and (b) for a fully coupled system (p. 174) | html | pdf |

X-ray detectors
- 7.1. Comparison of X-ray detectors (pp. 177-182) | html | pdf | chapter contents |
  S. M. Gruner, E. F. Eikenberry and M. W. Tate
  - 7.1.1. Commonly used detectors: general considerations (pp. 177-178) | html | pdf |
  - 7.1.2. Evaluating and comparing detectors (pp. 178-179) | html | pdf |
  - 7.1.3. Characteristics of different detector approaches (pp. 179-181) | html | pdf |
    - 7.1.3.1. Point versus linear versus area detection (p. 179) | html | pdf |
    - 7.1.3.2. Counting and integrating detectors (pp. 179-181) | html | pdf |
      - 7.1.3.2.1. Photon-counting detectors (pp. 179-180) | html | pdf |
      - 7.1.3.2.2. Integrating detectors (pp. 180-181) | html | pdf |
  - 7.1.4. Future detectors (p. 181) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 7.1.1.1. X-ray detectors for crystallography (p. 177) | html | pdf |
- 7.2. CCD detectors (pp. 183-188) | html | pdf | chapter contents |
  M. W. Tate, E. F. Eikenberry and S. M. Gruner
  - 7.2.1. Overview (p. 183) | html | pdf |
  - 7.2.2. CCD detector assembly (pp. 183-184) | html | pdf |
  - 7.2.3. Calibration and correction (pp. 184-186) | html | pdf |
    - 7.2.3.1. Dark-current subtraction (p. 185) | html | pdf |
    - 7.2.3.2. Removal of radioactive decay events (p. 185) | html | pdf |
    - 7.2.3.3. Geometric distortion (p. 185) | html | pdf |
    - 7.2.3.4. Flat-field corrections (pp. 185-186) | html | pdf |
    - 7.2.3.5. Obliquity correction (p. 186) | html | pdf |
    - 7.2.3.6. Modular images (p. 186) | html | pdf |
  - 7.2.4. Detector system integration (pp. 186-187) | html | pdf |
  - 7.2.5. Applications to macromolecular crystallography (p. 187) | html | pdf |
  - 7.2.6. Future of CCD detectors (p. 187) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 7.2.1.1. Schematic of a single-module CCD detector (p. 183) | html | pdf |

Synchrotron crystallography
- 8.1. Synchrotron-radiation instrumentation, methods and scientific utilization (pp. 189-204) | html | pdf | chapter contents |
  J. R. Helliwell
  - 8.1.1. Introduction (p. 189) | html | pdf |
  - 8.1.2. The physics of SR (pp. 189-190) | html | pdf |
  - 8.1.3. Insertion devices (IDs) (pp. 190-191) | html | pdf |
  - 8.1.4. Beam characteristics delivered at the crystal sample (pp. 191-192) | html | pdf |
  - 8.1.5. Evolution of SR machines and experiments (pp. 192-194) | html | pdf |
    - 8.1.5.1. First-generation SR machines (pp. 192-193) | html | pdf |
    - 8.1.5.2. Second-generation dedicated machines (p. 193) | html | pdf |
    - 8.1.5.3. Third-generation high spectral brightness machines (pp. 193-194) | html | pdf |
    - 8.1.5.4. New national SR machines (p. 194) | html | pdf |
    - 8.1.5.5. X-ray free-electron lasers (XFELs) (p. 194) | html | pdf |
  - 8.1.6. SR instrumentation (pp. 194-195) | html | pdf |
  - 8.1.7. SR monochromatic and Laue diffraction geometry (pp. 195-197) | html | pdf |
    - 8.1.7.1. Laue geometry: sources, optics, sample reflection bandwidth and spot size (pp. 195-196) | html | pdf |
    - 8.1.7.2. Monochromatic SR beams: optical configurations and sample rocking width (pp. 196-197) | html | pdf |
      - 8.1.7.2.1. Curved single-crystal monochromator (p. 196) | html | pdf |
      - 8.1.7.2.2. Double-crystal monochromator (p. 196) | html | pdf |
      - 8.1.7.2.3. Widening of monochromatic wavelength range provision (pp. 196-197) | html | pdf |
      - 8.1.7.2.4. Crystal sample rocking width (p. 197) | html | pdf |
  - 8.1.8. Scientific utilization of SR in protein crystallography (pp. 197-200) | html | pdf |
    - 8.1.8.1. Atomic and ultra-high-resolution macromolecular crystallography (p. 198) | html | pdf |
    - 8.1.8.2. Small crystals (p. 198) | html | pdf |
    - 8.1.8.3. Time-resolved macromolecular crystallography (p. 198) | html | pdf |
    - 8.1.8.4. Multi-macromolecular complexes (pp. 198-199) | html | pdf |
    - 8.1.8.5. Optimized anomalous dispersion (MAD), improved multiple isomorphous replacement (MIR) data and `structural genomics' (pp. 199-200) | html | pdf |
    - 8.1.8.6. Radiation damage (p. 200) | html | pdf |
  - 8.1.9. Concluding remarks (p. 200) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 8.1.2.1. The ring tunnel and part of the machine lattice at the ESRF, Grenoble, France (p. 189) | html | pdf |
    - Fig. 8.1.2.2. SR spectra (p. 190) | html | pdf |
    - Fig. 8.1.4.1. Common beamline optics modes (p. 191) | html | pdf |
    - Fig. 8.1.4.2. Single-crystal SR diffraction patterns (p. 191) | html | pdf |
    - Fig. 8.1.5.1. Anomalous dispersion (p. 193) | html | pdf |
    - Fig. 8.1.7.1. Single-crystal monochromator illuminated by SR (p. 196) | html | pdf |
    - Fig. 8.1.7.2. Double-crystal monochromator illuminated by SR (p. 197) | html | pdf |
    - Fig. 8.1.7.3. The rocking width of an individual reflection for the case of Fig. 8.1.7.1(c) and a vertical rotation axis (p. 197) | html | pdf |
    - Fig. 8.1.8.1. Determination of the protonation states of carboxylic acid side chains in proteins via hydrogen atoms and resolved single and double bond lengths (p. 198) | html | pdf |
    - Fig. 8.1.8.2. A view of SV40 virus (p. 199) | html | pdf |
    - Fig. 8.1.8.3. The protein crystal structure of F₁ ATPase (p. 199) | html | pdf |
    - Fig. 8.1.8.4. Side view of the structure of Photosystem II, the water-splitting enzyme of photosynthesis, determined using X-ray crystallography based on data recorded at the SLS and ESRF (p. 199) | html | pdf |
    - Fig. 8.1.9.1. Synchrotron structures deposited in the PDB versus all PDB deposited structures (p. 200) | html | pdf |
  - Tables
    - Table 8.1.4.1. Internet addresses of SR facilities with macromolecular crystallography beamlines (p. 192) | html | pdf |
    - Table 8.1.5.1. Structures in the Protein Data Bank (PDB) for which data were collected at the SRS (p. 194) | html | pdf |
- 8.2. Laue crystallography: time-resolved studies (pp. 205-210) | html | pdf | chapter contents |
  K. Moffat
  - 8.2.1. Introduction (p. 205) | html | pdf |
  - 8.2.2. Principles of Laue diffraction (pp. 205-206) | html | pdf |
  - 8.2.3. Practical considerations in the Laue technique (pp. 206-208) | html | pdf |
  - 8.2.4. The time-resolved experiment (pp. 208-209) | html | pdf |
  - 8.2.5. Conclusions (p. 209) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 8.2.2.1. Laue diffraction geometry (p. 205) | html | pdf |
    - Fig. 8.2.3.1. Flow chart of typical Laue data processing (p. 208) | html | pdf |
  - Tables
    - Table 8.2.2.1. Advantages and disadvantages of the Laue technique (p. 207) | html | pdf |
    - Table 8.2.5.1. Time-resolved Laue diffraction experiments (p. 209) | html | pdf |

X-ray data collection
- 9.1. Principles of monochromatic data collection (pp. 211-230) | html | pdf | chapter contents |
  Z. Dauter and K. S. Wilson
  - 9.1.1. Introduction (p. 211) | html | pdf |
  - 9.1.2. The components of a monochromatic X-ray experiment (p. 211) | html | pdf |
  - 9.1.3. Data completeness (p. 211) | html | pdf |
  - 9.1.4. X-ray sources (pp. 211-212) | html | pdf |
    - 9.1.4.1. Conventional sources (pp. 211-212) | html | pdf |
    - 9.1.4.2. Synchrotron storage rings (p. 212) | html | pdf |
  - 9.1.5. Goniostat geometry (pp. 212-213) | html | pdf |
    - 9.1.5.1. Overview (p. 212) | html | pdf |
    - 9.1.5.2. The screenless rotation method and 2D detectors (pp. 212-213) | html | pdf |
  - 9.1.6. Basis of the rotation method (pp. 213-217) | html | pdf |
    - 9.1.6.1. Rotation geometry (p. 213) | html | pdf |
    - 9.1.6.2. Diffraction pattern at a single orientation: the `still' image (pp. 213-214) | html | pdf |
    - 9.1.6.3. Rocking curve: crystal mosaicity and beam divergence (p. 214) | html | pdf |
    - 9.1.6.4. Rotation images and lunes (p. 214) | html | pdf |
    - 9.1.6.5. Partially and fully recorded reflections (pp. 214-215) | html | pdf |
    - 9.1.6.6. The width of the rotation range per image: fine φ slicing (p. 215) | html | pdf |
    - 9.1.6.7. Wide slicing (pp. 215-217) | html | pdf |
  - 9.1.7. Rotation method: geometrical completeness (pp. 217-221) | html | pdf |
    - 9.1.7.1. Total rotation range for non-anomalous data (pp. 217-219) | html | pdf |
    - 9.1.7.2. Total rotation range for anomalous-dispersion data (pp. 219-220) | html | pdf |
    - 9.1.7.3. Blind region (pp. 220-221) | html | pdf |
    - 9.1.7.4. Alternative indexing (p. 221) | html | pdf |
  - 9.1.8. Crystal-to-detector distance (pp. 221-222) | html | pdf |
  - 9.1.9. Wavelength (p. 222) | html | pdf |
  - 9.1.10. Lysozyme as an example (pp. 222-223) | html | pdf |
  - 9.1.11. Rotation method: qualitative factors (pp. 223-225) | html | pdf |
    - 9.1.11.1. Inspection of reflection profiles (pp. 223-224) | html | pdf |
    - 9.1.11.2. Exposure time (p. 224) | html | pdf |
    - 9.1.11.3. Overloads (p. 224) | html | pdf |
    - 9.1.11.4. R factor, I/σ(I) ratio and estimated uncertainties (pp. 224-225) | html | pdf |
  - 9.1.12. Radiation damage (pp. 225-226) | html | pdf |
    - 9.1.12.1. Historical perspective (p. 225) | html | pdf |
    - 9.1.12.2. Cryogenic vitrification (pp. 225-226) | html | pdf |
    - 9.1.12.3. High-intensity third-generation SR sources (p. 226) | html | pdf |
    - 9.1.12.4. Correcting data for the effects of radiation damage (p. 226) | html | pdf |
  - 9.1.13. Relating data collection to the problem in hand (pp. 226-228) | html | pdf |
    - 9.1.13.1. Isomorphous-anomalous derivatives (pp. 226-227) | html | pdf |
    - 9.1.13.2. Anomalous scattering, MAD and SAD (p. 227) | html | pdf |
    - 9.1.13.3. Molecular replacement (p. 227) | html | pdf |
    - 9.1.13.4. Definitive data for refinement of protein models (pp. 227-228) | html | pdf |
    - 9.1.13.5. A series of mutant or complex structures (p. 228) | html | pdf |
    - 9.1.13.6. Atomic resolution applications (p. 228) | html | pdf |
  - 9.1.14. The importance of low-resolution data (p. 228) | html | pdf |
  - 9.1.15. Data quality over the whole resolution range (pp. 228-229) | html | pdf |
  - 9.1.16. Strategies for automated data acquisition (p. 229) | html | pdf |
  - 9.1.17. Final remarks (p. 229) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 9.1.6.1. The Ewald-sphere construction (p. 213) | html | pdf |
    - Fig. 9.1.6.2. The plane of reflections in the reciprocal sphere that is approximately perpendicular to the X-ray beam gives rise to an ellipse of reflections on the detector (p. 213) | html | pdf |
    - Fig. 9.1.6.3. Schematic representation of beam divergence (δ) and crystal mosaicity (η) (p. 214) | html | pdf |
    - Fig. 9.1.6.4. A single lune on two consecutive exposures (p. 215) | html | pdf |
    - Fig. 9.1.6.5. Appearance of a lune for (left) a crystal of low mosaicity and (right) a highly mosaic crystal (p. 215) | html | pdf |
    - Fig. 9.1.6.6. The width of the lunes is proportional to the rotation range per image, Δφ, which increases from (a) to (c) (p. 216) | html | pdf |
    - Fig. 9.1.6.7. The largest allowed rotation range per exposure depends on the dimension of the primitive unit cell oriented along the X-ray beam; this is diminished by high mosaicity (p. 216) | html | pdf |
    - Fig. 9.1.6.8. If the crystal lattice is centred or if its orientation is non-axial, the reflections do not overlap in spite of overlapping lunes, as illustrated on the right with consecutive layers of reflections viewed from the side (p. 216) | html | pdf |
    - Fig. 9.1.7.1. Rotation of a triclinic crystal by 180° in the X-ray beam, represented as rotating the Ewald sphere with a stationary crystal, projected along the rotation axis (p. 218) | html | pdf |
    - Fig. 9.1.7.2. Rotation of a triclinic crystal by 135° is not sufficient to obtain totally complete data (p. 218) | html | pdf |
    - Fig. 9.1.7.3. After a 90° rotation out of a required 180°, the overall completeness is higher than 50% (p. 218) | html | pdf |
    - Fig. 9.1.7.4. For an orthorhombic crystal, a 90° rotation is sufficient provided the starting or final orientation is along the major axis (p. 219) | html | pdf |
    - Fig. 9.1.7.5. Rotation of an orthorhombic crystal by 90° between two diagonal orientations leaves a part of the reciprocal space unmeasured (p. 219) | html | pdf |
    - Fig. 9.1.7.6. For data containing an anomalous signal, when both Bijvoet mates have to be measured, 180° rotation of a triclinic crystal is not sufficient and at least an additional $[2\theta_{\max}]$ is required (p. 220) | html | pdf |
    - Fig. 9.1.7.7. Rotation by 360° leaves the part of the reciprocal space in the blind region unmeasured, since the reflections near the rotation axis do not cross the surface of the Ewald sphere (p. 220) | html | pdf |
    - Fig. 9.1.7.8. Dependence of the total fraction of reflections in the blind region on the resolution for three different wavelengths: 1.54, 1 and 0.71 Å (p. 220) | html | pdf |
    - Fig. 9.1.7.9. For shorter wavelengths the blind region is narrower, since the Ewald sphere is flatter (p. 220) | html | pdf |
    - Fig. 9.1.7.10. If the crystal has a symmetry axis, it should be skewed from the rotation axis by at least $[\theta_{\max}]$ to be able to collect the reflections equivalent to those in the blind region (p. 221) | html | pdf |
    - Fig. 9.1.10.1. Images recorded from a crystal of lysozyme (p. 223) | html | pdf |
  - Tables
    - Table 9.1.1.1. Size of the unit cell and number of reflections (p. 211) | html | pdf |
    - Table 9.1.7.1. Standard choice of asymmetric unit in reciprocal space for different point groups from the CCP4 program suite (p. 217) | html | pdf |
    - Table 9.1.7.2. Rotation range (°) required in different crystal classes (p. 219) | html | pdf |
    - Table 9.1.7.3. Space groups with alternative, non-equivalent indexing schemes (p. 221) | html | pdf |
- 9.2. Robotic crystal loading (pp. 231-233) | html | pdf | chapter contents |
  T. Earnest and C. Cork
  - 9.2.1. Introduction (p. 231) | html | pdf |
  - 9.2.2. Robotic sample loaders (pp. 231-233) | html | pdf |
  - 9.2.3. Conclusion (p. 233) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 9.2.2.1. (a) Hardware for the storage and transport of crystals (p. 232) | html | pdf |
    - Fig. 9.2.2.2. Crystal gripper assembly with low-force actuator (labelled `small move') (p. 232) | html | pdf |
- 9.3. X-ray diffraction imaging of whole cells (pp. 234-239) | html | pdf | chapter contents |
  D. Shapiro
  - 9.3.1. Introduction (pp. 234-235) | html | pdf |
  - 9.3.2. Phase retrieval from single-particle diffraction data (p. 235) | html | pdf |
  - 9.3.3. High-resolution imaging of yeast (pp. 235-237) | html | pdf |
    - 9.3.3.1. Radiation damage (pp. 236-237) | html | pdf |
    - 9.3.3.2. Low-dose three-dimensional imaging; low damage potential of stereoscopic viewing (p. 237) | html | pdf |
  - 9.3.4. Conclusions (pp. 237-238) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 9.3.1.1. First soft X-ray demonstration of the CXDM method (p. 234) | html | pdf |
    - Fig. 9.3.3.1. Diffraction pattern (left) and reconstruction (right) of a freeze-dried budding yeast cell (p. 236) | html | pdf |
    - Fig. 9.3.3.2. Exposure to ionizing radiation causes shrinkage of organic matter (p. 237) | html | pdf |
    - Fig. 9.3.3.3. Stereo image of a budding yeast cell (p. 238) | html | pdf |
  - Tables
    - Table 9.3.2.1. Summary of various algorithms (p. 235) | html | pdf |

Cryocrystallography
- 10.1. Introduction to cryocrystallography (pp. 241-248) | html | pdf | chapter contents |
  H. Hope and S. Parkin
  - 10.1.1. Cooling of biocrystals (pp. 241-242) | html | pdf |
    - 10.1.1.1. Physical chemistry of biocrystals (pp. 241-242) | html | pdf |
    - 10.1.1.2. Internal ice or phase transition (p. 242) | html | pdf |
    - 10.1.1.3. Removal of the solvent layer (p. 242) | html | pdf |
    - 10.1.1.4. Cooling rates (p. 242) | html | pdf |
  - 10.1.2. Beneficial effects of low temperature (pp. 242-244) | html | pdf |
    - 10.1.2.1. Suppression of radiation damage (pp. 242-243) | html | pdf |
    - 10.1.2.2. Mechanical stability of the crystal mount (p. 243) | html | pdf |
    - 10.1.2.3. Effect on resolution (p. 243) | html | pdf |
    - 10.1.2.4. Annealing of biocrystals (pp. 243-244) | html | pdf |
    - 10.1.2.5. Additional benefits from sub-77 K cooling with helium (p. 244) | html | pdf |
  - 10.1.3. Principles of cooling equipment (pp. 244-245) | html | pdf |
    - 10.1.3.1. Liquid-nitrogen-based cold gas supply (p. 244) | html | pdf |
    - 10.1.3.2. Liquid-helium-based cold gas supply (pp. 244-245) | html | pdf |
    - 10.1.3.3. Frost prevention (p. 245) | html | pdf |
  - 10.1.4. Operational considerations (pp. 245-247) | html | pdf |
    - 10.1.4.1. Dual-stream instruments (p. 245) | html | pdf |
    - 10.1.4.2. Electrically heated nozzle (pp. 245-246) | html | pdf |
    - 10.1.4.3. Temperature calibration (pp. 246-247) | html | pdf |
    - 10.1.4.4. Transfer of the crystal to the diffractometer (p. 247) | html | pdf |
    - 10.1.4.5. Automated robotic crystal handling (p. 247) | html | pdf |
  - 10.1.5. Concluding note (p. 247) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 10.1.4.1. Schematic drawing of a dual-stream setup with the streams parallel to the diffractometer φ axis (p. 245) | html | pdf |
    - Fig. 10.1.4.2. Schematic drawing of a dual-stream setup with the streams angled relative to the diffractometer φ axis (p. 245) | html | pdf |
    - Fig. 10.1.4.3. Schematic drawing of a single-stream setup with the stream parallel to the diffractometer φ axis (p. 246) | html | pdf |
    - Fig. 10.1.4.4. Schematic drawing of a single-stream setup with the stream angled relative to the diffractometer φ axis (p. 246) | html | pdf |
    - Fig. 10.1.4.5. A crystal in a helium stream at 8 K in a setup corresponding to Fig. 10.1.4.4 (p. 246) | html | pdf |
- 10.2. Cryocrystallography techniques and devices (pp. 249-255) | html | pdf | chapter contents |
  D. W. Rodgers
  - 10.2.1. Introduction (p. 249) | html | pdf |
  - 10.2.2. Crystal preparation (pp. 249-250) | html | pdf |
  - 10.2.3. Crystal mounting (pp. 250-252) | html | pdf |
  - 10.2.4. Flash cooling (pp. 252-253) | html | pdf |
  - 10.2.5. Transfer and storage (pp. 253-254) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 10.2.2.1. Recommended pathway for optimizing cryoprotectant conditions and flash cooling (p. 250) | html | pdf |
    - Fig. 10.2.3.1. Different crystal mounts for flash cooling and cryogenic data collection (p. 251) | html | pdf |
    - Fig. 10.2.3.2. Mounting a crystal in a loop (p. 251) | html | pdf |
    - Fig. 10.2.3.3. Photograph of a flash-cooled crystal mounted in a nylon loop (p. 251) | html | pdf |
    - Fig. 10.2.3.4. Arrangement for using the loop-mounting technique at non-cryogenic temperatures (p. 251) | html | pdf |
    - Fig. 10.2.4.1. Flash cooling a crystal in the cold gas stream from a cryostat (p. 252) | html | pdf |
    - Fig. 10.2.4.2. Flash cooling in a liquid cryogen (p. 253) | html | pdf |
    - Fig. 10.2.5.1. Transfer of the flash-cooled crystal and loop assembly to a goniometer using a cryovial (p. 253) | html | pdf |
    - Fig. 10.2.5.2. Transfer using an alternative device for achieving the correct magnetic mount orientation (p. 254) | html | pdf |
    - Fig. 10.2.5.3. Transfer using tongs (p. 254) | html | pdf |
  - Tables
    - Table 10.2.2.1. List of cryoprotectants used successfully for flash cooling macromolecular crystals (p. 249) | html | pdf |
    - Table 10.2.2.2. Methods for introducing the cryoprotectants needed for flash cooling (p. 249) | html | pdf |
- 10.3. Radiation damage (pp. 256-261) | html | pdf | chapter contents |
  E. F. Garman
  - 10.3.1. Introduction (p. 256) | html | pdf |
  - 10.3.2. Cryocrystallography as a mitigation strategy (pp. 256-257) | html | pdf |
  - 10.3.3. Characteristics of radiation damage at cryotemperatures (pp. 257-258) | html | pdf |
  - 10.3.4. Understanding radiation damage (pp. 258-259) | html | pdf |
  - 10.3.5. Mitigating and correcting for radiation damage (p. 259) | html | pdf |
  - 10.3.6. Using radiation damage (p. 260) | html | pdf |
  - 10.3.7. Open questions (p. 260) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 10.3.3.1. Global radiation-damage indicators as a function of dose for four holoferritin crystals (p. 257) | html | pdf |
    - Fig. 10.3.3.2. Specific structural damage inflicted on a cryocooled crystal of apoferritin during sequential data sets collected at ID14–4, ESRF (p. 258) | html | pdf |
    - Fig. 10.3.3.3. Photograph of a 400 µm neuraminidase crystal (subtype N9 from avian influenza isolated from a Noddy Tern) that has been irradiated on ID14–4 at the ESRF at 100 K and then allowed to warm to room temperature (p. 258) | html | pdf |
    - Fig. 10.3.4.1. Microspectrophotometer absorption spectra of native and ascorbate-soaked hen egg-white lysozyme crystals at 100 K (p. 259) | html | pdf |

Data processing
- 11.1. Automatic indexing of oscillation images (pp. 263-265) | html | pdf | chapter contents |
  M. G. Rossmann
  - 11.1.1. Introduction (p. 263) | html | pdf |
  - 11.1.2. The crystal orientation matrix (p. 263) | html | pdf |
  - 11.1.3. Fourier analysis of the reciprocal-lattice vector distribution when projected onto a chosen direction (pp. 263-264) | html | pdf |
  - 11.1.4. Exploring all possible directions to find a good set of basis vectors (p. 264) | html | pdf |
  - 11.1.5. The program (p. 265) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.1.3.1. Frequency distribution of the projected reciprocal-lattice vectors for a suitably chosen direction of a diffraction pattern from a fibritin crystal (p. 264) | html | pdf |
    - Fig. 11.1.3.2. Fourier analysis of the distribution shown in Fig. 11.1.3.1 (p. 264) | html | pdf |
- 11.2. Integration of macromolecular diffraction data (pp. 266-271) | html | pdf | chapter contents |
  A. G. W. Leslie
  - 11.2.1. Introduction (p. 266) | html | pdf |
  - 11.2.2. Prerequisites for accurate integration (p. 266) | html | pdf |
    - 11.2.2.1. Crystal parameters (p. 266) | html | pdf |
    - 11.2.2.2. Detector parameters (p. 266) | html | pdf |
  - 11.2.3. Methods of integration (pp. 266-267) | html | pdf |
  - 11.2.4. The measurement box (p. 267) | html | pdf |
  - 11.2.5. Integration by simple summation (pp. 267-268) | html | pdf |
    - 11.2.5.1. Determination of the best background plane (p. 267) | html | pdf |
      - 11.2.5.1.1. Outlier rejection (p. 267) | html | pdf |
    - 11.2.5.2. Evaluating the integrated intensity and standard deviation (pp. 267-268) | html | pdf |
    - 11.2.5.3. The effect of instrument or detector errors (p. 268) | html | pdf |
  - 11.2.6. Integration by profile fitting (pp. 268-271) | html | pdf |
    - 11.2.6.1. Forming the standard profiles (pp. 268-269) | html | pdf |
    - 11.2.6.2. Evaluation of the profile-fitted intensity (p. 269) | html | pdf |
    - 11.2.6.3. Modifications for very close spots (pp. 269-270) | html | pdf |
    - 11.2.6.4. Profile fitting very strong reflections (p. 270) | html | pdf |
    - 11.2.6.5. Profile fitting very weak reflections (p. 270) | html | pdf |
    - 11.2.6.6. Improvement provided by profile fitting weak reflections (p. 270) | html | pdf |
    - 11.2.6.7. Other benefits of profile fitting (pp. 270-271) | html | pdf |
      - 11.2.6.7.1. Incompletely resolved spots (p. 270) | html | pdf |
      - 11.2.6.7.2. Elimination of peak pixel outliers (pp. 270-271) | html | pdf |
      - 11.2.6.7.3. Estimation of overloaded reflections (p. 271) | html | pdf |
    - 11.2.6.8. Profile fitting partially recorded reflections (p. 271) | html | pdf |
    - 11.2.6.9. Systematic errors in profile-fitted intensities (p. 271) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.2.4.1. The measurement-box definition used in MOSFLM (p. 267) | html | pdf |
- 11.3. Integration, scaling, space-group assignment and post refinement (pp. 272-281) | html | pdf | chapter contents |
  W. Kabsch
  - 11.3.1. Introduction (p. 272) | html | pdf |
  - 11.3.2. Modelling rotation images (pp. 272-275) | html | pdf |
    - 11.3.2.1. Coordinate systems and parameters (p. 272) | html | pdf |
    - 11.3.2.2. Spot prediction (pp. 272-273) | html | pdf |
    - 11.3.2.3. Standard spot shape (p. 273) | html | pdf |
    - 11.3.2.4. Spot centroids and partiality (p. 273) | html | pdf |
    - 11.3.2.5. Localizing diffraction spots (pp. 273-274) | html | pdf |
    - 11.3.2.6. Basis extraction (p. 274) | html | pdf |
    - 11.3.2.7. Indexing (pp. 274-275) | html | pdf |
    - 11.3.2.8. Refinement (p. 275) | html | pdf |
  - 11.3.3. Integration (pp. 275-277) | html | pdf |
    - 11.3.3.1. Reflection mask (pp. 275-276) | html | pdf |
    - 11.3.3.2. Background (p. 276) | html | pdf |
    - 11.3.3.3. Standard profiles (p. 276) | html | pdf |
    - 11.3.3.4. Intensity estimation (pp. 276-277) | html | pdf |
  - 11.3.4. Scaling (p. 277) | html | pdf |
  - 11.3.5. Post refinement (pp. 277-278) | html | pdf |
  - 11.3.6. Space-group assignment (pp. 278-280) | html | pdf |
    - 11.3.6.1. Determination of the Bravais lattice (pp. 279-280) | html | pdf |
    - 11.3.6.2. Finding possible space groups (p. 280) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 11.3.6.1. Rating of lattice types implied by a given reduced cell (p. 279) | html | pdf |
    - Table 11.3.6.2. Identification of possible space groups (p. 280) | html | pdf |
- 11.4. DENZO and SCALEPACK (pp. 282-295) | html | pdf | chapter contents |
  Z. Otwinowski, W. Minor, D. Borek and M. Cymborowski
  - 11.4.1. Introduction (p. 282) | html | pdf |
  - 11.4.2. Diffraction from a perfect crystal lattice (pp. 282-283) | html | pdf |
  - 11.4.3. Autoindexing (pp. 283-284) | html | pdf |
    - 11.4.3.1. Lattice symmetry (pp. 283-284) | html | pdf |
    - 11.4.3.2. Lattice pseudosymmetry (p. 284) | html | pdf |
    - 11.4.3.3. Data-collection requirements (p. 284) | html | pdf |
    - 11.4.3.4. Misindexing (p. 284) | html | pdf |
    - 11.4.3.5. Twins (p. 284) | html | pdf |
  - 11.4.4. Coordinate systems (pp. 284-285) | html | pdf |
    - 11.4.4.1. Beam–gravity (p. 284) | html | pdf |
    - 11.4.4.2. Data (p. 284) | html | pdf |
    - 11.4.4.3. Beam–spindle (pp. 284-285) | html | pdf |
    - 11.4.4.4. Beam–2θ (p. 285) | html | pdf |
  - 11.4.5. Experimental assumptions (pp. 285-288) | html | pdf |
    - 11.4.5.1. Crystal diffraction (p. 286) | html | pdf |
    - 11.4.5.2. Data model (p. 286) | html | pdf |
    - 11.4.5.3. Data-model refinement (pp. 286-287) | html | pdf |
    - 11.4.5.4. Correlation between parameters (p. 287) | html | pdf |
    - 11.4.5.5. Single- and multiframe refinement (p. 287) | html | pdf |
    - 11.4.5.6. Active area (p. 287) | html | pdf |
    - 11.4.5.7. Flood field (p. 287) | html | pdf |
    - 11.4.5.8. Absolute configuration (p. 287) | html | pdf |
    - 11.4.5.9. Detector goniostat (p. 287) | html | pdf |
    - 11.4.5.10. Crystal goniostat (pp. 287-288) | html | pdf |
    - 11.4.5.11. Crystal orthogonalization convention (p. 288) | html | pdf |
    - 11.4.5.12. Refinement and calibration (p. 288) | html | pdf |
  - 11.4.6. Prediction of the diffraction pattern (pp. 288-289) | html | pdf |
    - 11.4.6.1. Refinement of crystal and detector parameters (p. 288) | html | pdf |
    - 11.4.6.2. Bragg's law for non-ideal conditions: mosaicity (pp. 288-289) | html | pdf |
    - 11.4.6.3. Detector distortions (p. 289) | html | pdf |
  - 11.4.7. Integration of diffraction maxima by profile fitting (p. 289) | html | pdf |
  - 11.4.8. Scaling – multiplicative corrections (pp. 289-291) | html | pdf |
    - 11.4.8.1. Global and local scaling (p. 290) | html | pdf |
    - 11.4.8.2. Stabilization of scaling parameters based on prior knowledge (pp. 290-291) | html | pdf |
  - 11.4.9. Global refinement or post refinement (p. 291) | html | pdf |
  - 11.4.10. Merging – assessment of the error model and signal magnitudes in the data (pp. 291-292) | html | pdf |
    - 11.4.10.1. Estimation of random errors (p. 291) | html | pdf |
    - 11.4.10.2. Estimation of multiplicative errors (p. 291) | html | pdf |
    - 11.4.10.3. Merging and signal validation (p. 292) | html | pdf |
  - 11.4.11. Detector diagnostics (p. 292) | html | pdf |
  - 11.4.12. HKL-2000 and HKL-3000 (pp. 292-294) | html | pdf |
  - 11.4.13. Final note (p. 294) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.4.12.1. General layout of HKL-3000 (p. 293) | html | pdf |
- 11.5. The use of partially recorded reflections for post refinement, scaling and averaging X-ray diffraction data (pp. 296-303) | html | pdf | chapter contents |
  C. G. van Beek, R. Bolotovsky and M. G. Rossmann
  - 11.5.1. Introduction (p. 296) | html | pdf |
  - 11.5.2. Generalization of the Hamilton, Rollett and Sparks equations to take into account partial reflections (pp. 296-297) | html | pdf |
  - 11.5.3. Selection of reflections useful for scaling (p. 297) | html | pdf |
  - 11.5.4. Restraints and constraints (pp. 297-298) | html | pdf |
  - 11.5.5. Generalization of the procedure for averaging reflection intensities (p. 298) | html | pdf |
  - 11.5.6. Estimating the quality of data scaling and averaging (p. 298) | html | pdf |
  - 11.5.7. Experimental results (pp. 298-301) | html | pdf |
    - 11.5.7.1. Variation of scale factors versus frame number (pp. 298-299) | html | pdf |
    - 11.5.7.2. R factor as a function of `sum-of-partialities' (method 1) (pp. 299-300) | html | pdf |
    - 11.5.7.3. Statistics for rejecting reflections and data quality as a function of frame number (p. 300) | html | pdf |
    - 11.5.7.4. Observed versus calculated partiality (p. 300) | html | pdf |
    - 11.5.7.5. Anisotropic mosaicity (p. 300) | html | pdf |
    - 11.5.7.6. Anomalous dispersion (pp. 300-301) | html | pdf |
  - 11.5.8. Conclusions (p. 301) | html | pdf |
  - Appendix 11.5.1. Partiality model (Rossmann, 1979; Rossmann et al., 1979) (pp. 301-302) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.5.7.1. Linear scale factors as a function of frame number for a φX174 data set (p. 299) | html | pdf |
    - Fig. 11.5.7.2. Linear scale factor as a function of frame number for an HRV14 data set (p. 299) | html | pdf |
    - Fig. 11.5.7.3. Linear scale factor determined by method 2 as a function of frame number for an SCP(114–264) data set (p. 299) | html | pdf |
    - Fig. 11.5.7.4. R factor as a function of the difference of calculated `sum-of-partialities' and unity for the estimates of full reflections when method 1 is used for the scaling and averaging of a φX174 data set (p. 300) | html | pdf |
    - Fig. 11.5.7.5. R factor per frame as a function of frame number for a φX174 data set (p. 300) | html | pdf |
    - Fig. 11.5.7.6. The observed partialities plotted against calculated partialities for a φX174 data set (p. 300) | html | pdf |
    - Fig. 11.5.7.7. Variation of (unconstrained) mosaicity for a monoclinic crystal of the bacterial virus alpha3 (p. 300) | html | pdf |
    - Fig. 11.5.7.8. Quality of anomalous-dispersion data for an SeMet derivative of dioxygenase Rieske ferredoxin (p. 301) | html | pdf |
  - Tables
    - Table 11.5.3.1. Hierarchy of criteria for selecting reflections for scaling and averaging procedures (p. 297) | html | pdf |
- 11.6. XDS (pp. 304-310) | html | pdf | chapter contents |
  W. Kabsch
  - 11.6.1. Functional specification (p. 304) | html | pdf |
  - 11.6.2. XDS (pp. 304-308) | html | pdf |
    - 11.6.2.1. XYCORR (p. 304) | html | pdf |
    - 11.6.2.2. INIT (pp. 304-305) | html | pdf |
    - 11.6.2.3. COLSPOT (p. 305) | html | pdf |
    - 11.6.2.4. IDXREF (pp. 305-306) | html | pdf |
    - 11.6.2.5. DEFPIX (p. 306) | html | pdf |
    - 11.6.2.6. XPLAN (pp. 306-307) | html | pdf |
    - 11.6.2.7. INTEGRATE (p. 307) | html | pdf |
    - 11.6.2.8. CORRECT (pp. 307-308) | html | pdf |
  - 11.6.3. XSCALE (pp. 308-309) | html | pdf |
  - 11.6.4. XDSCONV (p. 309) | html | pdf |
  - 11.6.5. Parallelization of XDS (pp. 309-310) | html | pdf |
  - 11.6.6. Availability (p. 310) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 11.6.2.1. Information exchange between program steps of XDS (p. 305) | html | pdf |
- 11.7. Detecting twinning by merohedry (pp. 311-316) | html | pdf | chapter contents |
  T. O. Yeates and Y. Tsai
  - 11.7.1. Introduction (p. 311) | html | pdf |
  - 11.7.2. Twinning by merohedry – considerations of lattice symmetry (pp. 311-312) | html | pdf |
  - 11.7.3. Considerations of length scale and effects in reciprocal space (p. 312) | html | pdf |
  - 11.7.4. Extent of twinning: the twin fraction (p. 312) | html | pdf |
  - 11.7.5. Indications of twinning (pp. 312-313) | html | pdf |
  - 11.7.6. Twinning tests based on overall intensity statistics (pp. 313-314) | html | pdf |
  - 11.7.7. Tests for partial twinning based on comparison of twin-related reflections (pp. 314-315) | html | pdf |
  - 11.7.8. Higher forms of twinning (p. 315) | html | pdf |
  - 11.7.9. Other kinds of disorder (p. 315) | html | pdf |
  - 11.7.10. Summary (p. 315) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.7.1.1. Hierarchy of multiple types of twinning (p. 311) | html | pdf |
    - Fig. 11.7.2.1. A cartoon depicting partial merohedral twinning in space group P4 (p. 311) | html | pdf |
    - Fig. 11.7.6.1. Detection of high or perfect twinning by analysing overall intensity statistics (p. 313) | html | pdf |
    - Fig. 11.7.7.1. Estimation of the twin fraction α based on the variable H (see text) (p. 314) | html | pdf |
  - Tables
    - Table 11.7.2.1. Symmetries in which twinning by merohedry can occur in biological macromolecules (p. 312) | html | pdf |
    - Table 11.7.6.1. Twinning statistics for acentric intensity data from a crystal specimen with different numbers of twin domain orientations (n) (p. 314) | html | pdf |

Isomorphous replacement
- 12.1. The preparation of heavy-atom derivatives of protein crystals for use in multiple isomorphous replacement and anomalous scattering (pp. 317-326) | html | pdf | chapter contents |
  D. Carvin, S. A. Islam, M. J. E. Sternberg and T. L. Blundell
  - 12.1.1. Introduction (p. 317) | html | pdf |
  - 12.1.2. Heavy-atom data bank (pp. 317-318) | html | pdf |
  - 12.1.3. Properties of heavy-atom compounds and their complexes (pp. 318-320) | html | pdf |
    - 12.1.3.1. Stability (p. 318) | html | pdf |
    - 12.1.3.2. Lability (p. 318) | html | pdf |
    - 12.1.3.3. Oxidation state of metal ions in protein crystals (p. 318) | html | pdf |
    - 12.1.3.4. Effect of pH (pp. 318-319) | html | pdf |
    - 12.1.3.5. Effect of precipitants and buffers on heavy-atom binding (p. 319) | html | pdf |
    - 12.1.3.6. Solubility of heavy-atom compounds (pp. 319-320) | html | pdf |
    - 12.1.3.7. Effect of concentration, time of soak and temperature on heavy-atom binding (p. 320) | html | pdf |
  - 12.1.4. Amino acids as ligands (pp. 320-321) | html | pdf |
  - 12.1.5. Protein chemistry of heavy-atom reagents (pp. 321-324) | html | pdf |
    - 12.1.5.1. Hard cations (p. 321) | html | pdf |
    - 12.1.5.2. Thallium and lead ions (p. 321) | html | pdf |
    - 12.1.5.3. B-metal reagents (pp. 321-323) | html | pdf |
    - 12.1.5.4. Electrostatic binding of heavy-atom anions (p. 323) | html | pdf |
    - 12.1.5.5. Hydrophobic heavy-atom reagents (pp. 323-324) | html | pdf |
    - 12.1.5.6. Iodine (p. 324) | html | pdf |
    - 12.1.5.7. Polynuclear reagents (p. 324) | html | pdf |
  - 12.1.6. Metal-ion replacement in metalloproteins (p. 324) | html | pdf |
  - 12.1.7. Analogues of amino acids (pp. 324-325) | html | pdf |
  - 12.1.8. Use of the heavy-atom data bank to select derivatives (p. 325) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 12.1.5.1. The binding site for uranyl ions in cytochrome b5 (oxidized: 3B5C) (p. 321) | html | pdf |
    - Fig. 12.1.5.2. Mercuric ions replace zinc in thermolysin (3TLN) (p. 322) | html | pdf |
    - Fig. 12.1.5.3. The binding of a silver ion to immunoglobulin Fab (2FB4) (p. 322) | html | pdf |
    - Fig. 12.1.5.4. The binding of $[\hbox{PtCl}_{4}^{2-}]$ through a methionine in azurin (1AZU) (p. 323) | html | pdf |
    - Fig. 12.1.5.5. The relative positions of methionine side chains (carbon: green; sulfur: yellow) in the parent crystals to the binding of platinum (pink) of $[\hbox{PtCl}_{4}^{2-}]$ (p. 323) | html | pdf |
    - Fig. 12.1.5.6. The relative positions of cystine disulfide bridges (carbon: green; sulfur: yellow) in the parent crystals to the binding of platinum (pink) of $[\hbox{PtCl}_{4}^{2-}]$ (p. 323) | html | pdf |
    - Fig. 12.1.5.7. The binding of $[\hbox{Pt(CN)}_{4}^{2-}]$ to aldose dehydrogenase (8ADH) (p. 323) | html | pdf |
    - Fig. 12.1.6.1. The displacement of calcium by samarium in thermolysin (p. 325) | html | pdf |
  - Tables
    - Table 12.1.3.1. Useful pH ranges of some heavy-atom reagents derived from the heavy-atom data bank (p. 319) | html | pdf |
    - Table 12.1.5.1. The 23 most commonly used heavy-atom reagents (p. 321) | html | pdf |
    - Table 12.1.5.2. The five most popular uranium derivatives (p. 321) | html | pdf |
    - Table 12.1.5.3. The five most popular mercury derivatives (p. 322) | html | pdf |
    - Table 12.1.5.4. The five most popular platinum derivatives (p. 322) | html | pdf |
- 12.2. Locating heavy-atom sites (pp. 327-332) | html | pdf | chapter contents |
  M. T. Stubbs and R. Huber
  - 12.2.1. The origin of the phase problem (pp. 327-328) | html | pdf |
  - 12.2.2. The Patterson function (pp. 328-329) | html | pdf |
  - 12.2.3. The difference Fourier (p. 329) | html | pdf |
  - 12.2.4. Reality (pp. 329-330) | html | pdf |
    - 12.2.4.1. Treatment of errors (pp. 329-330) | html | pdf |
    - 12.2.4.2. Automated search procedures (p. 330) | html | pdf |
  - 12.2.5. Special complications (pp. 330-331) | html | pdf |
    - 12.2.5.1. Lack of isomorphism (pp. 330-331) | html | pdf |
    - 12.2.5.2. Space-group problems (p. 331) | html | pdf |
    - 12.2.5.3. High levels of substitution; noncrystallographic symmetry (p. 331) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 12.2.1.1. Relationships in diffraction space (p. 327) | html | pdf |
    - Fig. 12.2.1.2. The effect of introducing a heavy atom or anomalous scatterer (p. 328) | html | pdf |
    - Fig. 12.2.2.1. The Patterson map with symmetry (p. 328) | html | pdf |
    - Fig. 12.2.2.2. The vector superposition method (p. 329) | html | pdf |
    - Fig. 12.2.4.1. The treatment of phase errors (p. 330) | html | pdf |

Molecular replacement
- 13.1. Noncrystallographic symmetry (pp. 333-339) | html | pdf | chapter contents |
  D. M. Blow
  - 13.1.1. Introduction (p. 333) | html | pdf |
  - 13.1.2. Definition of noncrystallographic symmetry (p. 333) | html | pdf |
    - 13.1.2.1. Standard noncrystallographic symmetry (p. 333) | html | pdf |
    - 13.1.2.2. Generalized noncrystallographic symmetry (p. 333) | html | pdf |
    - 13.1.2.3. Exploitation of noncrystallographic symmetry (p. 333) | html | pdf |
  - 13.1.3. Use of the Patterson function to interpret noncrystallographic symmetry (pp. 333-335) | html | pdf |
    - 13.1.3.1. Rotation operations (pp. 333-334) | html | pdf |
    - 13.1.3.2. Translation operations (pp. 334-335) | html | pdf |
  - 13.1.4. Interpretation of generalized noncrystallographic symmetry where the molecular structure is partially known (p. 335) | html | pdf |
    - 13.1.4.1. The cross-rotation function (p. 335) | html | pdf |
    - 13.1.4.2. The cross-translation function (p. 335) | html | pdf |
    - 13.1.4.3. Structure determination (p. 335) | html | pdf |
  - 13.1.5. The power of noncrystallographic symmetry in structure analysis (pp. 336-338) | html | pdf |
    - 13.1.5.1. Relevant parameters: standard case (p. 336) | html | pdf |
    - 13.1.5.2. Information gain from ideal noncrystallographic symmetry (pp. 336-337) | html | pdf |
    - 13.1.5.3. Information gain in the non-ideal case (p. 337) | html | pdf |
    - 13.1.5.4. Relevant parameters: generalized case (p. 337) | html | pdf |
    - 13.1.5.5. Noncrystallographic symmetry in atomic coordinate refinement (pp. 337-338) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 13.1.3.1. (a) A dimer in which the two subunits are related by arbitrary rotation and translation (p. 334) | html | pdf |
  - Tables
    - Table 13.1.2.1. Noncrystallographic symmetry in crystals (p. 333) | html | pdf |
    - Table 13.1.4.1. Structure determination using noncrystallographic symmetry (p. 335) | html | pdf |
- 13.2. Rotation functions (pp. 340-346) | html | pdf | chapter contents |
  J. Navaza
  - 13.2.1. Overview (p. 340) | html | pdf |
  - 13.2.2. Rotations in three-dimensional Euclidean space (pp. 340-341) | html | pdf |
    - 13.2.2.1. The metric of the rotation group (p. 341) | html | pdf |
  - 13.2.3. The rotation function (pp. 341-343) | html | pdf |
    - 13.2.3.1. Computing the rotation function (p. 342) | html | pdf |
    - 13.2.3.2. Plotting and sampling the rotation function (pp. 342-343) | html | pdf |
    - 13.2.3.3. Strategies (p. 343) | html | pdf |
    - 13.2.3.4. Symmetry properties of the rotation function (p. 343) | html | pdf |
  - 13.2.4. The locked rotation function (pp. 343-344) | html | pdf |
  - 13.2.5. Other rotation functions (p. 344) | html | pdf |
  - 13.2.6. Concluding remarks (p. 344) | html | pdf |
  - Appendix 13.2.1. Formulae for the derivation and computation of the fast rotation function (pp. 344-346) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 13.2.2.1. Illustration of rotations defined by (a) the spherical polar angles (χ, ω, φ); (b) the Euler angles (α, β, γ) (p. 340) | html | pdf |
- 13.3. Translation functions (pp. 347-351) | html | pdf | chapter contents |
  L. Tong
  - 13.3.1. Introduction (p. 347) | html | pdf |
  - 13.3.2. R-factor and correlation-coefficient translation functions (pp. 347-348) | html | pdf |
  - 13.3.3. Patterson-correlation translation function (p. 348) | html | pdf |
  - 13.3.4. Phased translation function (p. 349) | html | pdf |
  - 13.3.5. Packing check in translation functions (p. 349) | html | pdf |
  - 13.3.6. The unique region of a translation function (the Cheshire group) (p. 349) | html | pdf |
  - 13.3.7. Combined molecular replacement (pp. 349-350) | html | pdf |
  - 13.3.8. The locked translation function (p. 350) | html | pdf |
  - 13.3.9. Miscellaneous translation functions (p. 350) | html | pdf |
  - References | html | pdf |
- 13.4. Noncrystallographic symmetry averaging of electron density for molecular-replacement phase refinement and extension (pp. 352-363) | html | pdf | chapter contents |
  M. G. Rossmann and E. Arnold
  - 13.4.1. Introduction (p. 352) | html | pdf |
  - 13.4.2. Noncrystallographic symmetry (NCS) (pp. 352-354) | html | pdf |
  - 13.4.3. Phase determination using NCS (p. 354) | html | pdf |
  - 13.4.4. The p- and h-cells (pp. 354-355) | html | pdf |
  - 13.4.5. Combining crystallographic and noncrystallographic symmetry (pp. 355-356) | html | pdf |
    - 13.4.5.1. General considerations (p. 355) | html | pdf |
    - 13.4.5.2. Averaging with the p-cell (pp. 355-356) | html | pdf |
    - 13.4.5.3. Averaging the p-cell and placing the results into the h-cell (p. 356) | html | pdf |
  - 13.4.6. Determining the molecular envelope (pp. 356-357) | html | pdf |
  - 13.4.7. Finding the averaged density (pp. 357-358) | html | pdf |
  - 13.4.8. Interpolation (p. 358) | html | pdf |
  - 13.4.9. Combining different crystal forms (p. 358) | html | pdf |
  - 13.4.10. Phase extension and refinement of the NCS parameters (p. 359) | html | pdf |
  - 13.4.11. Convergence (pp. 359-360) | html | pdf |
  - 13.4.12. Ab initio phasing starts (p. 360) | html | pdf |
  - 13.4.13. Recent salient examples in low-symmetry cases: multidomain averaging and systematic applications of multiple-crystal-form averaging (pp. 360-361) | html | pdf |
  - 13.4.14. Programs (p. 361) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 13.4.2.1. The two-dimensional periodic design shows crystallographic twofold axes perpendicular to the page and local noncrystallographic rotation axes in the plane of the paper (design by Audrey Rossmann) (p. 352) | html | pdf |
    - Fig. 13.4.2.2. (a) NCS in a triclinic cell (p. 353) | html | pdf |
    - Fig. 13.4.2.3. The position of the twofold rotation axis which relates the two piglets is completely arbitrary (p. 353) | html | pdf |
    - Fig. 13.4.4.1. Stereographic projections showing alternative definitions of the `standard orientation' of an icosahedron in the h-cell (p. 355) | html | pdf |
    - Fig. 13.4.6.1. The volume of the molecular mask expressed as a percentage of the volume of the p-cell asymmetric unit, as determined by the density cutoff in the h-cell (p. 357) | html | pdf |
    - Fig. 13.4.8.1. Interpolation box for finding the approximate electron density at G(Δx, Δy, Δz), given the eight densities at the corners of the box (p. 358) | html | pdf |
    - Fig. 13.4.11.1. Plot of a correlation coefficient as the phases were extended from 8 to 3 Å resolution in the structure determination of Mengo virus (p. 359) | html | pdf |
    - Fig. 13.4.12.1. Structure amplitudes of the type II crystals of southern bean mosaic virus, averaged within shells of reciprocal space, shown in relation to the Fourier transform of a 284 Å diameter sphere (p. 360) | html | pdf |
  - Tables
    - Table 13.4.7.1. Mean root-mean-square scatter between noncrystallographically related points (p. 357) | html | pdf |
- 13.5. Molecular replacement with MOLREP (pp. 364-366) | html | pdf | chapter contents |
  A. Vagin and A. Teplyakov
  - 13.5.1. Introduction (p. 364) | html | pdf |
  - 13.5.2. Program operation (p. 364) | html | pdf |
  - 13.5.3. Preparation of the search model (p. 364) | html | pdf |
  - 13.5.4. Preparation of the X-ray data (pp. 364-365) | html | pdf |
  - 13.5.5. Rotational search (p. 365) | html | pdf |
  - 13.5.6. Positional search (p. 365) | html | pdf |
  - 13.5.7. Multi-copy search (pp. 365-366) | html | pdf |
  - 13.5.8. Fitting the model into electron density (p. 366) | html | pdf |
  - 13.5.9. Distribution (p. 366) | html | pdf |
  - References | html | pdf |

Anomalous dispersion
- 14.1. Heavy-atom location and phase determination with single-wavelength diffraction data (pp. 367-372) | html | pdf | chapter contents |
  B. W. Matthews
  - 14.1.1. Introduction (p. 367) | html | pdf |
  - 14.1.2. The isomorphous-replacement method (pp. 367-368) | html | pdf |
  - 14.1.3. The method of multiple isomorphous replacement (p. 368) | html | pdf |
  - 14.1.4. The method of Blow & Crick (pp. 368-369) | html | pdf |
  - 14.1.5. The best Fourier (p. 369) | html | pdf |
  - 14.1.6. Anomalous scattering (p. 369) | html | pdf |
  - 14.1.7. Theory of anomalous scattering (pp. 369-370) | html | pdf |
  - 14.1.8. The phase probability distribution for anomalous scattering (pp. 370-371) | html | pdf |
  - 14.1.9. Anomalous scattering without isomorphous replacement (p. 371) | html | pdf |
  - 14.1.10. Location of heavy-atom sites (p. 371) | html | pdf |
  - 14.1.11. Use of anomalous-scattering data in heavy-atom location (p. 371) | html | pdf |
  - 14.1.12. Use of difference Fourier syntheses (p. 371) | html | pdf |
  - 14.1.13. Single isomorphous replacement (pp. 371-372) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 14.1.2.1. (a) Harker construction for a single isomorphous replacement (p. 367) | html | pdf |
    - Fig. 14.1.3.1. (a) Harker construction for a double isomorphous replacement (p. 368) | html | pdf |
    - Fig. 14.1.4.1. Vector diagram illustrating the lack of closure, ɛ, of an isomorphous-replacement phase triangle (p. 368) | html | pdf |
    - Fig. 14.1.7.1. (a) Vector diagrams illustrating anomalous scattering for the reflections hkl and $[\overline{hkl}]$ (p. 369) | html | pdf |
    - Fig. 14.1.7.2. Harker construction for a single isomorphous replacement with anomalous scattering, in the absence of errors (p. 370) | html | pdf |
    - Fig. 14.1.8.1. Vector diagrams illustrating lack of closure in the anomalous-scattering method (p. 370) | html | pdf |
    - Fig. 14.1.8.2. Combination of isomorphous replacement and anomalous-scattering phase probabilities for a single isomorphous replacement (p. 370) | html | pdf |
    - Fig. 14.1.13.1. The consequences of using the incorrect hand for the heavy-atom arrangement in phase determination (p. 372) | html | pdf |
- 14.2. Multiwavelength anomalous diffraction (pp. 373-378) | html | pdf | chapter contents |
  J. L. Smith and W. A. Hendrickson
  - 14.2.1. Anomalous scattering factors (pp. 373-374) | html | pdf |
  - 14.2.2. A phase equation for MAD (pp. 374-375) | html | pdf |
  - 14.2.3. Diffraction ratios for estimating the MAD phasing signal (p. 375) | html | pdf |
  - 14.2.4. Experimental considerations (pp. 375-376) | html | pdf |
  - 14.2.5. Data handling (p. 376) | html | pdf |
  - 14.2.6. Approaches to MAD phasing (pp. 376-377) | html | pdf |
  - 14.2.7. Determination of the anomalous-scatterer partial structure (p. 377) | html | pdf |
  - 14.2.8. General anomalous-scatterer labels for biological macromolecules (pp. 377-378) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 14.2.1.1. Anomalous scattering factors for Se in a protein labelled with selenomethionine (p. 374) | html | pdf |
- 14.3. Automated MAD and MIR structure solution (pp. 379-383) | html | pdf | chapter contents |
  T. C. Terwilliger and J. Berendzen
  - 14.3.1. Introduction (p. 379) | html | pdf |
  - 14.3.2. MAD and MIR structure solution (p. 379) | html | pdf |
  - 14.3.3. Decision making and structure solution (p. 379) | html | pdf |
  - 14.3.4. The need for rapid refinement and phasing during automated structure solution (p. 379) | html | pdf |
  - 14.3.5. Conversion of MAD data to a pseudo-SIRAS form (pp. 379-380) | html | pdf |
  - 14.3.6. Scoring of trial heavy-atom solutions (pp. 380-381) | html | pdf |
  - 14.3.7. Automated MIR and MAD structure determination (pp. 381-382) | html | pdf |
  - 14.3.8. Generation of model X-ray data sets (p. 382) | html | pdf |
  - 14.3.9. Conclusions (p. 382) | html | pdf |
  - 14.3.10. Software availability (p. 382) | html | pdf |
  - References | html | pdf |

Density modification and phase combination
- 15.1. Phase improvement by iterative density modification (pp. 385-400) | html | pdf | chapter contents |
  K. Y. J. Zhang, K. D. Cowtan and P. Main
  - 15.1.1. Introduction (p. 385) | html | pdf |
  - 15.1.2. Density-modification methods (pp. 385-393) | html | pdf |
    - 15.1.2.1. Solvent flattening (pp. 385-388) | html | pdf |
      - 15.1.2.1.1. Introduction (pp. 386-387) | html | pdf |
      - 15.1.2.1.2. The automated convolution method for molecular-boundary identification (p. 387) | html | pdf |
      - 15.1.2.1.3. The solvent-flattening procedure (p. 388) | html | pdf |
    - 15.1.2.2. Histogram matching (pp. 388-390) | html | pdf |
      - 15.1.2.2.1. Introduction (p. 388) | html | pdf |
      - 15.1.2.2.2. The prediction of the ideal histogram (pp. 388-389) | html | pdf |
      - 15.1.2.2.3. The process of histogram matching (pp. 389-390) | html | pdf |
      - 15.1.2.2.4. Scaling the observed structure-factor amplitudes according to the ideal density histogram (p. 390) | html | pdf |
    - 15.1.2.3. Averaging (pp. 390-392) | html | pdf |
      - 15.1.2.3.1. Introduction (p. 390) | html | pdf |
      - 15.1.2.3.2. The determination of noncrystallographic symmetry (pp. 390-391) | html | pdf |
      - 15.1.2.3.3. The refinement of noncrystallographic symmetry (p. 391) | html | pdf |
      - 15.1.2.3.4. The averaging of NCS-related molecules (pp. 391-392) | html | pdf |
    - 15.1.2.4. Skeletonization (p. 392) | html | pdf |
    - 15.1.2.5. Sayre's equation (p. 392) | html | pdf |
      - 15.1.2.5.1. Sayre's equation in real and reciprocal space (p. 392) | html | pdf |
      - 15.1.2.5.2. The application of Sayre's equation to macromolecules at non-atomic resolution – the θ( $[{\bf h}]$ ) curve (p. 392) | html | pdf |
    - 15.1.2.6. Atomization (pp. 392-393) | html | pdf |
  - 15.1.3. Reciprocal-space interpretation of density modification (pp. 393-394) | html | pdf |
  - 15.1.4. Phase combination (pp. 394-396) | html | pdf |
    - 15.1.4.1. Sim and $[\sigma_{a}]$ weighting (pp. 394-395) | html | pdf |
    - 15.1.4.2. Reflection omit (p. 395) | html | pdf |
    - 15.1.4.3. The γ correction and solvent flipping (p. 395) | html | pdf |
    - 15.1.4.4. Resolution extrapolation (pp. 395-396) | html | pdf |
  - 15.1.5. Combining constraints for phase improvement (pp. 396-398) | html | pdf |
    - 15.1.5.1. The system of nonlinear constraint equations (p. 396) | html | pdf |
    - 15.1.5.2. Least-squares solution to the system of nonlinear constraint equations (pp. 396-398) | html | pdf |
      - 15.1.5.2.1. The conjugate-gradient method (p. 397) | html | pdf |
      - 15.1.5.2.2. The full-matrix solution (p. 397) | html | pdf |
      - 15.1.5.2.3. The diagonal approximation (pp. 397-398) | html | pdf |
  - 15.1.6. Statistical density-modification methods (p. 398) | html | pdf |
  - 15.1.7. Example (pp. 398-399) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 15.1.2.1. Density-modification calculation showing iterative application of real-space and reciprocal-space constraints (p. 385) | html | pdf |
    - Fig. 15.1.2.2. Solvent mask determined from a map by Wang's method (p. 387) | html | pdf |
    - Fig. 15.1.2.3. Transformation of density ρ to $[\rho'_{\rm mod}]$ by histogram matching (p. 389) | html | pdf |
    - Fig. 15.1.2.4. Types of noncrystallographic symmetry and averaging calculation (p. 391) | html | pdf |
    - Fig. 15.1.3.1. The functions $[g({\bf x})]$ and $[G({\bf h})]$ for solvent flattening, histogram matching and averaging (p. 393) | html | pdf |
    - Fig. 15.1.7.1. Phase correlations after different combinations of density modifications (p. 398) | html | pdf |
  - Tables
    - Table 15.1.2.1. Constraints used in density modification (p. 386) | html | pdf |
- 15.2. Model phases: probabilities, bias and maps (pp. 401-406) | html | pdf | chapter contents |
  R. J. Read
  - 15.2.1. Introduction (p. 401) | html | pdf |
  - 15.2.2. Model bias: importance of phase (p. 401) | html | pdf |
    - 15.2.2.1. Parseval's theorem (p. 401) | html | pdf |
  - 15.2.3. Structure-factor probability relationships (pp. 401-403) | html | pdf |
    - 15.2.3.1. Wilson and Sim structure-factor distributions in P1 (p. 402) | html | pdf |
    - 15.2.3.2. Probability distributions for variable coordinate errors (pp. 402-403) | html | pdf |
    - 15.2.3.3. General treatment of the structure-factor distribution (p. 403) | html | pdf |
    - 15.2.3.4. Estimating $[\sigma_{A}]$ (p. 403) | html | pdf |
    - 15.2.3.5. Accounting for measurement errors (p. 403) | html | pdf |
  - 15.2.4. Figure-of-merit weighting for model phases (p. 404) | html | pdf |
  - 15.2.5. Map coefficients to reduce model bias (p. 404) | html | pdf |
    - 15.2.5.1. Model bias in figure-of-merit weighted maps (p. 404) | html | pdf |
    - 15.2.5.2. Model bias in combined phase maps (p. 404) | html | pdf |
  - 15.2.6. Estimation of overall coordinate error (pp. 404-405) | html | pdf |
  - 15.2.7. Difference-map coefficients (p. 405) | html | pdf |
  - 15.2.8. Refinement bias (p. 405) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 15.2.2.1. Schematic illustration of the relative errors introduced by a random choice of phase or a random choice of amplitude (p. 401) | html | pdf |
    - Fig. 15.2.3.1. Centroid of the structure-factor contribution from a single atom (p. 402) | html | pdf |
    - Fig. 15.2.3.2. Schematic illustration of the general structure-factor distribution, relevant in the case of any set of independent random errors in the atomic model (p. 403) | html | pdf |
    - Fig. 15.2.4.1. Figure-of-merit weighted model-phased structure factor, obtained as the probability-weighted average over all possible phases (p. 404) | html | pdf |
- 15.3. DM/DMMULTI software for phase improvement by density modification (pp. 407-412) | html | pdf | chapter contents |
  K. D. Cowtan, K. Y. J. Zhang and P. Main
  - 15.3.1. Introduction (p. 407) | html | pdf |
  - 15.3.2. Program operation (p. 407) | html | pdf |
  - 15.3.3. Preparation of input data (pp. 407-408) | html | pdf |
  - 15.3.4. Choice of modes (pp. 408-410) | html | pdf |
    - 15.3.4.1. Density-modification modes (pp. 408-409) | html | pdf |
    - 15.3.4.2. Phase-combination modes (p. 409) | html | pdf |
    - 15.3.4.3. Phase-extension schemes (pp. 409-410) | html | pdf |
  - 15.3.5. Code description (pp. 410-412) | html | pdf |
    - 15.3.5.1. Scaling (pp. 410-411) | html | pdf |
    - 15.3.5.2. Solvent-mask determination (p. 411) | html | pdf |
    - 15.3.5.3. Averaging-mask determination (p. 411) | html | pdf |
    - 15.3.5.4. Fourier transforms (p. 411) | html | pdf |
    - 15.3.5.5. Histogram matching (p. 411) | html | pdf |
    - 15.3.5.6. Averaging (pp. 411-412) | html | pdf |
    - 15.3.5.7. Multi-crystal averaging (p. 412) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 15.3.3.1. (a) Input and output data for a DM calculation with no averaging (p. 408) | html | pdf |
    - Fig. 15.3.5.1. (a) Flow chart for a simple DM calculation with free-Sim phase combination (p. 410) | html | pdf |
    - Fig. 15.3.5.2. (a) Conceptual flowchart for a DMMULTI multi-crystal calculation (p. 411) | html | pdf |

Direct methods
- 16.1. Ab initio phasing (pp. 413-432) | html | pdf | chapter contents |
  G. M. Sheldrick, C. J. Gilmore, H. A. Hauptman, C. M. Weeks, R. Miller and I. Usón
  - 16.1.1. Introduction (pp. 413-415) | html | pdf |
    - 16.1.1.1. Data resolution (pp. 413-414) | html | pdf |
    - 16.1.1.2. Data completeness (p. 414) | html | pdf |
    - 16.1.1.3. Summary (pp. 414-415) | html | pdf |
  - 16.1.2. Normalized structure-factor magnitudes (pp. 415-416) | html | pdf |
    - 16.1.2.1. SIR differences (p. 416) | html | pdf |
    - 16.1.2.2. SAD differences (p. 416) | html | pdf |
    - 16.1.2.3. Difference intensities and direct methods (p. 416) | html | pdf |
  - 16.1.3. Starting the phasing process (pp. 416-417) | html | pdf |
    - 16.1.3.1. Structure invariants (pp. 416-417) | html | pdf |
    - 16.1.3.2. `Multisolution' methods and trial structures (p. 417) | html | pdf |
  - 16.1.4. Reciprocal-space phase refinement or expansion (shaking) (pp. 417-418) | html | pdf |
    - 16.1.4.1. The tangent formula (p. 417) | html | pdf |
    - 16.1.4.2. The minimal function (pp. 417-418) | html | pdf |
    - 16.1.4.3. Parameter shift (p. 418) | html | pdf |
  - 16.1.5. Real-space constraints (baking) (pp. 418-419) | html | pdf |
    - 16.1.5.1. Simple peak picking (p. 418) | html | pdf |
    - 16.1.5.2. Iterative peaklist optimization (pp. 418-419) | html | pdf |
    - 16.1.5.3. Random omit maps (p. 419) | html | pdf |
  - 16.1.6. Fourier refinement (p. 419) | html | pdf |
  - 16.1.7. Resolution enhancement: the `free lunch' algorithm (p. 419) | html | pdf |
  - 16.1.8. Utilizing Pattersons for better starts (pp. 419-420) | html | pdf |
  - 16.1.9. Shake-and-Bake: an analysis of a dual-space method in action (pp. 420-422) | html | pdf |
    - 16.1.9.1. Flowchart and program comparison (pp. 420-421) | html | pdf |
    - 16.1.9.2. Parameters and procedures (p. 421) | html | pdf |
    - 16.1.9.3. Recognizing solutions (pp. 421-422) | html | pdf |
  - 16.1.10. Applying dual-space programs successfully (pp. 422-425) | html | pdf |
    - 16.1.10.1. Avoiding false minima (pp. 422-423) | html | pdf |
    - 16.1.10.2. Choosing a refinement strategy (pp. 423-424) | html | pdf |
    - 16.1.10.3. Expansion to P1 (pp. 424-425) | html | pdf |
    - 16.1.10.4. Substructure applications (p. 425) | html | pdf |
  - 16.1.11. Substructure solution for native sulfurs and halide soaks (pp. 425-426) | html | pdf |
  - 16.1.12. Computer programs for dual-space phasing (pp. 426-429) | html | pdf |
    - 16.1.12.1. ACORN (pp. 426-427) | html | pdf |
    - 16.1.12.2. IL MILIONE (pp. 427-428) | html | pdf |
    - 16.1.12.3. SHELX (p. 428) | html | pdf |
    - 16.1.12.4. SnB and BnP (p. 428) | html | pdf |
    - 16.1.12.5. HySS (p. 428) | html | pdf |
    - 16.1.12.6. SUPERFLIP: charge flipping (pp. 428-429) | html | pdf |
    - 16.1.12.7. CRUNCH2 – Karle–Hauptman determinants (p. 429) | html | pdf |
  - 16.1.13. Conclusions and the grand challenge (p. 429) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 16.1.1.1. Averaged squared normalized structure-factor amplitudes over 700 protein structures with standard deviations calculated from the population of individual |E|² profiles (from Morris & Bricogne, 2003) (p. 413) | html | pdf |
    - Fig. 16.1.1.2. (a) Mean phase error as a function of resolution for the two independent ab initio SHELXD solutions of the previously unsolved protein hirustasin (p. 414) | html | pdf |
    - Fig. 16.1.3.1. The conditional probability distribution, $[P(\Phi_{\bf HK})]$ , of the three-phase structure invariants, $[\Phi_{\bf HK}]$ , having associated parameters A_HK with values of 0, 1, 2, 4 and 6 (p. 416) | html | pdf |
    - Fig. 16.1.9.1. A flowchart for the Shake-and-Bake procedure, which is implemented in both SnB and SHELXD (p. 420) | html | pdf |
    - Fig. 16.1.9.2. A histogram of figure-of-merit values (minimal function) for 378 scorpion toxin II trials (p. 421) | html | pdf |
    - Fig. 16.1.9.3. Tracing the history of a solution and a nonsolution trial for scorpion toxin II as a function of Shake-and-Bake cycle (p. 422) | html | pdf |
    - Fig. 16.1.10.1. Success rates for triclinic lysozyme are strongly influenced by the size of the parameter-shift angle (p. 423) | html | pdf |
    - Fig. 16.1.10.2. (a) Success rates and (b) cost effectiveness for several dual-space strategies as applied to a 148-atom P1 structure (p. 424) | html | pdf |
    - Fig. 16.1.10.3. Success rates for the 317-atom $[P2_{1}2_{1}2_{1}]$ structure of gramicidin A (p. 424) | html | pdf |
    - Fig. 16.1.11.1. Relative occupancy against peak number for SHELXD substructure solutions of elastase (p. 426) | html | pdf |
  - Tables
    - Table 16.1.1.1. Success rates for three P1 structures illustrate the importance of using complete data to the highest possible resolution (p. 415) | html | pdf |
    - Table 16.1.1.2. Improving success rates by `completing' the vancomycin data (p. 415) | html | pdf |
    - Table 16.1.2.1. Theoretical values pertaining to 's (p. 415) | html | pdf |
    - Table 16.1.8.1. Overall success rates for full structure solution for hirustasin using different two-atom search vectors chosen from the Patterson peak list (p. 420) | html | pdf |
    - Table 16.1.9.1. Recommended parameter values for the SnB program (p. 421) | html | pdf |
    - Table 16.1.10.1. Some large structures solved by the Shake-and-Bake method (p. 423) | html | pdf |
- 16.2. The maximum-entropy method (pp. 433-436) | html | pdf | chapter contents |
  G. Bricogne
  - 16.2.1. Introduction (p. 433) | html | pdf |
  - 16.2.2. The maximum-entropy principle in a general context (pp. 433-435) | html | pdf |
    - 16.2.2.1. Sources of random symbols and the notion of source entropy (p. 433) | html | pdf |
    - 16.2.2.2. The meaning of entropy: Shannon's theorems (pp. 433-434) | html | pdf |
    - 16.2.2.3. Jaynes' maximum-entropy principle (pp. 434-433) | html | pdf |
    - 16.2.2.4. Jaynes' maximum-entropy formalism (pp. 434-435) | html | pdf |
  - 16.2.3. Adaptation to crystallography (pp. 435-436) | html | pdf |
    - 16.2.3.1. The random-atom model (p. 435) | html | pdf |
    - 16.2.3.2. Conventional direct methods and their limitations (p. 435) | html | pdf |
    - 16.2.3.3. The notion of recentring and the maximum-entropy criterion (p. 435) | html | pdf |
    - 16.2.3.4. The crystallographic maximum-entropy formalism (p. 435) | html | pdf |
    - 16.2.3.5. Connection with the saddlepoint method (pp. 435-436) | html | pdf |
  - References | html | pdf |
- 16.3. Ab initio phasing of low-resolution Fourier syntheses (pp. 437-442) | html | pdf | chapter contents |
  V. Y. Lunin, A. G. Urzhumtsev and A. Podjarny
  - 16.3.1. Introduction (p. 437) | html | pdf |
  - 16.3.2. General features of low-resolution images (p. 437) | html | pdf |
  - 16.3.3. Low-resolution phasing (pp. 437-438) | html | pdf |
  - 16.3.4. Phase generation and selection (pp. 438-439) | html | pdf |
    - 16.3.4.1. Generation of the phase sets (p. 438) | html | pdf |
    - 16.3.4.2. Search targets – overview (p. 438) | html | pdf |
    - 16.3.4.3. Histogram of a Fourier synthesis (p. 438) | html | pdf |
    - 16.3.4.4. Map connectivity (p. 438) | html | pdf |
    - 16.3.4.5. Few-atoms model approach (p. 439) | html | pdf |
    - 16.3.4.6. Likelihood-based selection (p. 439) | html | pdf |
    - 16.3.4.7. Binary functions (p. 439) | html | pdf |
    - 16.3.4.8. Common features of selection criteria (p. 439) | html | pdf |
  - 16.3.5. Processing of the output (pp. 439-441) | html | pdf |
    - 16.3.5.1. Formal comparison of phase sets (pp. 439-440) | html | pdf |
    - 16.3.5.2. Phase ambiguity and alignment of phase sets (p. 440) | html | pdf |
    - 16.3.5.3. Multiple alignment and `central' phase set (p. 440) | html | pdf |
    - 16.3.5.4. Phase averaging and assignment of the probability distribution (pp. 440-441) | html | pdf |
    - 16.3.5.5. Cluster analysis (p. 441) | html | pdf |
  - 16.3.6. Conclusions and examples (p. 441) | html | pdf |
  - References | html | pdf |

Model building and computer graphics
- 17.1. Macromolecular model building and validation using Coot (pp. 443-447) | html | pdf | chapter contents |
  P. Emsley, B. Lohkamp and K. Cowtan
  - 17.1.1. Introduction (p. 443) | html | pdf |
  - 17.1.2. Model building (pp. 443-445) | html | pdf |
    - 17.1.2.1. Tools for general model building (pp. 443-444) | html | pdf |
      - 17.1.2.1.1. Cα baton mode (p. 443) | html | pdf |
      - 17.1.2.1.2. Find secondary structure (pp. 443-444) | html | pdf |
      - 17.1.2.1.3. Place helix here and Place strand here (p. 444) | html | pdf |
      - 17.1.2.1.4. Find ligands (p. 444) | html | pdf |
    - 17.1.2.2. Rebuilding and refinement (p. 444) | html | pdf |
    - 17.1.2.3. Tools for moving existing atoms (pp. 444-445) | html | pdf |
      - 17.1.2.3.1. Real-space refine zone (p. 444) | html | pdf |
      - 17.1.2.3.2. Sphere refinement (p. 444) | html | pdf |
      - 17.1.2.3.3. Ramachandran restraints (p. 444) | html | pdf |
      - 17.1.2.3.4. Rotamer tools (pp. 444-445) | html | pdf |
      - 17.1.2.3.5. Torsion editing (p. 445) | html | pdf |
    - 17.1.2.4. Tools for adding atoms to the model (p. 445) | html | pdf |
      - 17.1.2.4.1. Find waters (p. 445) | html | pdf |
      - 17.1.2.4.2. Add terminal residue (p. 445) | html | pdf |
    - 17.1.2.5. Tools for handling noncrystallographic symmetry (NCS) (p. 445) | html | pdf |
  - 17.1.3. Validation (pp. 445-446) | html | pdf |
    - 17.1.3.1. Ramachandran plot (p. 446) | html | pdf |
    - 17.1.3.2. Geometry analysis (p. 446) | html | pdf |
    - 17.1.3.3. Peptide $[\omega]$ analysis (p. 446) | html | pdf |
    - 17.1.3.4. Rotamer analysis (p. 446) | html | pdf |
    - 17.1.3.5. Density-fit analysis (p. 446) | html | pdf |
  - 17.1.4. Scripting (p. 446) | html | pdf |
  - 17.1.5. Discussion (p. 446) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 17.1.1.1. The Coot main window (p. 443) | html | pdf |
    - Fig. 17.1.3.1. A typical validation graph (p. 445) | html | pdf |
    - Fig. 17.1.3.2. Interactive Ramachandran plot (p. 446) | html | pdf |
- 17.2. Molecular graphics and animation (pp. 448-458) | html | pdf | chapter contents |
  A. J. Olson
  - 17.2.1. Introduction (p. 448) | html | pdf |
  - 17.2.2. Background – the evolution of molecular graphics hardware and software (pp. 448-449) | html | pdf |
  - 17.2.3. Representation and visualization of molecular data and models (pp. 449-454) | html | pdf |
    - 17.2.3.1. Geometric representation (pp. 450-452) | html | pdf |
    - 17.2.3.2. Volumetric representation (pp. 452-454) | html | pdf |
    - 17.2.3.3. Information visualization (p. 454) | html | pdf |
  - 17.2.4. Presentation graphics (pp. 454-457) | html | pdf |
    - 17.2.4.1. Illustration (pp. 455-456) | html | pdf |
    - 17.2.4.2. Animation (p. 456) | html | pdf |
    - 17.2.4.3. The return of physical models (pp. 456-457) | html | pdf |
  - 17.2.5. Looking ahead (p. 457) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 17.2.1.1. Model of a crystal structure proposed by René Häuy (p. 448) | html | pdf |
    - Fig. 17.2.2.1. One bay of X-RAC showing coefficient panels and the display oscilloscope (p. 448) | html | pdf |
    - Fig. 17.2.3.1. ORTEP plot of phenylhydroxynorbornanone showing atomic thermal ellipsoids (p. 449) | html | pdf |
    - Fig. 17.2.3.2. Ribbon diagram of actin monomer (PDB code: 1atn) (Kabsch et al., 1990) (p. 450) | html | pdf |
    - Fig. 17.2.3.3. Simple bonding diagram of a DNA structure (PDB code: 140D) (p. 450) | html | pdf |
    - Fig. 17.2.3.4. CPK representation of the same DNA structure as in Fig. 17.2.3.3 (p. 451) | html | pdf |
    - Fig. 17.2.3.5. Solvent-excluded surface of the DNA structure using a water probe radius of 1.5 Å (p. 451) | html | pdf |
    - Fig. 17.2.3.6. Hydrophobicity mapped onto a molecular surface (p. 452) | html | pdf |
    - Fig. 17.2.3.7. Crystallographic electron-density isosurfaces, showing details of a protein iron–sulfur cluster (p. 453) | html | pdf |
    - Fig. 17.2.3.8. A difference-electron-density map of a minor-groove drug binding in DNA (p. 453) | html | pdf |
    - Fig. 17.2.3.9. A difference distance matrix plot of the α₁–β₂ interface of haemoglobin in the T to R transformation (p. 454) | html | pdf |
    - Fig. 17.2.4.1. Line-art molecular illustration (p. 455) | html | pdf |
    - Fig. 17.2.4.2. A stereolithographic model of betalactamase inhibitory protein (BLIP) (p. 455) | html | pdf |
    - Fig. 17.2.5.1. This image represents a volume of blood plasma 750 Å on a side (p. 456) | html | pdf |

Refinement
- 18.1. Introduction to refinement (pp. 459-465) | html | pdf | chapter contents |
  L. F. Ten Eyck and K. D. Watenpaugh
  - 18.1.1. Overview (p. 459) | html | pdf |
  - 18.1.2. Background (p. 459) | html | pdf |
  - 18.1.3. Objectives (p. 459) | html | pdf |
  - 18.1.4. Least squares and maximum likelihood (p. 460) | html | pdf |
  - 18.1.5. Optimization (p. 460) | html | pdf |
  - 18.1.6. Data (p. 460) | html | pdf |
  - 18.1.7. Models (pp. 461-462) | html | pdf |
  - 18.1.8. Optimization methods (pp. 462-463) | html | pdf |
    - 18.1.8.1. Solving the refinement equations (pp. 462-463) | html | pdf |
    - 18.1.8.2. Normal equations (p. 463) | html | pdf |
    - 18.1.8.3. Choice of optimization method (p. 463) | html | pdf |
    - 18.1.8.4. Singularity in refinement (p. 463) | html | pdf |
  - 18.1.9. Evaluation of the model (p. 464) | html | pdf |
    - 18.1.9.1. Examination of outliers in the model (p. 464) | html | pdf |
    - 18.1.9.2. Examination of model electron density (p. 464) | html | pdf |
    - 18.1.9.3. R and R_free (p. 464) | html | pdf |
  - 18.1.10. Conclusion (p. 464) | html | pdf |
  - References | html | pdf |
- 18.2. Enhanced macromolecular refinement by simulated annealing (pp. 466-473) | html | pdf | chapter contents |
  A. T. Brunger, P. D. Adams and L. M. Rice
  - 18.2.1. Introduction (p. 466) | html | pdf |
  - 18.2.2. Cross validation (pp. 466-467) | html | pdf |
  - 18.2.3. The target function (pp. 467-468) | html | pdf |
    - 18.2.3.1. X-ray diffraction data versus model (pp. 467-468) | html | pdf |
    - 18.2.3.2. A priori chemical information (p. 468) | html | pdf |
  - 18.2.4. Searching conformational space (pp. 468-470) | html | pdf |
    - 18.2.4.1. Molecular dynamics (p. 469) | html | pdf |
    - 18.2.4.2. Temperature control (pp. 469-470) | html | pdf |
    - 18.2.4.3. Annealing schedules (p. 470) | html | pdf |
    - 18.2.4.4. An intuitive explanation of simulated annealing (p. 470) | html | pdf |
  - 18.2.5. Examples (pp. 470-471) | html | pdf |
  - 18.2.6. Multi-start refinement and structure-factor averaging (p. 471) | html | pdf |
  - 18.2.7. Ensemble models (pp. 471-472) | html | pdf |
  - 18.2.8. Conclusions (p. 472) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.2.2.1. Effect of resolution on coordinate-error estimates (p. 467) | html | pdf |
    - Fig. 18.2.3.1. The Gaussian probability distribution forms the basis of maximum-likelihood targets in crystallographic refinement (p. 467) | html | pdf |
    - Fig. 18.2.4.1. Illustration of simulated annealing for minimization of a one-dimensional function (p. 469) | html | pdf |
    - Fig. 18.2.5.1. Simulated annealing produces better models than extensive conjugate-gradient minimization (p. 470) | html | pdf |
    - Fig. 18.2.5.2. Maximum-likelihood targets significantly decrease model bias in simulated-annealing refinement (p. 471) | html | pdf |
- 18.3. Structure quality and target parameters (pp. 474-484) | html | pdf | chapter contents |
  R. A. Engh and R. Huber
  - 18.3.1. Purpose of restraints (p. 474) | html | pdf |
    - 18.3.1.1. Utility of restraints: protein/special geometries (p. 474) | html | pdf |
    - 18.3.1.2. Risk of restraints: bias, lack of cross validation (p. 474) | html | pdf |
  - 18.3.2. Formulation of refinement restraints (pp. 475-483) | html | pdf |
    - 18.3.2.1. Choice of properties for restraint (p. 475) | html | pdf |
    - 18.3.2.2. Simple derivation of force constants from parameter distributions (pp. 475-477) | html | pdf |
      - 18.3.2.2.1. Clustering (pp. 475-477) | html | pdf |
      - 18.3.2.2.2. Treatment of outliers (p. 477) | html | pdf |
    - 18.3.2.3. Bonds and angles (pp. 477-481) | html | pdf |
      - 18.3.2.3.1. Peptide parameters: proline, glycine, alanine and CB substitution (pp. 477-478) | html | pdf |
      - 18.3.2.3.2. Aromatic residues: tryptophan, phenylalanine, tyrosine, histidine (pp. 480-481) | html | pdf |
      - 18.3.2.3.3. Aliphatic residues: leucine, isoleucine, valine (p. 481) | html | pdf |
      - 18.3.2.3.4. Neutral polar residues: serine, threonine, glutamine, asparagine (p. 481) | html | pdf |
      - 18.3.2.3.5. Acidic residues: glutamate, aspartate (p. 481) | html | pdf |
      - 18.3.2.3.6. Basic residues: arginine, lysine (p. 481) | html | pdf |
      - 18.3.2.3.7. Sulfur-containing residues: methionine, cysteine, disulfides (p. 481) | html | pdf |
    - 18.3.2.4. Planarity restraints (pp. 481-482) | html | pdf |
    - 18.3.2.5. Torsion angles (p. 482) | html | pdf |
    - 18.3.2.6. Non-bonded interactions (p. 482) | html | pdf |
    - 18.3.2.7. Effects of hydrogen atoms in parameterization (p. 482) | html | pdf |
    - 18.3.2.8. Special geometries: cofactors, ligands, metals etc. (pp. 482-483) | html | pdf |
    - 18.3.2.9. Addition of tailored information sources (p. 483) | html | pdf |
  - 18.3.3. Strategy of application during building/refinement (p. 483) | html | pdf |
    - 18.3.3.1. Confidence in restraints versus information from diffraction (p. 483) | html | pdf |
  - 18.3.4. Future perspectives (p. 483) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.3.2.1. Torsion dependence of proline angle geometry (p. 478) | html | pdf |
    - Fig. 18.3.2.2. Bimodal distributions for tyrosine (p. 478) | html | pdf |
    - Fig. 18.3.2.3. Tryptophan $[\chi_{2}]$ dihedral angle distribution (p. 481) | html | pdf |
  - Tables
    - Table 18.3.2.1. Bond lengths of standard amino-acid side chains (pp. 476-477) | html | pdf |
    - Table 18.3.2.2. Bond angles of standard amino-acid side chains (pp. 479-480) | html | pdf |
    - Table 18.3.2.3. Bond lengths (Å) and angles (°) of peptide backbone fragments (p. 482) | html | pdf |
- 18.4. Refinement at atomic resolution (pp. 485-498) | html | pdf | chapter contents |
  Z. Dauter, G. N. Murshudov and K. S. Wilson
  - 18.4.1. The atomic model and a definition of atomic resolution (pp. 485-487) | html | pdf |
    - 18.4.1.1. The atomic model (p. 485) | html | pdf |
    - 18.4.1.2. What is `atomic resolution'? (pp. 486-487) | html | pdf |
    - 18.4.1.3. A theoretical approach to `atomic resolution' (p. 487) | html | pdf |
  - 18.4.2. Data (pp. 487-488) | html | pdf |
    - 18.4.2.1. Data quality (pp. 487-488) | html | pdf |
    - 18.4.2.2. Anisotropic scaling (p. 488) | html | pdf |
  - 18.4.3. Computational algorithms and strategies (pp. 488-489) | html | pdf |
    - 18.4.3.1. Classical least-squares refinement of small molecules (p. 488) | html | pdf |
    - 18.4.3.2. Least-squares refinement of large structures (pp. 488-489) | html | pdf |
    - 18.4.3.3. Fast Fourier transform (p. 489) | html | pdf |
    - 18.4.3.4. Maximum likelihood (p. 489) | html | pdf |
    - 18.4.3.5. Twinning (p. 489) | html | pdf |
    - 18.4.3.6. Computer power (p. 489) | html | pdf |
  - 18.4.4. Computational options and tactics (pp. 489-491) | html | pdf |
    - 18.4.4.1. Use of F (amplitudes) or F² (intensities) (pp. 489-490) | html | pdf |
    - 18.4.4.2. Restraints on coordinates and ADPs (p. 490) | html | pdf |
    - 18.4.4.3. Partial occupancy (pp. 490-491) | html | pdf |
    - 18.4.4.4. Validation of extra parameters during the refinement process (p. 491) | html | pdf |
  - 18.4.5. Features in the refined model (pp. 491-495) | html | pdf |
    - 18.4.5.1. Hydrogen atoms (pp. 491-492) | html | pdf |
    - 18.4.5.2. Anisotropic atomic displacement parameters (p. 492) | html | pdf |
    - 18.4.5.3. Alternative conformations (p. 492) | html | pdf |
    - 18.4.5.4. Ordered solvent water (p. 493) | html | pdf |
    - 18.4.5.5. Automatic location of water sites (p. 493) | html | pdf |
    - 18.4.5.6. Bulk solvent and the low-resolution reflections (pp. 493-494) | html | pdf |
    - 18.4.5.7. Metal ions and other ligands in the solvent (p. 494) | html | pdf |
    - 18.4.5.8. Deformation density (pp. 494-495) | html | pdf |
  - 18.4.6. Quality assessment of the model (p. 495) | html | pdf |
  - 18.4.7. Relation to biological chemistry (pp. 495-496) | html | pdf |
  - 18.4.8. Practical strategies (p. 496) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.4.1.1. The thermal-ellipsoid model used to represent anisotropic atomic displacement, with major axes indicated (p. 485) | html | pdf |
    - Fig. 18.4.1.2. Histograms of B values for a protein structure, Micrococcus lysodecticus catalase (Murshudov et al., 1999), for two different crystals which diffracted to different limiting resolutions (p. 487) | html | pdf |
    - Fig. 18.4.5.1. (a), (b) Representative electron-density maps for the refinement of Clostridium acidurici ferredoxin at 0.94 Å resolution (Dauter, Wilson et al., 1997) (p. 491) | html | pdf |
    - Fig. 18.4.5.2. Schematic representation of the bulk-solvent models described in the text (p. 494) | html | pdf |
  - Tables
    - Table 18.4.1.1. The parameters of an atomic model (p. 485) | html | pdf |
    - Table 18.4.1.2. Features which can be seen in the electron density at different resolutions (p. 486) | html | pdf |
- 18.5. Coordinate uncertainty (pp. 499-511) | html | pdf | chapter contents |
  D. W. J. Cruickshank
  - 18.5.1. Introduction (pp. 499-500) | html | pdf |
    - 18.5.1.1. Background (p. 499) | html | pdf |
    - 18.5.1.2. Accuracy and precision (p. 499) | html | pdf |
    - 18.5.1.3. Effect of atomic displacement parameters (or `temperature factors') (pp. 499-500) | html | pdf |
  - 18.5.2. The least-squares method (pp. 500-501) | html | pdf |
    - 18.5.2.1. The normal equations (p. 500) | html | pdf |
    - 18.5.2.2. Weights (pp. 500-501) | html | pdf |
    - 18.5.2.3. Statistical descriptors and goodness of fit (p. 501) | html | pdf |
  - 18.5.3. Restrained refinement (pp. 501-502) | html | pdf |
    - 18.5.3.1. Residual function (p. 501) | html | pdf |
    - 18.5.3.2. A very simple protein model (pp. 501-502) | html | pdf |
    - 18.5.3.3. Relative weighting of diffraction and restraint terms (p. 502) | html | pdf |
  - 18.5.4. Two examples of full-matrix inversion (pp. 502-505) | html | pdf |
    - 18.5.4.1. Unrestrained and restrained inversions for concanavalin A (pp. 502-504) | html | pdf |
    - 18.5.4.2. Unrestrained inversion for an immunoglobulin (p. 504) | html | pdf |
    - 18.5.4.3. Comments on restrained refinement (pp. 504-505) | html | pdf |
    - 18.5.4.4. Full-matrix estimates of precision (p. 505) | html | pdf |
  - 18.5.5. Approximate methods (pp. 505-506) | html | pdf |
    - 18.5.5.1. Block calculations (p. 505) | html | pdf |
    - 18.5.5.2. The modified Fourier method (p. 505) | html | pdf |
    - 18.5.5.3. Application of the modified Fourier method (pp. 505-506) | html | pdf |
  - 18.5.6. The diffraction-component precision index (pp. 506-507) | html | pdf |
    - 18.5.6.1. Statistical expectation of error dependence (p. 506) | html | pdf |
    - 18.5.6.2. A simple error formula (p. 506) | html | pdf |
    - 18.5.6.3. Extension for low-resolution structures and use of R_free (pp. 506-507) | html | pdf |
    - 18.5.6.4. Position error (p. 507) | html | pdf |
  - 18.5.7. Examples of the diffraction-component precision index (pp. 507-509) | html | pdf |
    - 18.5.7.1. Full-matrix comparison with the diffraction-component precision index (p. 507) | html | pdf |
    - 18.5.7.2. Further examples of the DPI using R (pp. 507-508) | html | pdf |
    - 18.5.7.3. Examples of the DPI using R_free (p. 508) | html | pdf |
    - 18.5.7.4. Comments on the diffraction-component precision index (pp. 508-509) | html | pdf |
  - 18.5.8. Luzzati plots (pp. 509-510) | html | pdf |
    - 18.5.8.1. Luzzati's theory (p. 509) | html | pdf |
    - 18.5.8.2. Statistical reinterpretation of Luzzati plots (pp. 509-510) | html | pdf |
    - 18.5.8.3. Comments on Luzzati plots (p. 510) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.5.4.1. Plots of $[\sigma (r)]$ versus $[B_{\rm eq}]$ for concanavalin A with 0.94 Å data, (a) restrained full-matrix $[\sigma_{\rm res}(r)]$ , (b) unrestrained full-matrix $[\sigma_{\rm diff}(r)]$ (p. 503) | html | pdf |
    - Fig. 18.5.4.2. Plots of $[\sigma (l)]$ versus average $[B_{\rm eq}]$ for concanavalin A with 0.94 Å data, (a) restrained full-matrix $[\sigma_{\rm res}(l)]$ , (b) unrestrained full-matrix $[\sigma_{\rm diff}(l)]$ (p. 503) | html | pdf |
    - Fig. 18.5.4.3. Plot of $[\sigma_{\rm diff}(r)]$ versus $[B_{\rm eq}]$ from an unrestrained full matrix for immunoglobulin mutant (T39K) with 1.70 Å data (p. 504) | html | pdf |
    - Fig. 18.5.4.4. Plot of $[\sigma_{\rm diff}(l)]$ versus average $[B_{\rm eq}]$ from an unrestrained full matrix for immunoglobulin mutant (T39K) with 1.70 Å data (p. 504) | html | pdf |
    - Fig. 18.5.8.1. Luzzati plots showing the refined R factor as a function of resolution for 1TGI (solid squares) and 1TGF (open squares) (Daopin et al., 1994) (p. 509) | html | pdf |
  - Tables
    - Table 18.5.7.1. Comparison of full-matrix $[\sigma (r, B_{\rm avg})]$ with the diffraction-component precision index (DPI) (p. 507) | html | pdf |
    - Table 18.5.7.2. Examples of diffraction-component precision indices (DPIs) (p. 507) | html | pdf |
    - Table 18.5.7.3. Comparison of DPIs using R and R_free (p. 508) | html | pdf |
    - Table 18.5.8.1. $[R = \langle |\Delta F|\rangle / \langle |F|\rangle]$ as a function of $[s\langle \Delta r\rangle]$ in the Luzzati model for three-dimensional noncentrosymmetric structures $[(s=2\sin\theta/\lambda)]$ (p. 509) | html | pdf |
- 18.6. CNS, a program system for structure-determination and refinement (pp. 512-519) | html | pdf | chapter contents |
  A. T. Brunger, P. D. Adams, W. L. DeLano, P. Gros, R. W. Grosse-Kunstleve, J.-S. Jiang, N. S. Pannu, R. J. Read, L. M. Rice and T. Simonson
  - 18.6.1. Introduction (p. 512) | html | pdf |
  - 18.6.2. The CNS language (pp. 512-513) | html | pdf |
  - 18.6.3. Symbols and parameters (p. 513) | html | pdf |
  - 18.6.4. Statistical functions (pp. 513-514) | html | pdf |
  - 18.6.5. Symbolic target function (pp. 514-515) | html | pdf |
  - 18.6.6. Modules and procedures (pp. 515-516) | html | pdf |
  - 18.6.7. Task files (p. 516) | html | pdf |
  - 18.6.8. HTML interface (pp. 516-517) | html | pdf |
  - 18.6.9. Example: combined maximum-likelihood and simulated-annealing refinement (p. 517) | html | pdf |
  - 18.6.10. Conclusions (p. 517) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.6.1.1. CNS consists of five layers which are under user control (p. 512) | html | pdf |
    - Fig. 18.6.3.1. Examples of compound symbols and compound parameters (p. 513) | html | pdf |
    - Fig. 18.6.4.1. Example for statistical operations provided by the CNS language (p. 513) | html | pdf |
    - Fig. 18.6.5.1. Examples of symbolic definition of a refinement target function and its derivatives with respect to the calculated structure-factor arrays (p. 514) | html | pdf |
    - Fig. 18.6.6.1. Use of compound parameters within a module (p. 515) | html | pdf |
    - Fig. 18.6.6.2. Example of (a) a CNS module and (b) the corresponding module invocation (p. 515) | html | pdf |
    - Fig. 18.6.7.1. Procedures and features available in CNS for structure determination by X-ray crystallography (p. 516) | html | pdf |
    - Fig. 18.6.7.2. Example of a typical CNS task file (p. 516) | html | pdf |
    - Fig. 18.6.8.1. Example of a CNS HTML form page (p. 517) | html | pdf |
    - Fig. 18.6.8.2. Use of the CNS HTML form page interface, emphasizing the correspondence between input fields in the form page and parameters in the task file (p. 518) | html | pdf |
- 18.7. The TNT refinement package (pp. 520-524) | html | pdf | chapter contents |
  D. E. Tronrud and L. F. Ten Eyck
  - 18.7.1. Scope and function of the package (p. 520) | html | pdf |
  - 18.7.2. Historical context (p. 520) | html | pdf |
  - 18.7.3. Design principles (pp. 520-522) | html | pdf |
    - 18.7.3.1. Refinement should be simple to run (pp. 520-521) | html | pdf |
    - 18.7.3.2. Refinement should run quickly and use as little memory as possible (p. 521) | html | pdf |
    - 18.7.3.3. The source code should not require customization for each project (pp. 521-522) | html | pdf |
  - 18.7.4. Current structure of the package (p. 522) | html | pdf |
  - 18.7.5. Innovations first introduced in TNT (pp. 522-523) | html | pdf |
    - 18.7.5.1. Identifying and restraining symmetry-related contacts (1982) (p. 522) | html | pdf |
    - 18.7.5.2. The ability of a single package to perform both individual atom and rigid-body refinement (1982) (p. 522) | html | pdf |
    - 18.7.5.3. Space-group optimized FFTs for all space groups (1989) (p. 522) | html | pdf |
    - 18.7.5.4. Modelling bulk solvent scattering via local scaling (∼1989) (p. 522) | html | pdf |
    - 18.7.5.5. Preconditioned conjugate-gradient minimization (1990) (p. 522) | html | pdf |
    - 18.7.5.6. Restraining stereochemistry of chemical links to symmetry-related molecules (∼1992) (p. 522) | html | pdf |
    - 18.7.5.7. Knowledge-based B-factor restraints (∼1994) (pp. 522-523) | html | pdf |
    - 18.7.5.8. Block-diagonal preconditioned conjugate-gradient minimization with pseudoinverses (1998) (p. 523) | html | pdf |
    - 18.7.5.9. Generalization of noncrystallographic symmetry operators to include shifts in the average B factor (1998) (p. 523) | html | pdf |
  - 18.7.6. TNT as a research tool (p. 523) | html | pdf |
    - 18.7.6.1. Michael Chapman's real-space refinement package (p. 523) | html | pdf |
    - 18.7.6.2. Randy Read's maximum-likelihood function (p. 523) | html | pdf |
    - 18.7.6.3. J. P. Abrahams' likelihood-weighted noncrystallographic symmetry restraints (p. 523) | html | pdf |
    - 18.7.6.4. The Buster refinement package (p. 523) | html | pdf |
  - 18.7.7. Current status of TNT (p. 523) | html | pdf |
  - References | html | pdf |
- 18.8. ARP/wARP – automated model building and refinement (pp. 525-528) | html | pdf | chapter contents |
  V. S. Lamzin, A. Perrakis and K. S. Wilson
  - 18.8.1. Refinement and model building are two parts of modelling a structure (p. 525) | html | pdf |
  - 18.8.2. Free-atom and hybrid models (pp. 525-526) | html | pdf |
  - 18.8.3. ARP/wARP applications (pp. 526-528) | html | pdf |
    - 18.8.3.1. Iterative protein-model building (pp. 526-527) | html | pdf |
    - 18.8.3.2. Recognition of secondary structural elements (p. 527) | html | pdf |
    - 18.8.3.3. Building polynucleotide fragments (p. 527) | html | pdf |
    - 18.8.3.4. Building bound ligands (p. 527) | html | pdf |
    - 18.8.3.5. Solvent building (pp. 527-528) | html | pdf |
  - 18.8.4. Iterations (p. 528) | html | pdf |
  - 18.8.5. Applicability and requirements (p. 528) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.8.3.1. A flow chart of the iterative building of a protein structure with ARP/wARP (p. 526) | html | pdf |
- 18.9. Macromolecular applications of SHELX (pp. 529-533) | html | pdf | chapter contents |
  G. M. Sheldrick
  - 18.9.1. Introduction (p. 529) | html | pdf |
  - 18.9.2. Experimental phasing with SHELXC/D/E (pp. 529-530) | html | pdf |
    - 18.9.2.1. Substructure location with SHELXD (p. 529) | html | pdf |
    - 18.9.2.2. Practical considerations for substructure solution (pp. 529-530) | html | pdf |
    - 18.9.2.3. SHELXE: density modification (p. 530) | html | pdf |
    - 18.9.2.4. Integrated density modification and autotracing (p. 530) | html | pdf |
  - 18.9.3. Macromolecular refinement using SHELXL (pp. 531-532) | html | pdf |
    - 18.9.3.1. Constraints and restraints (p. 531) | html | pdf |
    - 18.9.3.2. Least-squares refinement algebra (p. 531) | html | pdf |
    - 18.9.3.3. Full-matrix estimates of standard uncertainties (p. 531) | html | pdf |
    - 18.9.3.4. Refinement of anisotropic displacement parameters (pp. 531-532) | html | pdf |
    - 18.9.3.5. Similar geometry and NCS restraints (p. 532) | html | pdf |
    - 18.9.3.6. Modelling disorder and solvent (p. 532) | html | pdf |
    - 18.9.3.7. Twinned crystals (p. 532) | html | pdf |
  - 18.9.4. SHELXPRO – protein interface to SHELX (p. 532) | html | pdf |
  - 18.9.5. Distribution and support of SHELX (p. 532) | html | pdf |
  - References | html | pdf |
- 18.10. PrimeX and the Schrödinger computational chemistry suite of programs (pp. 534-538) | html | pdf | chapter contents |
  J. A. Bell, Y. Cao, J. R. Gunn, T. Day, E. Gallicchio, Z. Zhou, R. Levy and R. Farid
  - 18.10.1. Introduction (p. 534) | html | pdf |
    - 18.10.1.1. Computational environment (p. 534) | html | pdf |
    - 18.10.1.2. Mission (p. 534) | html | pdf |
    - 18.10.1.3. Implementation path (p. 534) | html | pdf |
  - 18.10.2. Computational environment (pp. 534-535) | html | pdf |
    - 18.10.2.1. Molecular graphics (p. 534) | html | pdf |
    - 18.10.2.2. Supporting infrastructure (p. 534) | html | pdf |
    - 18.10.2.3. Molecular mechanics (p. 535) | html | pdf |
  - 18.10.3. Achieving the mission of PrimeX (pp. 535-536) | html | pdf |
    - 18.10.3.1. Molecular models and computational chemistry (p. 535) | html | pdf |
      - 18.10.3.1.1. Hydrogen atoms (p. 535) | html | pdf |
      - 18.10.3.1.2. Electrostatics and implicit solvation (p. 535) | html | pdf |
      - 18.10.3.1.3. van der Waals interactions (p. 535) | html | pdf |
    - 18.10.3.2. Molecular models consistent with X-ray data (pp. 535-536) | html | pdf |
    - 18.10.3.3. Automation of refinement tasks (p. 536) | html | pdf |
  - 18.10.4. PrimeX implementation and theory (pp. 536-538) | html | pdf |
    - 18.10.4.1. Force-field model and automatic atom typing (p. 536) | html | pdf |
    - 18.10.4.2. Reciprocal-space calculations (pp. 536-537) | html | pdf |
      - 18.10.4.2.1. Restrained maximum-likelihood minimization (p. 536) | html | pdf |
      - 18.10.4.2.2. Simulated annealing (p. 536) | html | pdf |
      - 18.10.4.2.3. Map generation (p. 536) | html | pdf |
      - 18.10.4.2.4. Omit maps (pp. 536-537) | html | pdf |
    - 18.10.4.3. Real-space tools (p. 537) | html | pdf |
      - 18.10.4.3.1. Loop refinement (p. 537) | html | pdf |
      - 18.10.4.3.2. Side-chain placement (p. 537) | html | pdf |
      - 18.10.4.3.3. Minimization (p. 537) | html | pdf |
    - 18.10.4.4. Water placement (p. 537) | html | pdf |
    - 18.10.4.5. Ligand placement (p. 537) | html | pdf |
    - 18.10.4.6. Validation (pp. 537-538) | html | pdf |
  - 18.10.5. Conclusion (p. 538) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.10.2.1. The project table entries track the steps of this refinement in progress (p. 535) | html | pdf |
    - Fig. 18.10.3.1. The hydrogen-bond network optimizer clusters hydrogen-bond donors and acceptors to group together those that could possibly interact, so that these interactions can be efficiently optimized (p. 536) | html | pdf |
    - Fig. 18.10.4.1. The ligand/solvent placement GUI provides a list of electron-density blobs from a map with coefficients F_o − F_c, together with their volume, and several ways to specify the molecules to be placed into the electron density (p. 537) | html | pdf |
    - Fig. 18.10.4.2. The density fit table provides a convenient method for finding residues where the main chain or side chain in the model poorly fits the electron density (p. 538) | html | pdf |
  - Tables
    - Table 18.10.1.1. Schrödinger software packages related to PrimeX (p. 534) | html | pdf |
- 18.11. PHENIX: a comprehensive Python-based system for macromolecular structure solution (pp. 539-547) | html | pdf | chapter contents |
  P. D. Adams, P. V. Afonine, G. Bunkóczi, V. B. Chen, I. W. Davis, N. Echols, J. J. Headd, L.-W. Hung, G. J. Kapral, R. W. Grosse-Kunstleve, A. J. McCoy, N. W. Moriarty, R. Oeffner, R. J. Read, D. C. Richardson, J. S. Richardson, T. C. Terwilliger and P. H. Zwart
  - 18.11.1. Foundations (p. 539) | html | pdf |
    - 18.11.1.1. PHENIX architecture (p. 539) | html | pdf |
    - 18.11.1.2. Graphical user interface (p. 539) | html | pdf |
  - 18.11.2. Analysis of experimental data (p. 540) | html | pdf |
  - 18.11.3. Substructure determination, phasing and molecular replacement (pp. 540-541) | html | pdf |
    - 18.11.3.1. Substructure determination (p. 540) | html | pdf |
    - 18.11.3.2. Phasing (p. 540) | html | pdf |
    - 18.11.3.3. Noncrystallographic symmetry (NCS) (pp. 540-541) | html | pdf |
  - 18.11.4. Model building, ligand fitting and nucleic acids (pp. 541-542) | html | pdf |
    - 18.11.4.1. Model building (p. 541) | html | pdf |
    - 18.11.4.2. Ligand fitting (p. 541) | html | pdf |
    - 18.11.4.3. RNA and DNA (p. 541) | html | pdf |
    - 18.11.4.4. Maps, models and avoiding bias (p. 542) | html | pdf |
  - 18.11.5. Model, and model-to-data, validation (pp. 542-543) | html | pdf |
    - 18.11.5.1. Model and structure-factor manipulation and analysis (pp. 542-543) | html | pdf |
  - 18.11.6. Structure refinement (pp. 543-544) | html | pdf |
    - 18.11.6.1. Ligand-coordinate and restraint-geometry generation (pp. 543-544) | html | pdf |
  - 18.11.7. Integrated structure determination (pp. 544-545) | html | pdf |
    - 18.11.7.1. Why automation? (p. 544) | html | pdf |
    - 18.11.7.2. Automated structure solution (p. 544) | html | pdf |
    - 18.11.7.3. Iterative model building, density modification and refinement (pp. 544-545) | html | pdf |
  - 18.11.8. Conclusions (p. 545) | html | pdf |
  - References | html | pdf |
- 18.12. Structure determination in the presence of twinning by merohedry (pp. 548-551) | html | pdf | chapter contents |
  T. O. Yeates and M. R. Sawaya
  - 18.12.1. Introduction (p. 548) | html | pdf |
  - 18.12.2. Detwinning based on observed intensities (p. 548) | html | pdf |
  - 18.12.3. Molecular replacement with twinning (p. 548) | html | pdf |
  - 18.12.4. Multiple isomorphous replacement and anomalous phasing with twinning (pp. 548-549) | html | pdf |
  - 18.12.5. Atomic refinement with twinning (pp. 549-550) | html | pdf |
  - 18.12.6. Detwinning on the basis of model F_calc values (p. 550) | html | pdf |
  - 18.12.7. Summary (pp. 550-551) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.12.4.1. An illustration of how twinning operations can mix together reflections denoted F⁺ and F⁻ (p. 549) | html | pdf |
    - Fig. 18.12.5.1. A comparison of calculated versus observed R_twin values indicates the presence of twinning in a crystal of alanyl-tRNA synthetase (PDB entry 1YFS; Swairjo & Schimmel, 2005) (p. 550) | html | pdf |

Other experimental techniques
- 19.1. Neutron crystallography: methods and information content (pp. 553-556) | html | pdf | chapter contents |
  A. A. Kossiakoff
  - 19.1.1. Introduction (p. 553) | html | pdf |
  - 19.1.2. Diffraction geometries (p. 553) | html | pdf |
    - 19.1.2.1. Quasi-Laue diffractometry (p. 553) | html | pdf |
  - 19.1.3. Neutron density maps – information content (pp. 553-554) | html | pdf |
  - 19.1.4. Phasing models and evaluation of correctness (p. 554) | html | pdf |
  - 19.1.5. Evaluation of correctness (pp. 554-555) | html | pdf |
  - 19.1.6. Refinement (p. 555) | html | pdf |
  - 19.1.7. D₂O − H₂O solvent difference maps (p. 555) | html | pdf |
  - 19.1.8. Applications of D₂O − H₂O solvent difference maps (pp. 555-556) | html | pdf |
    - 19.1.8.1. Orientation of water molecules (p. 555) | html | pdf |
    - 19.1.8.2. H/D exchange (p. 556) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.1.3.1. Information content in neutron density maps (p. 554) | html | pdf |
    - Fig. 19.1.3.2. Sections of a neutron difference Fourier map showing methyl hydrogen densities for several representative methyl groups (p. 554) | html | pdf |
    - Fig. 19.1.5.1. Difference map of Asn34 in the trypsin structure (p. 555) | html | pdf |
    - Fig. 19.1.8.1. Sections of neutron density maps taken in the plane of the peptide group (p. 556) | html | pdf |
  - Tables
    - Table 19.1.1.1. Scattering lengths for atom types (p. 553) | html | pdf |
- 19.2. Electron diffraction of protein crystals (pp. 557-562) | html | pdf | chapter contents |
  W. Chiu
  - 19.2.1. Electron scattering (p. 557) | html | pdf |
  - 19.2.2. The electron microscope (p. 557) | html | pdf |
  - 19.2.3. Data collection (pp. 557-558) | html | pdf |
    - 19.2.3.1. Specimen preparation (pp. 557-558) | html | pdf |
    - 19.2.3.2. Radiation damage (p. 558) | html | pdf |
    - 19.2.3.3. Other technical factors (p. 558) | html | pdf |
  - 19.2.4. Data processing (pp. 558-561) | html | pdf |
    - 19.2.4.1. Data sampling (pp. 558-559) | html | pdf |
    - 19.2.4.2. Amplitudes and phases (pp. 559-560) | html | pdf |
    - 19.2.4.3. 3D map (p. 560) | html | pdf |
    - 19.2.4.4. Refinement (pp. 560-561) | html | pdf |
  - 19.2.5. Future development (p. 561) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.2.3.1. Electron diffraction pattern of trehalose-embedded bacteriorhodopsin, with Bragg reflections extending to 2.5 Å (p. 558) | html | pdf |
    - Fig. 19.2.4.1. Schematic diagram of data distribution in Fourier space for a two-dimensional crystal (p. 559) | html | pdf |
    - Fig. 19.2.4.2. Experimental intensities from electron diffraction patterns and phases from images of bacteriorhodopsin, recorded from tilted crystals in an electron cryomicroscope (p. 560) | html | pdf |
    - Fig. 19.2.4.3. Ribbon diagram of a tubulin dimer, whose structure has been solved to 3.7 Å resolution (p. 561) | html | pdf |
- 19.3. Small-angle X-ray scattering (pp. 563-574) | html | pdf | chapter contents |
  H. Tsuruta and J. E. Johnson
  - 19.3.1. Introduction (p. 563) | html | pdf |
  - 19.3.2. Small-angle single-crystal X-ray diffraction studies (pp. 563-564) | html | pdf |
  - 19.3.3. Solution X-ray scattering studies (pp. 564-573) | html | pdf |
    - 19.3.3.1. Information content of solution scattering (pp. 564-568) | html | pdf |
      - 19.3.3.1.1. Solution scattering and crystal structures (p. 567) | html | pdf |
      - 19.3.3.1.2. Low-resolution model determination using solution scattering (pp. 567-568) | html | pdf |
    - 19.3.3.2. Instrumentation for small-angle X-ray scattering (pp. 568-569) | html | pdf |
      - 19.3.3.2.1. Instruments on conventional sources (p. 568) | html | pdf |
      - 19.3.3.2.2. Synchrotron instruments (pp. 568-569) | html | pdf |
    - 19.3.3.3. Experimental considerations (pp. 569-571) | html | pdf |
      - 19.3.3.3.1. Sample preparation (p. 569) | html | pdf |
      - 19.3.3.3.2. Sample-handling devices (pp. 569-570) | html | pdf |
      - 19.3.3.3.3. Designing experiments (p. 570) | html | pdf |
      - 19.3.3.3.4. Data-collection practices (pp. 570-571) | html | pdf |
      - 19.3.3.3.5. Data processing and analysis (p. 571) | html | pdf |
    - 19.3.3.4. Recent applications of solution X-ray scattering in structural molecular biology (pp. 571-573) | html | pdf |
      - 19.3.3.4.1. Studies of proteins in solution that complement high-resolution structures (pp. 571-572) | html | pdf |
      - 19.3.3.4.2. Time-resolved studies (p. 572) | html | pdf |
      - 19.3.3.4.3. Protein-folding studies (pp. 572-573) | html | pdf |
  - Figures
    - Fig. 19.3.2.1. A cross section of the electron-density map of sFHV at 14 Å resolution (p. 563) | html | pdf |
    - Fig. 19.3.2.2. Comparison of the absolute values of single-crystal reflection amplitudes (circles), the solution scattering intensity (thick curve) and the calculated scattering intensity from a uniform sphere (thin curve) (p. 564) | html | pdf |
    - Fig. 19.3.3.1. Definition of electron-density contrast (p. 565) | html | pdf |
    - Fig. 19.3.3.2. (a) The calculated solution X-ray scattering curves from the crystal structure of Salmonella typhimorium glutamine synthetase (p. 565) | html | pdf |
    - Fig. 19.3.3.3. (a) Interparticle interference in biological small-angle scattering (p. 566) | html | pdf |
    - Fig. 19.3.3.4. Definition of the electron pair distance distribution function $[P({\bf r})]$ (p. 567) | html | pdf |
    - Fig. 19.3.3.5. A small-angle X-ray scattering instrument on BL 4–2 at the Stanford Synchrotron Radiation Laboratory (p. 568) | html | pdf |
    - Fig. 19.3.3.6. (a) Flat-window cells for solution scattering and (b) a diagram of a stopped-flow rapid mixer for time-resolved solution scattering (p. 570) | html | pdf |
  - Tables
    - Table 19.3.3.1. List of commonly used software for solution scattering (p. 571) | html | pdf |
- 19.4. Small-angle neutron scattering (pp. 575-582) | html | pdf | chapter contents |
  D. M. Engelman and P. B. Moore
  - 19.4.1. Introduction (p. 575) | html | pdf |
  - 19.4.2. Fundamental relationships (pp. 575-577) | html | pdf |
  - 19.4.3. Contrast variation (pp. 577-579) | html | pdf |
    - 19.4.3.1. Variation of solvent density (p. 577) | html | pdf |
    - 19.4.3.2. Variation of internal contrast (pp. 577-578) | html | pdf |
    - 19.4.3.3. Relationship of contrasting regions (p. 578) | html | pdf |
    - 19.4.3.4. The triple isotopic substitution method (p. 578) | html | pdf |
    - 19.4.3.5. Nuclear spin contrast variation (p. 578) | html | pdf |
    - 19.4.3.6. Interpretation of small-angle scattering using models (pp. 578-579) | html | pdf |
    - 19.4.3.7. Use of forward scattering to measure molecular weights (p. 579) | html | pdf |
  - 19.4.4. Distance measurements (pp. 579-580) | html | pdf |
    - 19.4.4.1. Theory and background (p. 579) | html | pdf |
    - 19.4.4.2. Neutron distance measurements (pp. 579-580) | html | pdf |
    - 19.4.4.3. The statistical labelling method (p. 580) | html | pdf |
  - 19.4.5. Practical considerations (p. 580) | html | pdf |
    - 19.4.5.1. Feasibility (p. 580) | html | pdf |
    - 19.4.5.2. Homogeneity and stability (p. 580) | html | pdf |
    - 19.4.5.3. Solvent conditions (p. 580) | html | pdf |
  - 19.4.6. Examples (pp. 580-581) | html | pdf |
    - 19.4.6.1. Contrast variation (p. 580) | html | pdf |
    - 19.4.6.2. Contrast matching (p. 580) | html | pdf |
    - 19.4.6.3. Spin contrast variation (p. 580) | html | pdf |
    - 19.4.6.4. Specific deuteration, combination with X-ray measurements (p. 580) | html | pdf |
    - 19.4.6.5. Distance measurements and triangulation (pp. 580-581) | html | pdf |
  - References | html | pdf |
- 19.5. Fibre diffraction (pp. 583-592) | html | pdf | chapter contents |
  R. Chandrasekaran and G. Stubbs
  - 19.5.1. Introduction (p. 583) | html | pdf |
  - 19.5.2. Types of fibres (pp. 583-584) | html | pdf |
  - 19.5.3. Diffraction by helical molecules (pp. 584-585) | html | pdf |
    - 19.5.3.1. Fibre diffraction patterns (p. 584) | html | pdf |
    - 19.5.3.2. Helical symmetry (p. 584) | html | pdf |
    - 19.5.3.3. Structure factors (p. 584) | html | pdf |
    - 19.5.3.4. Fourier–Bessel syntheses (p. 584) | html | pdf |
    - 19.5.3.5. Diffracted intensities: noncrystalline fibres (p. 584) | html | pdf |
    - 19.5.3.6. Diffracted intensities: polycrystalline fibres (pp. 584-585) | html | pdf |
  - 19.5.4. Fibre preparation (p. 585) | html | pdf |
  - 19.5.5. Data collection (p. 585) | html | pdf |
  - 19.5.6. Data processing (pp. 585-586) | html | pdf |
    - 19.5.6.1. Coordinate transformation (p. 585) | html | pdf |
    - 19.5.6.2. Intensity correction (pp. 585-586) | html | pdf |
    - 19.5.6.3. Background subtraction (p. 586) | html | pdf |
    - 19.5.6.4. Integration of crystalline fibre data (p. 586) | html | pdf |
    - 19.5.6.5. Integration of continuous data (p. 586) | html | pdf |
  - 19.5.7. Determination of structures (pp. 586-588) | html | pdf |
    - 19.5.7.1. Initial models: small unit cells (pp. 586-587) | html | pdf |
    - 19.5.7.2. Refinement: small unit cells (p. 587) | html | pdf |
    - 19.5.7.3. Data-to-parameter ratio (p. 587) | html | pdf |
    - 19.5.7.4. Initial models: large unit cells (p. 587) | html | pdf |
    - 19.5.7.5. Refinement: large unit cells (pp. 587-588) | html | pdf |
    - 19.5.7.6. Difference Fourier methods (p. 588) | html | pdf |
    - 19.5.7.7. Evaluation (p. 588) | html | pdf |
  - 19.5.8. Structures determined by X-ray fibre diffraction (pp. 588-590) | html | pdf |
    - 19.5.8.1. Polypeptides (pp. 588-589) | html | pdf |
    - 19.5.8.2. Polynucleotides (p. 589) | html | pdf |
    - 19.5.8.3. Polysaccharides (p. 589) | html | pdf |
    - 19.5.8.4. Helical viruses and bacteriophages (pp. 589-590) | html | pdf |
    - 19.5.8.5. Other large assemblies (p. 590) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.5.2.1. X-ray diffraction patterns showing (a) continuous intensity on layer lines from an oriented nucleic acid fibre and (b) Bragg reflections from an oriented and polycrystalline polysaccharide fibre (p. 583) | html | pdf |
    - Fig. 19.5.7.1. Flow chart of the principal steps in the determination and refinement of fibre structures with small unit cells (p. 586) | html | pdf |
    - Fig. 19.5.8.1. X-ray diffraction pattern from an oriented sol of the U2 strain of tobacco mosaic virus (p. 589) | html | pdf |
- 19.6. Electron cryomicroscopy of biological macromolecules (pp. 593-614) | html | pdf | chapter contents |
  T. S. Baker and R. Henderson
  - 19.6.1. Abbreviations used (p. 593) | html | pdf |
  - 19.6.2. Introduction: macromolecular structure determination using electron microscopy (p. 593) | html | pdf |
  - 19.6.3. Physics of electron scattering and radiation damage (pp. 593-595) | html | pdf |
    - 19.6.3.1. Elastic and inelastic scattering (p. 594) | html | pdf |
    - 19.6.3.2. Radiation damage (pp. 594-595) | html | pdf |
    - 19.6.3.3. Required properties of the illuminating electron beam (p. 595) | html | pdf |
  - 19.6.4. Three-dimensional electron cryomicroscopy of macromolecules (pp. 595-601) | html | pdf |
    - 19.6.4.1. Overview of conceptual steps (pp. 595-596) | html | pdf |
    - 19.6.4.2. Classification of macromolecules (p. 597) | html | pdf |
    - 19.6.4.3. Specimen preparation (pp. 597-599) | html | pdf |
    - 19.6.4.4. Microscopy (pp. 599-600) | html | pdf |
    - 19.6.4.5. Selection and preprocessing of digitized images (p. 601) | html | pdf |
  - 19.6.5. Image processing and 3D reconstruction (pp. 601-604) | html | pdf |
    - 19.6.5.1. 2D crystals (p. 603) | html | pdf |
    - 19.6.5.2. Helical particles (p. 603) | html | pdf |
    - 19.6.5.3. Icosahedral particles (pp. 603-604) | html | pdf |
    - 19.6.5.4. Electron cryo-tomography (p. 604) | html | pdf |
  - 19.6.6. Visualization, modelling and interpretation of results (pp. 604-605) | html | pdf |
  - 19.6.7. Trends (pp. 605-606) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.6.3.1. Schematic diagram showing the principle of image formation and diffraction in the transmission electron microscope (p. 594) | html | pdf |
    - Fig. 19.6.4.1. Flow diagram showing common procedures involved in cryoTEM from sample preparation to map interpretation (p. 595) | html | pdf |
    - Fig. 19.6.4.2. A display of the results at different stages of image processing of a digitized micrograph of a 2D crystal of bacteriorhodopsin (p. 596) | html | pdf |
    - Fig. 19.6.4.3. Schematic diagram to illustrate the principle of 3D reconstruction (p. 597) | html | pdf |
    - Fig. 19.6.4.4. Representative plots of the microscope CTF as a function of spatial frequency, for two different defocus settings (0.7 and 4.0 µm underfocus) and for a field-emission (light curve) or tungsten (dark curve) electron source (p. 600) | html | pdf |
    - Fig. 19.6.7.1. Examples of macromolecules studied by cryoTEM and 3D image reconstruction and the resulting 3D structures (bottom row) after cryoTEM analysis (p. 605) | html | pdf |
  - Tables
    - Table 19.6.4.1. Classification of macromolecules according to periodic order and symmetry (p. 598) | html | pdf |
    - Table 19.6.5.1. Methods of three-dimensional image reconstruction (p. 602) | html | pdf |
- 19.7. Nuclear magnetic resonance (NMR) spectroscopy (pp. 615-619) | html | pdf | chapter contents |
  K. Wüthrich
  - 19.7.1. Complementary roles of NMR in solution and X-ray crystallography in structural biology (p. 615) | html | pdf |
  - 19.7.2. A standard protocol for NMR structure determination of proteins and nucleic acids (pp. 615-617) | html | pdf |
  - 19.7.3. Combined use of single-crystal X-ray diffraction and solution NMR for structure determination (p. 617) | html | pdf |
  - 19.7.4. NMR studies of solvation in solution (pp. 617-618) | html | pdf |
  - 19.7.5. NMR studies of rate processes and conformational equilibria in three-dimensional macromolecular structures (p. 618) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.7.2.1. Diagram outlining the course of a macromolecular structure determination by NMR in solution (p. 615) | html | pdf |
    - Fig. 19.7.2.2. (a) Sequential resonance assignment based on sequential ¹H–¹H NOEs (p. 616) | html | pdf |
    - Fig. 19.7.2.3. Polypeptide backbone of 19 energy-refined conformers selected to represent the NMR solution structure of the Antennapedia homeodomain (p. 617) | html | pdf |
    - Fig. 19.7.5.1. 180° ring flips of tyrosine and phenylalanine about the C^β—C¹ bond (p. 618) | html | pdf |
- 19.8. Use of SPIDER and SPIRE in image reconstruction (pp. 620-623) | html | pdf | chapter contents |
  A. Leith, W. Baxter and J. Frank
  - 19.8.1. Introduction (p. 620) | html | pdf |
  - 19.8.2. Basic philosophy of single-particle reconstruction (pp. 620-621) | html | pdf |
  - 19.8.3. Implementation of single-particle reconstruction in SPIDER (pp. 621-623) | html | pdf |
    - 19.8.3.1. Level 1: elementary commands (pp. 621-622) | html | pdf |
    - 19.8.3.2. Level 2: procedures (pp. 622-623) | html | pdf |
  - 19.8.4. Implementation of single-particle reconstruction in SPIRE (p. 623) | html | pdf |
  - 19.8.5. Conclusion (p. 623) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.8.2.1. Flow diagram of reference-based single-particle reconstruction by defocus groups (p. 621) | html | pdf |
    - Fig. 19.8.3.1. Schematic representation of the SPIDER hierarchy of functional units and calling levels (p. 622) | html | pdf |
    - Fig. 19.8.4.1. A SPIRE form, displaying the parameters, input files and output files of a SPIDER procedure file (p. 622) | html | pdf |
    - Fig. 19.8.5.1. Reconstruction of the E. coli ribosome bound with the Phe-tRNA·EF-Tu·GDP ternary complex at 6.7 Å resolution, obtained by the protocol outlined here (LeBarron et al., 2008) (p. 622) | html | pdf |
- 19.9. Four-dimensional cryo-electron microscopy at quasi-atomic resolution: IMAGIC 4D (pp. 624-628) | html | pdf | chapter contents |
  M. van Heel, R. Portugal, A. Rohou, C. Linnemayr, C. Bebeacua, R. Schmidt, T. Grant and M. Schatz
  - 19.9.1. Introduction (p. 624) | html | pdf |
  - 19.9.2. The IMAGIC software system (p. 624) | html | pdf |
  - 19.9.3. IMAGIC `4D' processing/data format (pp. 624-625) | html | pdf |
  - 19.9.4. Software parallelization (p. 625) | html | pdf |
  - 19.9.5. Full 2D (parallel) astigmatic contrast transfer function correction (p. 625) | html | pdf |
  - 19.9.6. Parallel automatic particle picking (p. 625) | html | pdf |
  - 19.9.7. Parallel multi-reference alignments and reference bias (p. 626) | html | pdf |
  - 19.9.8. MSA and its parallelization (p. 626) | html | pdf |
  - 19.9.9. Handling multiple 3D reconstructions in parallel (pp. 626-627) | html | pdf |
  - 19.9.10. Angular reconstitution 4D refinements (p. 627) | html | pdf |
  - 19.9.11. Discussion (p. 627) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.9.3.1. IMAGIC 4D file format (p. 625) | html | pdf |
    - Fig. 19.9.7.1. One starts with the (a priori) assignment of the images in a stack (original images or class averages) to a number of 3D volumes (named 3D-1 to 3D-3) (p. 626) | html | pdf |
- 19.10. Single-particle reconstruction with EMAN (pp. 629-632) | html | pdf | chapter contents |
  S. Ludtke
  - 19.10.1. Introduction (p. 629) | html | pdf |
  - 19.10.2. Overview of EMAN (pp. 629-630) | html | pdf |
    - 19.10.2.1. GUI layer and workflow (p. 629) | html | pdf |
    - 19.10.2.2. Command-line programs (pp. 629-630) | html | pdf |
    - 19.10.2.3. Python wrapper (p. 630) | html | pdf |
    - 19.10.2.4. C++ (p. 630) | html | pdf |
    - 19.10.2.5. Cross-platform support (p. 630) | html | pdf |
    - 19.10.2.6. Parallel processing (p. 630) | html | pdf |
    - 19.10.2.7. File formats and other conventions (p. 630) | html | pdf |
  - 19.10.3. Single-particle reconstruction (p. 631) | html | pdf |
    - 19.10.3.1. Particle selection (e2boxer.py) (p. 631) | html | pdf |
    - 19.10.3.2. Contrast transfer function/image evaluation (e2ctf.py) (p. 631) | html | pdf |
    - 19.10.3.3. Grouping particles into sets (p. 631) | html | pdf |
    - 19.10.3.4. Reference-free two-dimensional classification (e2refine2d.py) (p. 631) | html | pdf |
    - 19.10.3.5. Initial model generation (e2initialmodel.py) (p. 631) | html | pdf |
    - 19.10.3.6. Refinement (e2refine.py) (p. 631) | html | pdf |
  - 19.10.4. Evaluating the reconstruction (pp. 631-632) | html | pdf |
    - 19.10.4.1. Model accuracy (p. 632) | html | pdf |
    - 19.10.4.2. Measures of resolution and resolvability (p. 632) | html | pdf |
    - 19.10.4.3. Model/noise bias (p. 632) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.10.2.1. The overall workflow interface, and the dialogue for the three-dimensional refinement subtask (p. 629) | html | pdf |
    - Fig. 19.10.2.2. A representation of the Euler GUI tool (p. 630) | html | pdf |
  - Tables
    - Table 19.10.2.1. Listing of EMAN2 supported file formats and whether each has read (R) and/or write (W) support (p. 630) | html | pdf |

Energy calculations and molecular dynamics
- 20.1. Molecular-dynamics simulation of protein crystals: convergence of molecular properties of ubiquitin (pp. 633-641) | html | pdf | chapter contents |
  U. Stocker and W. F. van Gunsteren
  - 20.1.1. Introduction (p. 633) | html | pdf |
  - 20.1.2. Methods (pp. 633-634) | html | pdf |
  - 20.1.3. Results (pp. 634-640) | html | pdf |
    - 20.1.3.1. Energetic properties (p. 634) | html | pdf |
    - 20.1.3.2. Structural properties (pp. 634-636) | html | pdf |
    - 20.1.3.3. Effect of the translational and rotational fitting procedure (pp. 636-638) | html | pdf |
    - 20.1.3.4. Effect of the averaging period (pp. 638-639) | html | pdf |
    - 20.1.3.5. Internal motions of the proteins (p. 639) | html | pdf |
    - 20.1.3.6. Dihedral-angle fluctuations and transitions (pp. 639-640) | html | pdf |
    - 20.1.3.7. Water diffusion (p. 640) | html | pdf |
  - 20.1.4. Conclusions (p. 640) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 20.1.3.1. Non-bonded energies (in kJ mol⁻¹) of the simulated system as a function of time (p. 634) | html | pdf |
    - Fig. 20.1.3.2. Root-mean-square atom-positional deviations (RMSD) in nm from the X-ray structure of the four different protein molecules in the unit cell as a function of time (p. 634) | html | pdf |
    - Fig. 20.1.3.3. Root-mean-square Cα-atom-position deviation (RMSD) in nm from a reference structure as a function of the residue number using the final 1.6 ns of the simulation (p. 635) | html | pdf |
    - Fig. 20.1.3.4. Root-mean-square Cα-atom-position fluctuations (RMSFs) in nm are shown for molecule 4 as a function of residue number (p. 638) | html | pdf |
    - Fig. 20.1.3.5. Root-mean-square Cα-atom-position fluctuations (RMSFs) in nm are shown using the same fitting protocols as in Fig. 20.1.3.4, but averaged over all four protein molecules in the unit cell (p. 638) | html | pdf |
    - Fig. 20.1.3.6. Root-mean-square Cα-atom-position fluctuations (RMSFs) in nm are shown for molecule 4, with full translational and rotational fitting over the Cα atoms of residues 1–72 (p. 638) | html | pdf |
    - Fig. 20.1.3.7. Root-mean-square Cα-atom-position fluctuations (RMSFs) in nm are shown using the same averaging periods as in Fig. 20.1.3.6, but averaged over all four protein molecules in the unit cell (p. 638) | html | pdf |
    - Fig. 20.1.3.8. Root-mean-square Cα-atom-position fluctuations (RMSFs) in nm for the four protein molecules in the unit cell as a function of the residue number (p. 639) | html | pdf |
    - Fig. 20.1.3.9. The number of water molecules with a given root-mean-square oxygen-position fluctuation (RMSF) in nm are shown for different averaging periods: 400–800 ps (solid line), 400–1200 ps (short-dashed line), 400–2000 ps (long-dashed line) (p. 640) | html | pdf |
  - Tables
    - Table 20.1.3.1. Occurrence of intramolecular hydrogen bonds (%) during the final 1.6 ns of the simulation (pp. 636-637) | html | pdf |
    - Table 20.1.3.2. Occurrence of intermolecular hydrogen bonds (%) during the final 1.6 ns of the simulation (p. 637) | html | pdf |
    - Table 20.1.3.3. Root-mean-square fluctuations of polypeptide backbone and ψ dihedral angles (°) for the different molecules using different time-averaging periods (p. 639) | html | pdf |
    - Table 20.1.3.4. Number of protein-backbone dihedral-angle transitions per 100 ps for the different molecules using different time periods (p. 639) | html | pdf |
- 20.2. Molecular-dynamics simulations of biological macromolecules (pp. 642-648) | html | pdf | chapter contents |
  C. B. Post and V. M. Dadarlat
  - 20.2.1. Introduction (p. 642) | html | pdf |
  - 20.2.2. The simulation method (p. 642) | html | pdf |
  - 20.2.3. Potential-energy function (pp. 642-644) | html | pdf |
    - 20.2.3.1. Empirical energy (pp. 642-643) | html | pdf |
    - 20.2.3.2. Particle mesh Ewald (p. 643) | html | pdf |
    - 20.2.3.3. Experimental restraints in the energy function (pp. 643-644) | html | pdf |
  - 20.2.4. Empirical parameterization of the force field (p. 644) | html | pdf |
  - 20.2.5. Modifications in the force field for structure determination (p. 644) | html | pdf |
  - 20.2.6. Internal dynamics and average structures (pp. 644-645) | html | pdf |
  - 20.2.7. Assessment of the simulation procedure (p. 645) | html | pdf |
  - 20.2.8. Effect of crystallographic atomic resolution on structural stability during molecular dynamics (pp. 645-647) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 20.2.7.1. Structural comparison and radii of gyration of various proteins as a function of time in the molecular-dynamics simulation (p. 645) | html | pdf |
    - Fig. 20.2.8.1. Cα tracings of BPTI (p. 646) | html | pdf |
    - Fig. 20.2.8.2. BPTI r.m.s. coordinate differences between the energy-minimized crystallographic structure and MD snapshots from three simulations (p. 646) | html | pdf |
  - Tables
    - Table 20.2.8.1. R.m.s. coordinate differences between crystallographic structures and average MD structures (p. 646) | html | pdf |

Structure validation
- 21.1. Validation of protein crystal structures (pp. 649-661) | html | pdf | chapter contents |
  G. J. Kleywegt
  - 21.1.1. Introduction (p. 649) | html | pdf |
  - 21.1.2. Types of error (pp. 649-650) | html | pdf |
  - 21.1.3. Detecting outliers (pp. 650-651) | html | pdf |
    - 21.1.3.1. Classes of quality indicators (p. 650) | html | pdf |
    - 21.1.3.2. Local statistics (pp. 650-651) | html | pdf |
    - 21.1.3.3. Global statistics (p. 651) | html | pdf |
  - 21.1.4. Fixing errors (pp. 651-652) | html | pdf |
  - 21.1.5. Preventing errors (p. 652) | html | pdf |
  - 21.1.6. Final model (p. 652) | html | pdf |
  - 21.1.7. A compendium of quality criteria (pp. 652-658) | html | pdf |
    - 21.1.7.1. Data quality (pp. 653-654) | html | pdf |
      - 21.1.7.1.1. Merging R values (p. 653) | html | pdf |
      - 21.1.7.1.2. Completeness (p. 653) | html | pdf |
      - 21.1.7.1.3. Redundancy (p. 653) | html | pdf |
      - 21.1.7.1.4. Signal strength (p. 653) | html | pdf |
      - 21.1.7.1.5. Resolution (p. 653) | html | pdf |
      - 21.1.7.1.6. Unit-cell parameters (pp. 653-654) | html | pdf |
      - 21.1.7.1.7. Symmetry (p. 654) | html | pdf |
    - 21.1.7.2. Model quality, coordinates (pp. 654-656) | html | pdf |
      - 21.1.7.2.1. Geometry and stereochemistry (p. 654) | html | pdf |
      - 21.1.7.2.2. Torsion angles (dihedrals) (pp. 654-655) | html | pdf |
      - 21.1.7.2.3. C^α-only models (p. 655) | html | pdf |
      - 21.1.7.2.4. Contacts and environments (pp. 655-656) | html | pdf |
      - 21.1.7.2.5. Noncrystallographic symmetry (p. 656) | html | pdf |
      - 21.1.7.2.6. Solvent molecules (p. 656) | html | pdf |
      - 21.1.7.2.7. Miscellaneous (p. 656) | html | pdf |
    - 21.1.7.3. Model quality, temperature factors (pp. 656-657) | html | pdf |
    - 21.1.7.4. Model versus experimental data (pp. 657-658) | html | pdf |
      - 21.1.7.4.1. R values (p. 657) | html | pdf |
      - 21.1.7.4.2. Real-space fits (p. 657) | html | pdf |
      - 21.1.7.4.3. Coordinate error estimates (pp. 657-658) | html | pdf |
      - 21.1.7.4.4. Noncrystallographic symmetry (p. 658) | html | pdf |
      - 21.1.7.4.5. Difference density quality (p. 658) | html | pdf |
    - 21.1.7.5. Accountancy (p. 658) | html | pdf |
  - 21.1.8. Future (p. 658) | html | pdf |
  - References | html | pdf |
- 21.2. Assessing the quality of macromolecular structures (pp. 662-676) | html | pdf | chapter contents |
  S. J. Wodak, A. A. Vagin, J. Richelle, U. Das, J. Pontius and H. M. Berman
  - 21.2.1. Introduction (p. 662) | html | pdf |
  - 21.2.2. Validating the geometric and stereochemical parameters of the model (pp. 662-665) | html | pdf |
    - 21.2.2.1. Comparisons against standard values derived from crystals of small molecules (pp. 662-663) | html | pdf |
    - 21.2.2.2. Comparisons against standard values derived from surveys of other macromolecules (pp. 663-665) | html | pdf |
      - 21.2.2.2.1. Validation of stereochemical and non-bonded parameters (p. 663) | html | pdf |
      - 21.2.2.2.2. Validation using knowledge-based interaction potentials and profiles (pp. 663-664) | html | pdf |
      - 21.2.2.2.3. Deviations from standard atomic volumes as a quality measure for protein crystal structures (pp. 664-665) | html | pdf |
  - 21.2.3. Validation of a model versus experimental data (pp. 665-673) | html | pdf |
    - 21.2.3.1. A systematic approach using the SFCHECK software (pp. 666-673) | html | pdf |
      - 21.2.3.1.1. Tasks performed by SFCHECK  (pp. 666-667) | html | pdf |
        21.2.3.1.1.1. Treatment of structure-factor data and scaling  (p. 666) | html | pdf |
        21.2.3.1.1.2. Global agreement between the model and experimental data  (p. 666) | html | pdf |
        21.2.3.1.1.3. Estimations of errors in atomic positions  (p. 667) | html | pdf |
        21.2.3.1.1.4. Local agreement between the model and the experimental data  (p. 667) | html | pdf |
      - 21.2.3.1.2. Evaluation of individual structures (pp. 667-668) | html | pdf |
      - 21.2.3.1.3. Quality assessment based on surveys across structures  (pp. 668-673) | html | pdf |
        21.2.3.1.3.1. Assessing the quality of a structure as a whole  (pp. 668-669) | html | pdf |
        21.2.3.1.3.2. Assessing the quality in specific regions of a model  (pp. 670-673) | html | pdf |
  - 21.2.4. Atomic resolution structures (p. 673) | html | pdf |
  - 21.2.5. Concluding remarks (p. 673) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.2.2.1. The Voronoi polyhedron (p. 664) | html | pdf |
    - Fig. 21.2.2.2. Atomic volume Z score r.m.s. variation with nominal resolution (d spacing) in 900 protein structures from the PDB (p. 665) | html | pdf |
    - Fig. 21.2.3.1. Typical SFCHECK output in PostScript format, illustrated for the protein rusticyanin from Thiobacillus ferrooxidans (1RCY) (Walter et al., 1996) (p. 668) | html | pdf |
    - Fig. 21.2.3.2. Graphical output from the SFCHECK analysis of global characteristics of the structure-factor data and the model agreement with those data for the same structure as in Fig. 21.2.3.1 (p. 669) | html | pdf |
    - Fig. 21.2.3.3. SFCHECK evaluation summary of the local agreement between the model and the electron density for the same structure as in Fig. 21.2.3.1 (pp. 671-672) | html | pdf |
    - Fig. 21.2.3.4. Variation of global quality indicators with the nominal resolution (d spacing) of the crystallographic data (p. 672) | html | pdf |
    - Fig. 21.2.3.5. Pairwise correlations between the various local quality indicators computed by SFCHECK (p. 673) | html | pdf |
    - Fig. 21.2.3.6. B factors and density indices for residues across different structures (p. 674) | html | pdf |
  - Tables
    - Table 21.2.3.1. Parameters computed for the analysis of the structure-factor data (p. 666) | html | pdf |
    - Table 21.2.3.2. Estimation of errors in atomic coordinates (p. 667) | html | pdf |
    - Table 21.2.3.3. Parameters computed by SFCHECK to assess the quality of the model in specific regions (p. 672) | html | pdf |
- 21.3. Detection of errors in protein models (pp. 677-683) | html | pdf | chapter contents |
  O. Dym, D. Eisenberg and T. O. Yeates
  - 21.3.1. Motivation and introduction (p. 677) | html | pdf |
  - 21.3.2. Separating evaluation from refinement (p. 677) | html | pdf |
  - 21.3.3. Algorithms for the detection of errors in protein models and the types of errors they detect (pp. 677-679) | html | pdf |
    - 21.3.3.1. PROCHECK (pp. 677-678) | html | pdf |
    - 21.3.3.2. WHAT IF (p. 678) | html | pdf |
    - 21.3.3.3. VERIFY3D (p. 678) | html | pdf |
    - 21.3.3.4. ERRAT (pp. 678-679) | html | pdf |
  - 21.3.4. Selection of database (p. 679) | html | pdf |
  - 21.3.5. Examples: detection of errors in structures (pp. 679-682) | html | pdf |
    - 21.3.5.1. Specific examples (pp. 679-682) | html | pdf |
    - 21.3.5.2. Survey of old and revised structures (p. 682) | html | pdf |
  - 21.3.6. Summary (p. 682) | html | pdf |
  - 21.3.7. Availability of software (p. 682) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.3.5.1. Detection of errors in the small subunit of ribulose-1,5-bisphospate carboxylase/oxygenase (RuBisCO) (p. 679) | html | pdf |
    - Fig. 21.3.5.2. The detection of model errors due to refinement in an incorrect space group: an example (3xia.coor) from the archive of obsolete PDB entries (p. 680) | html | pdf |
    - Fig. 21.3.5.3. The usefulness of validation programs during model building is suggested by the example of the triacylglycerol lipase from Pseudomonas cepacia at different stages of atomic refinement (p. 681) | html | pdf |
    - Fig. 21.3.5.4. VERIFY3D profile plots of diphtheria toxin (DT) in three forms: open and closed monomers and the dimer (p. 681) | html | pdf |
    - Fig. 21.3.5.5. Evaluation of old and revised models in a database survey by ERRAT (p. 682) | html | pdf |
- 21.4. PROCHECK: validation of protein-structure coordinates (pp. 684-687) | html | pdf | chapter contents |
  R. A. Laskowski, M. W. MacArthur and J. M. Thornton
  - 21.4.1. Introduction (p. 684) | html | pdf |
  - 21.4.2. The program (p. 684) | html | pdf |
  - 21.4.3. The parameters (pp. 684-685) | html | pdf |
  - 21.4.4. Which parameters are best? (p. 685) | html | pdf |
  - 21.4.5. Input (p. 686) | html | pdf |
  - 21.4.6. Output produced (p. 686) | html | pdf |
  - 21.4.7. Other validation tools (p. 686) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.4.4.1. PROCHECK Ramachandran plots (p. 685) | html | pdf |
    - Fig. 21.4.6.1. Two of the residue-property plots generated by PROCHECK (p. 685) | html | pdf |
    - Fig. 21.4.6.2. Schematic plots of various residue-by-residue properties (p. 686) | html | pdf |
  - Tables
    - Table 21.4.3.1. Summary of expected values for stereochemical parameters in well resolved structures (p. 684) | html | pdf |
- 21.5. KiNG and kinemages (pp. 688-693) | html | pdf | chapter contents |
  V. B. Chen, J. S. Richardson and D. C. Richardson
  - 21.5.1. Introduction to aims and concepts (pp. 688-689) | html | pdf |
  - 21.5.2. Uses of KiNG and kinemages (pp. 689-692) | html | pdf |
    - 21.5.2.1. Use as a reader of existing kinemages (p. 689) | html | pdf |
    - 21.5.2.2. Use for teaching and on the web (p. 689) | html | pdf |
    - 21.5.2.3. Use for research (pp. 689-690) | html | pdf |
    - 21.5.2.4. Cystallographic rebuilding tools (pp. 691-692) | html | pdf |
  - 21.5.3. Making kinemages (pp. 692-693) | html | pdf |
  - 21.5.4. Software notes (p. 693) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.5.1.1. Illustration of combining molecular representations in kinemage format, shown in KiNG (p. 689) | html | pdf |
    - Fig. 21.5.2.1. Screenshot of KiNG presenting interactive three-dimensional validation data directly in the browser, in a MolProbity session for PDB code 2C0Q (Ekstrom et al., 2006), a better-than-average 2.5 Å resolution structure (p. 690) | html | pdf |
    - Fig. 21.5.2.2. Screen capture of side-chain rebuilding in KiNG using the side-chain rotator and backrub tools, with display of electron density, all-atom contacts and rotamer quality (p. 691) | html | pdf |
- 21.6. MolProbity: all-atom structure validation for macromolecular crystallography (pp. 694-701) | html | pdf | chapter contents |
  V. B. Chen, W. B. Arendall III, J. J. Headd, D. A. Keedy, R. M. Immormino, G. J. Kapral, L. W. Murray, J. S. Richardson and D. C. Richardson
  - 21.6.1. Summary of MolProbity flow and user interactions (p. 694) | html | pdf |
  - 21.6.2. Validation analyses (pp. 694-697) | html | pdf |
    - 21.6.2.1. Addition of H atoms (pp. 694-695) | html | pdf |
    - 21.6.2.2. All-atom contact analysis (p. 695) | html | pdf |
    - 21.6.2.3. Torsion-angle combinations: updated Ramachandran and rotamer analyses (pp. 695-697) | html | pdf |
    - 21.6.2.4. Covalent-geometry analyses (p. 697) | html | pdf |
    - 21.6.2.5. Nucleic acid analyses (p. 697) | html | pdf |
    - 21.6.2.6. The overall MolProbity score (p. 697) | html | pdf |
  - 21.6.3. Correction of outliers (pp. 698-699) | html | pdf |
    - 21.6.3.1. Manual rebuilding (p. 698) | html | pdf |
    - 21.6.3.2. Automated corrections (p. 699) | html | pdf |
  - 21.6.4. Other MolProbity utility functions (pp. 699-700) | html | pdf |
    - 21.6.4.1. Interface analysis (p. 699) | html | pdf |
    - 21.6.4.2. Protein loop fitting (p. 699) | html | pdf |
    - 21.6.4.3. Kinemage construction and viewing (p. 699) | html | pdf |
    - 21.6.4.4. Other file types and functions (p. 699) | html | pdf |
    - 21.6.4.5. PDB-format interconversion (pp. 699-700) | html | pdf |
  - 21.6.5. Discussion (p. 700) | html | pdf |
    - 21.6.5.1. Global versus local, absolute versus comparative (p. 700) | html | pdf |
    - 21.6.5.2. Impact on database quality (p. 700) | html | pdf |
  - 21.6.6. MolProbity availability (p. 701) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.6.1.1. An outlier legend, showing each symbol used in a MolProbity multi-criterion kinemage and illustrating the relationship of the three types of all-atom contact to the atomic van der Waals (vdW) surfaces (spheres of small grey dots) (p. 694) | html | pdf |
    - Fig. 21.6.1.2. Two multi-criterion validation kinemages illustrating the successful outcome of an overall process of MolProbity diagnosis and structure improvement (p. 695) | html | pdf |
    - Fig. 21.6.2.1. The simple `flip' correction of a Gln side-chain amide in the 2dq4 threonine 3-dehydrogenase structure (p. 695) | html | pdf |
    - Fig. 21.6.2.2. A MolProbity results summary and sortable multi-criterion chart for the 1n78 Glu tRNA-synthetase complex at 2.1 Å resolution (p. 696) | html | pdf |
    - Fig. 21.6.2.3. The general case Ramachandran kinemage and the C^β deviation kinemage for file 2dq4 (p. 696) | html | pdf |
    - Fig. 21.6.2.4. Close-up of a ribose-pucker outlier in the multi-criterion kinemage for 1n78 , with backbone and bases turned on (p. 698) | html | pdf |
    - Fig. 21.6.3.1. Rebuilding of a backward-fitted Leu side chain in KiNG off-line in the DNA polymerase 1xwl at 1.7 Å resolution (p. 698) | html | pdf |
    - Fig. 21.6.5.1. MolProbity-relevant quality criteria as a function of time for all structures in the PDB at a middle range of resolution, separately fitted before and after introduction of the web site (p. 700) | html | pdf |

Molecular geometry and features
- 22.1. Protein geometry: volumes, areas and distances (pp. 703-712) | html | pdf | chapter contents |
  M. Gerstein and F. M. Richards
  - 22.1.1. Introduction (p. 703) | html | pdf |
  - 22.1.2. Definitions of protein volume (pp. 703-706) | html | pdf |
    - 22.1.2.1. Volume in terms of Voronoi polyhedra: overview (p. 703) | html | pdf |
    - 22.1.2.2. The basic Voronoi construction (pp. 703-704) | html | pdf |
      - 22.1.2.2.1. Integrating on a grid (pp. 703-704) | html | pdf |
      - 22.1.2.2.2. Finding polyhedron vertices (p. 704) | html | pdf |
      - 22.1.2.2.3. Collecting vertices and calculating volumes (p. 704) | html | pdf |
    - 22.1.2.3. Adapting Voronoi polyhedra to proteins (pp. 704-705) | html | pdf |
      - 22.1.2.3.1. Method B and a simplification of it: the ratio method (pp. 704-705) | html | pdf |
      - 22.1.2.3.2. Vertex error (p. 705) | html | pdf |
      - 22.1.2.3.3. `Chopping-down' method of finding vertices (p. 705) | html | pdf |
      - 22.1.2.3.4. Radical-plane method (p. 705) | html | pdf |
    - 22.1.2.4. Delaunay triangulation (pp. 705-706) | html | pdf |
  - 22.1.3. Definitions of protein surface (pp. 706-708) | html | pdf |
    - 22.1.3.1. The problem of the protein surface (p. 706) | html | pdf |
    - 22.1.3.2. Definitions of surface in terms of Voronoi polyhedra (the convex hull) (p. 706) | html | pdf |
    - 22.1.3.3. Definitions of surface in terms of a probe sphere (pp. 707-708) | html | pdf |
      - 22.1.3.3.1. van der Waals surface (VDWS) (p. 707) | html | pdf |
      - 22.1.3.3.2. Solvent-accessible surface (SAS) (p. 707) | html | pdf |
      - 22.1.3.3.3. Molecular surface as the sum of the contact and re-entrant surfaces (MS = CS + RS) (pp. 707-708) | html | pdf |
      - 22.1.3.3.4. Further points (p. 708) | html | pdf |
  - 22.1.4. Definitions of atomic radii (pp. 708-709) | html | pdf |
    - 22.1.4.1. van der Waals radii (pp. 708-709) | html | pdf |
    - 22.1.4.2. The probe radius (p. 709) | html | pdf |
  - 22.1.5. Application of geometry calculations: the measurement of packing (pp. 709-711) | html | pdf |
    - 22.1.5.1. Using volume to measure packing efficiency (pp. 709-710) | html | pdf |
    - 22.1.5.2. The tight packing of the protein core (pp. 710-711) | html | pdf |
    - 22.1.5.3. Looser packing on the surface (p. 711) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.1.2.1. The Voronoi construction in two and three dimensions (p. 703) | html | pdf |
    - Fig. 22.1.2.2. Labelling parts of Voronoi polyhedra (p. 704) | html | pdf |
    - Fig. 22.1.2.3. Positioning of the dividing plane (p. 704) | html | pdf |
    - Fig. 22.1.2.4. The `chopping-down' method of polyhedra construction (p. 705) | html | pdf |
    - Fig. 22.1.2.5. Delaunay triangulation and its relation to the Voronoi construction (p. 706) | html | pdf |
    - Fig. 22.1.3.1. The problem of the protein surface (p. 706) | html | pdf |
    - Fig. 22.1.3.2. Definitions of the protein surface (p. 707) | html | pdf |
    - Fig. 22.1.5.1. Packing efficiency (p. 709) | html | pdf |
  - Tables
    - Table 22.1.4.1. Standard atomic radii (Å) (p. 708) | html | pdf |
    - Table 22.1.4.2. Probe radii and their relation to surface definition (p. 709) | html | pdf |
    - Table 22.1.5.1. Standard residue volumes (p. 710) | html | pdf |
    - Table 22.1.5.2. Standard atomic volumes (p. 710) | html | pdf |
- 22.2. Molecular surfaces: calculations, uses and representations (pp. 713-720) | html | pdf | chapter contents |
  M. S. Chapman and M. L. Connolly
  - 22.2.1. Introduction (pp. 713-714) | html | pdf |
    - 22.2.1.1. Uses of surface-area calculations (p. 713) | html | pdf |
    - 22.2.1.2. Molecular, solvent-accessible and occluded surface areas (pp. 713-714) | html | pdf |
    - 22.2.1.3. Hydration surface (p. 714) | html | pdf |
    - 22.2.1.4. Hydrophobicity (p. 714) | html | pdf |
  - 22.2.2. Calculation of surface area and energies of interaction (pp. 714-715) | html | pdf |
    - 22.2.2.1. Introduction (p. 714) | html | pdf |
    - 22.2.2.2. Lee & Richards planar slices (p. 714) | html | pdf |
    - 22.2.2.3. Connolly dot surface algorithm (p. 714) | html | pdf |
    - 22.2.2.4. Marching-cube algorithm (p. 714) | html | pdf |
    - 22.2.2.5. Complete and connected rolling algorithms (pp. 714-715) | html | pdf |
    - 22.2.2.6. Analytic surface calculations and the Gauss–Bonnet theorem (p. 715) | html | pdf |
    - 22.2.2.7. Approximations to the surface (p. 715) | html | pdf |
    - 22.2.2.8. Extended atoms account for missing hydrogen atoms (p. 715) | html | pdf |
  - 22.2.3. Estimation of binding energies (pp. 715-717) | html | pdf |
    - 22.2.3.1. Hydrophobicity (pp. 715-716) | html | pdf |
    - 22.2.3.2. Estimates of binding energies (p. 716) | html | pdf |
    - 22.2.3.3. Other non-graphical interpretive methods using surface area (pp. 716-717) | html | pdf |
  - 22.2.4. Graphical representations of shape and properties (pp. 717-719) | html | pdf |
    - 22.2.4.1. Realistic (pp. 717-718) | html | pdf |
      - 22.2.4.1.1. Shaded backbone (p. 717) | html | pdf |
      - 22.2.4.1.2. `Connolly' and solid polyhedral surfaces (p. 717) | html | pdf |
      - 22.2.4.1.3. Photorealistic rendering (pp. 717-718) | html | pdf |
      - 22.2.4.1.4. GRASP surfaces (p. 718) | html | pdf |
      - 22.2.4.1.5. Implementations in popular packages (p. 718) | html | pdf |
    - 22.2.4.2. Schematic and two-dimensional representations such as `roadmap' (p. 719) | html | pdf |
  - 22.2.5. Conclusion (p. 719) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.2.1.1. Surfaces in a plane cut through a hypothetical molecule (p. 713) | html | pdf |
    - Fig. 22.2.4.1. GRASP example (p. 716) | html | pdf |
    - Fig. 22.2.4.2. (a) Solvent-accessible surface topology of a rhinovirus 14–drug complex (Kim et al., 1993) (p. 717) | html | pdf |
    - Fig. 22.2.4.3. Different projections illustrated with lysozyme (p. 718) | html | pdf |
  - Tables
    - Table 22.2.3.1. The atomic solvation parameters of Eisenberg & McLachlan (1986) (p. 715) | html | pdf |
- 22.3. Hydrogen bonding in biological macromolecules (pp. 721-729) | html | pdf | chapter contents |
  E. N. Baker
  - 22.3.1. Introduction (p. 721) | html | pdf |
  - 22.3.2. Nature of the hydrogen bond (p. 721) | html | pdf |
  - 22.3.3. Hydrogen-bonding groups (pp. 721-722) | html | pdf |
    - 22.3.3.1. Proteins (pp. 721-722) | html | pdf |
    - 22.3.3.2. Nucleic acids (p. 722) | html | pdf |
  - 22.3.4. Identification of hydrogen bonds: geometrical considerations (pp. 722-723) | html | pdf |
  - 22.3.5. Hydrogen bonding in proteins (pp. 723-726) | html | pdf |
    - 22.3.5.1. Contribution to protein folding, stability and function (p. 723) | html | pdf |
    - 22.3.5.2. Saturation of hydrogen-bond potential (p. 723) | html | pdf |
    - 22.3.5.3. Secondary structures (pp. 723-724) | html | pdf |
      - 22.3.5.3.1. Helices (pp. 723-724) | html | pdf |
      - 22.3.5.3.2. β-sheets (p. 724) | html | pdf |
      - 22.3.5.3.3. Turns (p. 724) | html | pdf |
      - 22.3.5.3.4. Aspects of in-plane geometry (p. 724) | html | pdf |
    - 22.3.5.4. Side-chain hydrogen bonding (pp. 724-725) | html | pdf |
    - 22.3.5.5. Hydrogen bonds with water molecules (pp. 725-726) | html | pdf |
  - 22.3.6. Hydrogen bonding in nucleic acids (pp. 726-727) | html | pdf |
    - 22.3.6.1. DNA (p. 726) | html | pdf |
    - 22.3.6.2. RNA (pp. 726-727) | html | pdf |
  - 22.3.7. Non-conventional hydrogen bonds (pp. 727-728) | html | pdf |
    - 22.3.7.1. C—H···O hydrogen bonds (p. 727) | html | pdf |
    - 22.3.7.2. Hydrogen bonds involving sulfur atoms (p. 727) | html | pdf |
    - 22.3.7.3. Amino–aromatic hydrogen bonding (p. 728) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.3.2.1. Hydrogen-bonding configurations (p. 721) | html | pdf |
    - Fig. 22.3.3.1. Hydrogen-bonding potential of protein functional groups (p. 722) | html | pdf |
    - Fig. 22.3.3.2. Hydrogen-bonding potential of nucleic acid bases guanine (G), adenine (A), cytosine (C) and thymine (T) in their normal canonical forms (p. 722) | html | pdf |
    - Fig. 22.3.4.1. Suggested criteria for identifying likely hydrogen bonds (p. 723) | html | pdf |
    - Fig. 22.3.5.1. Distribution of side-chain–main-chain hydrogen bonds as a function of the separation (Δ a.a.) along the polypeptide between the side-chain (sch) and main-chain (mch) groups involved (p. 725) | html | pdf |
    - Fig. 22.3.5.2. Schematic representations of common classes of side-chain–main-chain hydrogen bonds (a) in turns and (b) at helix N-termini (p. 725) | html | pdf |
    - Fig. 22.3.5.3. Typical scatter plots showing the distribution of hydrogen-bonding partners around protein side chains, shown for (a) Asn or Gln and (b) Tyr (p. 726) | html | pdf |
    - Fig. 22.3.6.1. Hydrogen-bonding interactions in RNA tertiary structure (p. 727) | html | pdf |
- 22.4. Electrostatic interactions in proteins (pp. 730-735) | html | pdf | chapter contents |
  K. A. Sharp
  - 22.4.1. Introduction (p. 730) | html | pdf |
  - 22.4.2. Theory (pp. 730-732) | html | pdf |
    - 22.4.2.1. The response of the system to electrostatic fields (pp. 730-731) | html | pdf |
    - 22.4.2.2. Dependence of the potential on the charge distribution (p. 731) | html | pdf |
    - 22.4.2.3. The concepts of screening, reaction potentials, solvation, dielectric, polarity and polarizability (pp. 731-732) | html | pdf |
    - 22.4.2.4. Calculation of energies and forces (p. 732) | html | pdf |
    - 22.4.2.5. Numerical methods (p. 732) | html | pdf |
  - 22.4.3. Applications (pp. 732-734) | html | pdf |
    - 22.4.3.1. Electrostatic potential distributions (pp. 732-733) | html | pdf |
    - 22.4.3.2. Charge-transfer equilibria (pp. 733-734) | html | pdf |
    - 22.4.3.3. Electrostatic contributions to binding energy (p. 734) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.4.3.1. (a) The proteolytic enzyme thrombin (yellow backbone worm) complexed with an inhibitor, hirudin (blue backbone worm) (p. 733) | html | pdf |
- 22.5. The relevance of the Cambridge Structural Database in protein crystallography (pp. 736-748) | html | pdf | chapter contents |
  F. H. Allen, J. C. Cole and M. L. Verdonk
  - 22.5.1. Introduction (p. 736) | html | pdf |
  - 22.5.2. The CSD and the PDB: data acquisition and data quality (pp. 736-737) | html | pdf |
    - 22.5.2.1. Statistical inferences (p. 736) | html | pdf |
    - 22.5.2.2. Data acquisition and completeness (p. 737) | html | pdf |
    - 22.5.2.3. Standard formats: CIF and mmCIF (p. 737) | html | pdf |
    - 22.5.2.4. Structure validation (p. 737) | html | pdf |
  - 22.5.3. Structural knowledge from the CSD (pp. 737-738) | html | pdf |
    - 22.5.3.1. The CSD software system (p. 737) | html | pdf |
    - 22.5.3.2. CSD structures and substructures of relevance to protein studies (p. 737) | html | pdf |
    - 22.5.3.3. Geometrical parameters of relevance to protein studies (pp. 737-738) | html | pdf |
  - 22.5.4. Intramolecular geometry (pp. 738-740) | html | pdf |
    - 22.5.4.1. Mean molecular dimensions (pp. 738-739) | html | pdf |
    - 22.5.4.2. Conformational information (p. 739) | html | pdf |
    - 22.5.4.3. Crystallographic conformations and energies (pp. 739-740) | html | pdf |
    - 22.5.4.4. Conformational libraries (p. 740) | html | pdf |
    - 22.5.4.5. Metal coordination geometry (p. 740) | html | pdf |
  - 22.5.5. Intermolecular data (pp. 740-745) | html | pdf |
    - 22.5.5.1. van der Waals radii (p. 740) | html | pdf |
    - 22.5.5.2. Hydrogen-bond geometry and directionality (pp. 740-741) | html | pdf |
    - 22.5.5.3. C—H···X hydrogen bonds (pp. 741-742) | html | pdf |
    - 22.5.5.4. O—H···π and N—H···π hydrogen bonds (p. 742) | html | pdf |
    - 22.5.5.5. Other non-covalent interactions (p. 742) | html | pdf |
    - 22.5.5.6. Intermolecular motif formation in small-molecule crystal structures (pp. 742-743) | html | pdf |
    - 22.5.5.7. The answer `no' (p. 743) | html | pdf |
    - 22.5.5.8. IsoStar: a library of non-bonded interactions (p. 743) | html | pdf |
    - 22.5.5.9. Protein–ligand binding (pp. 743-745) | html | pdf |
    - 22.5.5.10. Modelling applications that use CSD data (p. 745) | html | pdf |
  - 22.5.6. Conclusion (p. 745) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.5.2.1. (a) Growth rate of the CSD and (b) growth rate of the PDB, in terms of the numbers of structures published per annum for the period 1970–1995 (p. 736) | html | pdf |
    - Fig. 22.5.4.1. Distribution of torsion angles in C(sp³)—S—S—C(sp³) substructures located in the CSD (p. 739) | html | pdf |
    - Fig. 22.5.5.1. The IsoStar knowledge-based library of intermolecular interactions: interaction of O—H donors (contact groups) with one of the >C=O acceptors of a carboxylate group (the central group) (p. 741) | html | pdf |
    - Fig. 22.5.5.2. Distribution of O—H donors around ether oxygen acceptors (CSD data from the IsoStar library, see text) (p. 741) | html | pdf |
    - Fig. 22.5.5.3. Distribution of oxygen atoms around C(aromatic)—I (CSD data from the IsoStar library, see text) (p. 743) | html | pdf |
    - Fig. 22.5.5.4. Pairwise comparison of intermolecular-interaction density maps from the CSD and the PDB (p. 744) | html | pdf |
  - Tables
    - Table 22.5.3.1. Summary of amino-acid and peptide structures available in the CSD (April 1998, 181 309 entries) (p. 738) | html | pdf |
    - Table 22.5.3.2. CSD entry statistics for selected metal-containing structures (p. 738) | html | pdf |
    - Table 22.5.5.1. Residual densities for carboxylic acid groups (p. 745) | html | pdf |

Structural analysis and classification
- 23.1. Protein-fold classification (pp. 749-751) | html | pdf | chapter contents |
  C. Orengo and J. Thornton
  - References | html | pdf |
  - Figures
    - Fig. 23.1.1. Schematic representation of the (C)lass, (A)rchitecture and (T)opology/fold levels in the CATH database (p. 750) | html | pdf |
    - Fig. 23.1.2. `CATHerine wheel' plot showing the distribution of non-homologous structures (p. 750) | html | pdf |
- 23.2. Locating domains in three-dimensional structures (pp. 752-754) | html | pdf | chapter contents |
  L. Holm and C. Sander
  - 23.2.1. Introduction (p. 752) | html | pdf |
  - 23.2.2. Compactness (p. 752) | html | pdf |
  - 23.2.3. Recurrence (pp. 752-753) | html | pdf |
  - 23.2.4. Conclusion (p. 753) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.2.1.1. The structure of diphtheria toxin (Bennett & Eisenberg, 1994) beautifully illustrates domains as structural, functional and evolutionary units (p. 753) | html | pdf |
- 23.3. Protein–ligand interactions (pp. 755-765) | html | pdf | chapter contents |
  A. E. Hodel and F. A. Quiocho
  - 23.3.1. Introduction (p. 755) | html | pdf |
  - 23.3.2. Protein–carbohydrate interactions (pp. 755-756) | html | pdf |
    - 23.3.2.1. Carbohydrate recognition at the atomic level (pp. 755-756) | html | pdf |
  - 23.3.3. Metals (pp. 756-757) | html | pdf |
    - 23.3.3.1. Metals important in protein function and structure (pp. 756-757) | html | pdf |
  - 23.3.4. Protein–nucleic acid interactions (pp. 757-760) | html | pdf |
    - 23.3.4.1. The DNA double helix (pp. 757-759) | html | pdf |
    - 23.3.4.2. Single-stranded sequence-nonspecific DNA–protein interactions (p. 759) | html | pdf |
    - 23.3.4.3. RNA (p. 759) | html | pdf |
    - 23.3.4.4. Transfer RNA (p. 759) | html | pdf |
    - 23.3.4.5. Stem loops (pp. 759-760) | html | pdf |
    - 23.3.4.6. Single-stranded sequence-nonspecific RNA–protein interactions (p. 760) | html | pdf |
    - 23.3.4.7. The recognition of alkylated bases (p. 760) | html | pdf |
  - 23.3.5. Phosphate and sulfate (pp. 761-763) | html | pdf |
    - 23.3.5.1. Dominant role of local dipoles in stabilization of isolated charges (p. 762) | html | pdf |
    - 23.3.5.2. Short hydrogen bonds (p. 763) | html | pdf |
    - 23.3.5.3. Non-complementary negative electrostatic surface potential of protein sites specific for anions (p. 763) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.3.2.1. The atomic recognition of carbohydrates by a protein (p. 756) | html | pdf |
    - Fig. 23.3.4.1. A schematic diagram of the base pairs of DNA showing the hydrogen-bonding groups which may be used in the sequence-specific recognition of DNA (p. 758) | html | pdf |
    - Fig. 23.3.4.2. (a) A space-filling model of B-DNA showing the relative accessibility of the major and minor grooves (p. 758) | html | pdf |
    - Fig. 23.3.4.3. A comparison of the orientations of α-helices bound in the major groove (p. 758) | html | pdf |
    - Fig. 23.3.4.4. The sequence-nonspecific recognition of single-stranded nucleic acid (p. 760) | html | pdf |
    - Fig. 23.3.4.5. The specific recognition of the messenger RNA 7-methylguanosine cap (p. 761) | html | pdf |
    - Fig. 23.3.5.1. 12 hydrogen-bonding interactions between the phosphate-binding protein (PBP) and phosphate (p. 762) | html | pdf |
    - Fig. 23.3.5.2. Seven hydrogen-bonding interactions between the sulfate-binding protein (SBP) and sulfate (p. 762) | html | pdf |
    - Fig. 23.3.5.3. Electrostatic surface potential of (a) the phosphate-binding protein and (b) flavodoxin (p. 763) | html | pdf |
  - Tables
    - Table 23.3.3.1. Metal ions associated with proteins (p. 756) | html | pdf |
- 23.4. Nucleic acids (pp. 766-799) | html | pdf | chapter contents |
  R. E. Dickerson
  - 23.4.1. Introduction (p. 766) | html | pdf |
  - 23.4.2. Helix parameters (pp. 766-773) | html | pdf |
    - 23.4.2.1. Backbone geometry (p. 766) | html | pdf |
    - 23.4.2.2. Sugar ring conformations (pp. 766-767) | html | pdf |
    - 23.4.2.3. Base pairing (pp. 767-769) | html | pdf |
    - 23.4.2.4. Helix parameters (pp. 770-773) | html | pdf |
    - 23.4.2.5. Syn/anti glycosyl bond geometry (p. 773) | html | pdf |
  - 23.4.3. Comparison of A, B and Z helices (pp. 773-779) | html | pdf |
    - 23.4.3.1. x displacement and groove depth (p. 774) | html | pdf |
    - 23.4.3.2. Glycosyl bond geometry (pp. 774-775) | html | pdf |
    - 23.4.3.3. Sugar ring conformations (p. 775) | html | pdf |
    - 23.4.3.4. Helical twist and rise, and propeller twist (pp. 775-777) | html | pdf |
    - 23.4.3.5. Allowable RNA helices (p. 777) | html | pdf |
    - 23.4.3.6. Biological applications of A, B and Z helices (pp. 777-778) | html | pdf |
    - 23.4.3.7. `Watson–Crick' Z-DNA (pp. 778-779) | html | pdf |
  - 23.4.4. Sequence–structure relationships in B-DNA (pp. 779-784) | html | pdf |
    - 23.4.4.1. Sequence-dependent deformability (pp. 780-783) | html | pdf |
      - 23.4.4.1.1. Minor groove width (pp. 780-781) | html | pdf |
      - 23.4.4.1.2. Helix bending (pp. 781-783) | html | pdf |
    - 23.4.4.2. A-tract bending (pp. 783-784) | html | pdf |
  - 23.4.5. Summary (p. 784) | html | pdf |
  - Appendix 23.4.1. X-ray analyses of A, B and Z helices (pp. 787-797) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.4.1.1. `Hot wire' painting of A-DNA by Irving Geis (p. 767) | html | pdf |
    - Fig. 23.4.1.2. Infinite A-DNA helix (p. 768) | html | pdf |
    - Fig. 23.4.1.3. Infinite B-DNA helix (p. 768) | html | pdf |
    - Fig. 23.4.1.4. Infinite Z-DNA helix (p. 769) | html | pdf |
    - Fig. 23.4.2.1. Unrolled schematic of A- or B-DNA, viewed into the minor groove (p. 769) | html | pdf |
    - Fig. 23.4.2.2. Sugar–phosphate backbone of RNA and DNA polynucleotides (p. 770) | html | pdf |
    - Fig. 23.4.2.3. Definition of torsion angles (p. 770) | html | pdf |
    - Fig. 23.4.2.4. The three most common furanose ring geometries (p. 770) | html | pdf |
    - Fig. 23.4.2.5. Potential plot of all furanose ring conformations (p. 771) | html | pdf |
    - Fig. 23.4.2.6. Plot of observed sugar conformations in 296 nucleotides of A-DNA (crosses) and 280 of B-DNA (open circles) (p. 771) | html | pdf |
    - Fig. 23.4.2.7. A·T and G·C base pairs with minor groove edge below and major groove edge above (p. 772) | html | pdf |
    - Fig. 23.4.2.8. Alternative purines and pyrimidines, and possible base pairings (p. 772) | html | pdf |
    - Fig. 23.4.2.9. Watson–Crick pairing of a purine (A or G) with a pyrimidine to its right (T or C), and Hoogsteen pairing of the same purine with a pyrimidine above it (p. 772) | html | pdf |
    - Fig. 23.4.2.10. Definitions of local reference axes (x, y, z) at the first two base pairs of an n-base-pair double helix (p. 772) | html | pdf |
    - Fig. 23.4.2.11. Local helix parameters involving rotations (p. 773) | html | pdf |
    - Fig. 23.4.2.12. Local helix parameters involving translations (p. 773) | html | pdf |
    - Fig. 23.4.2.13. Syn versus anti orientation about the glycosyl bond connecting sugar and base (p. 773) | html | pdf |
    - Fig. 23.4.3.1. The A-DNA stereo pair drawing from which Fig. 23.4.1.2 was derived (p. 774) | html | pdf |
    - Fig. 23.4.3.2. The B-DNA stereo pair drawing from which Fig. 23.4.1.3 was derived (p. 775) | html | pdf |
    - Fig. 23.4.3.3. The Z-DNA stereo pair drawing from which Fig. 23.4.1.4 was derived (p. 776) | html | pdf |
    - Fig. 23.4.3.4. Glycosyl conformation and chain sense (p. 777) | html | pdf |
    - Fig. 23.4.3.5. The role of the C2′-OH in RNA helix geometry (p. 778) | html | pdf |
    - Fig. 23.4.3.6. Interconversion of a B to a Z helix (p. 778) | html | pdf |
    - Fig. 23.4.3.7. Z(WC)-DNA, or `Watson–Crick Z-DNA' (p. 779) | html | pdf |
    - Fig. 23.4.4.1. Structure of C-A-A-A-G-A-A-A-A-G (p. 780) | html | pdf |
    - Fig. 23.4.4.2. Relationship between minor groove width and propeller twist (p. 780) | html | pdf |
    - Fig. 23.4.4.3. Structure of the 1:1 complex of netropsin with C-G-C-G-A-A-T-T-C-G-C-G (p. 781) | html | pdf |
    - Fig. 23.4.4.4. Structure of the 2:1 complex of a di-imidazole lexitropsin with C-A-T-G-G-C-C-A-T-G (p. 782) | html | pdf |
    - Fig. 23.4.4.5. DNA duplex (red and blue strands) looped around IHF or integration host factor (p. 782) | html | pdf |
    - Fig. 23.4.4.6. Roll-angle plots for sequence-specific DNA–protein complexes with lacI (top) and purR (bottom) (p. 784) | html | pdf |
    - Fig. 23.4.4.7. Bending via roll at T-A steps in TBP or the TATA-binding protein (top) and in γδ-resolvase (bottom) (p. 784) | html | pdf |
    - Fig. 23.4.4.8. Representative base-pair steps from B-DNA single-crystal X-ray analyses (p. 785) | html | pdf |
    - Fig. 23.4.4.9. Slide versus roll plots for six of the ten possible base-pair steps (p. 786) | html | pdf |
  - Tables
    - Table 23.4.2.1. Average torsion-angle properties of A-, B- and Z-DNA (°) (p. 771) | html | pdf |
    - Table 23.4.2.2. Sugar ring conformations, pseudorotation angles and torsion angle δ (p. 771) | html | pdf |
    - Table 23.4.3.1. Comparison of structures of A, B and Z helices (p. 777) | html | pdf |
    - Table 23.4.4.1. Sequence-dependent differential deformability in B-DNA. I. The Major Canon (p. 783) | html | pdf |
    - Table 23.4.4.2. Sequence-dependent differential deformability in B-DNA. II. The Minor Canon (p. 785) | html | pdf |
- 23.5. Solvent structure (pp. 800-820) | html | pdf | chapter contents |
  C. Mattos and D. Ringe
  - 23.5.1. Introduction (pp. 800-801) | html | pdf |
  - 23.5.2. Determination of water molecules (pp. 801-802) | html | pdf |
  - 23.5.3. Structural features of protein–water interactions derived from database analysis (pp. 802-808) | html | pdf |
    - 23.5.3.1. Water distribution around the individual amino-acid residues in protein structures (pp. 802-805) | html | pdf |
    - 23.5.3.2. The effect of secondary structure on protein–water interactions (pp. 805-806) | html | pdf |
    - 23.5.3.3. The effect of tertiary structure on protein–water interactions (pp. 806-807) | html | pdf |
    - 23.5.3.4. Water mediation of protein–ligand interactions (pp. 807-808) | html | pdf |
  - 23.5.4. Water structure in groups of well studied proteins (pp. 808-814) | html | pdf |
    - 23.5.4.1. Crystal structures of homologous proteins (pp. 808-809) | html | pdf |
      - 23.5.4.1.1. Serine proteases of the trypsin family (p. 808) | html | pdf |
      - 23.5.4.1.2. Legume lectin family (pp. 808-809) | html | pdf |
    - 23.5.4.2. Multiple crystal structures of the same protein (pp. 809-814) | html | pdf |
      - 23.5.4.2.1. Elastase (pp. 809-812) | html | pdf |
      - 23.5.4.2.2. T4 lysozyme (pp. 812-813) | html | pdf |
      - 23.5.4.2.3. Ribonuclease T1 (p. 813) | html | pdf |
      - 23.5.4.2.4. Ribonuclease A (pp. 813-814) | html | pdf |
      - 23.5.4.2.5. Protein kinase A (p. 814) | html | pdf |
    - 23.5.4.3. Summary (p. 814) | html | pdf |
  - 23.5.5. The classic models: small proteins with high-resolution crystal structures (pp. 814-815) | html | pdf |
    - 23.5.5.1. Crambin (pp. 814-815) | html | pdf |
    - 23.5.5.2. Bovine pancreatic trypsin inhibitor (p. 815) | html | pdf |
    - 23.5.5.3. Summary (p. 815) | html | pdf |
  - 23.5.6. Water molecules as mediators of complex formation (pp. 815-817) | html | pdf |
    - 23.5.6.1. Antigen–antibody association (pp. 815-816) | html | pdf |
    - 23.5.6.2. Protein–DNA recognition (p. 816) | html | pdf |
    - 23.5.6.3. Cooperativity in dimeric haemoglobin (pp. 816-817) | html | pdf |
    - 23.5.6.4. Summary (p. 817) | html | pdf |
  - 23.5.7. Conclusions and future perspectives (pp. 817-818) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.5.3.1. Distribution of water-molecule sites (p. 803) | html | pdf |
    - Fig. 23.5.3.2. Distribution of atomic hydration values (p. 804) | html | pdf |
    - Fig. 23.5.3.3. Diagram of edge (W1), end (W2) and middle (W3) categories of interactions of water molecules with main-chain atoms in antiparallel β-sheets (p. 805) | html | pdf |
    - Fig. 23.5.3.4. Diagram of the hydrogen bonds in the α-helical structure in actinidin (p. 806) | html | pdf |
    - Fig. 23.5.3.5. Schematic illustration of water molecules bound in different types of grooves between protein and ligand (p. 807) | html | pdf |
    - Fig. 23.5.4.1. Stereoview of the set of 21 highly conserved buried waters in eukaryotic serine proteases (p. 808) | html | pdf |
    - Fig. 23.5.4.2. View of the 33 conserved hydration sites in the lentil lectin crystal structures superimposed on the backbone of the lentil lectin dimer (p. 809) | html | pdf |
    - Fig. 23.5.4.3. A $[2F_{o} - F_{c}]$ electron-density map contoured at the 1.2σ level shows a distinct ellipsoidal density for acetonitrile 707 and a spherical density for a nearby water molecule (p. 809) | html | pdf |
    - Fig. 23.5.4.4. Crystal structure of porcine pancreatic elastase represented as a ribbon diagram using MOLSCRIPT (Kraulis, 1991) (p. 810) | html | pdf |
    - Fig. 23.5.4.5. Elastase structure represented as in Fig. 23.5.4.4. The crystallographic water molecules found in channels in 11 superimposed elastase structures solved in a variety of solvents are shown in yellow (p. 811) | html | pdf |
    - Fig. 23.5.4.6. Elastase structure represented as in Fig. 23.5.4.4. The crystallographic water molecules involved in crystal contacts in 11 superimposed elastase structures solved in a variety of solvents are shown in green (p. 811) | html | pdf |
    - Fig. 23.5.4.7. Elastase structure represented as in Fig. 23.5.4.4. The surface crystallographic water molecules found in 11 superimposed elastase structures solved in a variety of solvents are shown in blue (p. 811) | html | pdf |
    - Fig. 23.5.4.8. Elastase structure represented as in Fig. 23.5.4.4. The 1661 water molecules found in 11 superimposed elastase structures of elastase are colour-coded as in Figs. 23.5.4.4–23.5.4.7 (p. 812) | html | pdf |
    - Fig. 23.5.4.9. Distribution of solvent-binding sites in 18 mutant T4 lysozymes from ten refined crystal structures (p. 812) | html | pdf |
    - Fig. 23.5.4.10. Three-dimensional structure of RNase T1 (p. 813) | html | pdf |
    - Fig. 23.5.4.11. Overall structure of RNase A (p. 813) | html | pdf |
    - Fig. 23.5.5.1. van der Waals surface diagram of the water pentagons A, C, D and E in crambin viewed in the negative a direction (p. 815) | html | pdf |
    - Fig. 23.5.6.1. Scapharca HbI interface water molecules (p. 817) | html | pdf |
  - Tables
    - Table 23.5.3.1. Specific hydrophilicity values for protein atoms (p. 804) | html | pdf |
    - Table 23.5.4.1. Multiple-solvent crystal structures of elastase (p. 810) | html | pdf |
- 23.6. Halogen interactions in biomolecular crystal structures (pp. 821-826) | html | pdf | chapter contents |
  M. J. Vallejos, P. Auffinger and P. S. Ho
  - 23.6.1. Introduction (p. 821) | html | pdf |
  - 23.6.2. Classical treatment of halogen interactions (pp. 821-822) | html | pdf |
    - 23.6.2.1. Non-specific hydrophobic effects (p. 821) | html | pdf |
    - 23.6.2.2. Substituent effects (pp. 821-822) | html | pdf |
  - 23.6.3. Electrostatic molecular halogen interactions (pp. 822-825) | html | pdf |
    - 23.6.3.1. Biological halogen bonds (pp. 822-825) | html | pdf |
    - 23.6.3.2. Other halogen-specific electrostatic interactions in biological macromolecules (p. 825) | html | pdf |
  - 23.6.4. Concluding remarks (p. 825) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.6.1.1. Examples of electrostatic interactions of halogenated ligands with proteins (p. 821) | html | pdf |
    - Fig. 23.6.3.1. The single-crystal structure of the DNA sequence d(CCAGTACbrUGG), where brU is 5-bromouracil (Br atom shown as a sphere), as a four-stranded Holliday junction (p. 822) | html | pdf |
    - Fig. 23.6.3.2. Properties of halogen bonds (p. 823) | html | pdf |
    - Fig. 23.6.3.3. The orthogonal relationship between hydrogen bonds and X bonds that share common carbonyl O atoms as acceptors (p. 824) | html | pdf |
    - Fig. 23.6.3.4. Competition assay to measure the energies of X bonds versus hydrogen bonds using a DNA junction (p. 824) | html | pdf |
  - Tables
    - Table 23.6.1.1. Interactions in crystal structures in the Protein Data Bank (p. 822) | html | pdf |
    - Table 23.6.2.1. Physical properties of molecular halogens (p. 822) | html | pdf |

Crystallographic databases
- 24.1. The Worldwide Protein Data Bank (pp. 827-832) | html | pdf | chapter contents |
  H. M. Berman, K. Henrick, G. Kleywegt, H. Nakamura and J. Markley
  - 24.1.1. Introduction (p. 827) | html | pdf |
  - 24.1.2. Data acquisition and processing (pp. 827-829) | html | pdf |
    - 24.1.2.1. Content of the data collected by the wwPDB (p. 827) | html | pdf |
    - 24.1.2.2. Data deposition sites (p. 827) | html | pdf |
    - 24.1.2.3. Validation and annotation (pp. 827-828) | html | pdf |
    - 24.1.2.4. Data processing statistics (p. 829) | html | pdf |
    - 24.1.2.5. Data uniformity (p. 829) | html | pdf |
  - 24.1.3. Data access (pp. 829-831) | html | pdf |
    - 24.1.3.1. ftp (p. 829) | html | pdf |
    - 24.1.3.2. Websites (pp. 829-831) | html | pdf |
      - 24.1.3.2.1. RCSB PDB (pp. 829-830) | html | pdf |
      - 24.1.3.2.2. PDBj (p. 830) | html | pdf |
      - 24.1.3.2.3. PDBe (pp. 830-831) | html | pdf |
      - 24.1.3.2.4. BMRB (p. 831) | html | pdf |
  - 24.1.4. Future (p. 831) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.1.2.1. Growth chart of the PDB showing the total number of structures available in the PDB archive per year (as of 31 May 2011) and highlighting example structures from different time periods (p. 829) | html | pdf |
    - Fig. 24.1.2.2. (a) Distribution of structures by experimental type (as of 31 May 2011) (p. 830) | html | pdf |
  - Tables
    - Table 24.1.2.1. Content of data in the PDB (p. 828) | html | pdf |
- 24.2. The Nucleic Acid Database (pp. 833-837) | html | pdf | chapter contents |
  B. Schneider, J. de la Cruz, S. Dutta, Z. Feng, L. Chen, J. Westbrook, H. Yang, J. Young, C. Zardecki and H. M. Berman
  - 24.2.1. Introduction (p. 833) | html | pdf |
  - 24.2.2. Data processing and validation (pp. 833-834) | html | pdf |
  - 24.2.3. The database (pp. 834-835) | html | pdf |
    - 24.2.3.1. Information content of the NDB (p. 834) | html | pdf |
    - 24.2.3.2. User web access (p. 834) | html | pdf |
    - 24.2.3.3. Query capabilities (p. 835) | html | pdf |
    - 24.2.3.4. Atlas pages (p. 835) | html | pdf |
  - 24.2.4. Distribution of information (p. 835) | html | pdf |
    - 24.2.4.1. Structural coordinates and experimental data (p. 835) | html | pdf |
    - 24.2.4.2. Standards and software tools (p. 835) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.2.1.1. Growth of the NDB (p. 833) | html | pdf |
    - Fig. 24.2.3.1. NDB Atlas entry for a structure of ribonuclease P RNA, UR0027 (p. 836) | html | pdf |
  - Tables
    - Table 24.2.3.1. The information content of the NDB (p. 834) | html | pdf |
    - Table 24.2.3.2. Reports automatically generated for searches of the NDB (p. 835) | html | pdf |
- 24.3. The Biological Macromolecule Crystallization Database (pp. 838-842) | html | pdf | chapter contents |
  D. T. Gallagher and M. Tung
  - 24.3.1. Introduction (p. 838) | html | pdf |
  - 24.3.2. History of the BMCD (p. 838) | html | pdf |
  - 24.3.3. BMCD data (pp. 838-839) | html | pdf |
  - 24.3.4. Web interface (p. 839) | html | pdf |
  - 24.3.5. Reproducing published crystallization procedures (pp. 839-840) | html | pdf |
  - 24.3.6. Crystallization screens (p. 840) | html | pdf |
  - 24.3.7. A general crystallization procedure (pp. 840-841) | html | pdf |
  - 24.3.8. The future of the BMCD (p. 841) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.3.3.1. Trends in the completeness of BMCD crystallization conditions (p. 839) | html | pdf |
    - Fig. 24.3.7.1. A general crystallization strategy based on the data contained in the BMCD (p. 840) | html | pdf |

A historical perspective
- 25.1. How the structure of lysozyme was actually determined (pp. 845-872) | html | pdf | chapter contents |
  C. C. F. Blake, R. H. Fenn, L. N. Johnson, D. F. Koenig, G. A. Mair, A. C. T. North, J. W. H. Oldham, D. C. Phillips, R. J. Poljak, V. R. Sarma and C. A. Vernon
  - 25.1.1. Introduction (p. 845) | html | pdf |
  - 25.1.2. Structure analysis at 6 Å resolution (pp. 845-854) | html | pdf |
    - 25.1.2.1. Technical facilities (p. 845) | html | pdf |
    - 25.1.2.2. Lysozyme crystallization (p. 846) | html | pdf |
    - 25.1.2.3. Preparation of heavy-atom derivatives (pp. 846-847) | html | pdf |
    - 25.1.2.4. Determination of heavy-atom positions (pp. 847-848) | html | pdf |
      - 25.1.2.4.1. The mercuri-iodide (K₂HgI₄) derivative (p. 847) | html | pdf |
      - 25.1.2.4.2. The palladium chloride (K₂PdCl₄) derivative (p. 847) | html | pdf |
      - 25.1.2.4.3. The o-mercurihydroxytoluene p-sulfonate (MHTS) derivative (p. 847) | html | pdf |
      - 25.1.2.4.4. Other potential derivatives (pp. 847-848) | html | pdf |
    - 25.1.2.5. Refinement of heavy-atom parameters (p. 848) | html | pdf |
    - 25.1.2.6. Analysis in three dimensions (pp. 848-852) | html | pdf |
      - 25.1.2.6.1. X-ray intensity measurements (pp. 848-850) | html | pdf |
      - 25.1.2.6.2. Data processing (pp. 850-851) | html | pdf |
      - 25.1.2.6.3. The absolute scale of the intensities (p. 851) | html | pdf |
      - 25.1.2.6.4. Re-assessment of heavy-atom derivatives (pp. 851-852) | html | pdf |
    - 25.1.2.7. Phase determination at 6 Å resolution (p. 852) | html | pdf |
    - 25.1.2.8. The electron-density map of lysozyme at 6 Å resolution (pp. 853-854) | html | pdf |
  - 25.1.3. Analysis of the structure at 2 Å resolution (pp. 854-866) | html | pdf |
    - 25.1.3.1. Heavy-atom derivatives at 2 Å resolution (pp. 855-856) | html | pdf |
    - 25.1.3.2. Intensity measurements (pp. 856-858) | html | pdf |
    - 25.1.3.3. The second low-resolution map at 6 Å (p. 858) | html | pdf |
    - 25.1.3.4. Intensity measurements at high resolution (pp. 858-859) | html | pdf |
      - 25.1.3.4.1. Experimental methods (pp. 858-859) | html | pdf |
      - 25.1.3.4.2. Diffractometer output (p. 859) | html | pdf |
    - 25.1.3.5. Data processing (pp. 859-860) | html | pdf |
      - 25.1.3.5.1. Absorption corrections (p. 860) | html | pdf |
    - 25.1.3.6. Further stages of data processing (pp. 860-861) | html | pdf |
    - 25.1.3.7. The crystal-type problem (pp. 861-862) | html | pdf |
    - 25.1.3.8. Final refinement of heavy-atom parameters (p. 862) | html | pdf |
    - 25.1.3.9. Calculation of phase values (pp. 862-863) | html | pdf |
    - 25.1.3.10. The electron-density map at 2 Å resolution (pp. 863-864) | html | pdf |
    - 25.1.3.11. Map interpretation and model building (pp. 864-866) | html | pdf |
  - 25.1.4. Structural studies on the biological function of lysozyme (pp. 866-871) | html | pdf |
    - 25.1.4.1. Lysozyme substrates (p. 866) | html | pdf |
    - 25.1.4.2. The crystal structure of GlcNAc (pp. 866-867) | html | pdf |
    - 25.1.4.3. Low-resolution binding studies of lysozyme with GlcNAc and other sugars (p. 867) | html | pdf |
    - 25.1.4.4. Binding studies of lysozyme with tri-N-acetyl-chitotriose, (GlcNAc)₃, at 2 Å resolution (pp. 867-868) | html | pdf |
    - 25.1.4.5. Proposals for the catalytic mechanism of lysozyme (pp. 868-871) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 25.1.2.10. Phase determination for reflection 424 (p. 852) | html | pdf |
    - Fig. 25.1.2.11. Electron-density difference syntheses showing the main sites of substitution and subsidiary sites with low occupancy in the PdCl₄ and MHTS derivatives (Fenn, 1964) (p. 853) | html | pdf |
    - Fig. 25.1.2.12. Electron-density distribution in lysozyme at 6 Å resolution viewed parallel to the c axis (p. 853) | html | pdf |
    - Fig. 25.1.2.13. Views of a 6 Å resolution model of the regions in which the electron density exceeds about 0.53 e Å⁻³ (p. 854) | html | pdf |
    - Fig. 25.1.2.1. Tetragonal lysozyme crystals with well developed {110} faces (left-hand crystal) and small {110} faces (right-hand crystal) (p. 846) | html | pdf |
    - Fig. 25.1.2.2. Difference-Patterson h0l projection map for the derivative obtained with K₂PdCl₄ (p. 847) | html | pdf |
    - Fig. 25.1.2.3. Difference-Patterson hk0 projection for the derivative obtained with MHTS (p. 847) | html | pdf |
    - Fig. 25.1.2.4. Reciprocal-space diagrams showing the direction of the incident X-ray beam, the Ewald sphere and the genesis of a reflection (a) in an equatorial plane and (b) in the equi-inclination setting (p. 848) | html | pdf |
    - Fig. 25.1.2.5. Crystal mounting (p. 849) | html | pdf |
    - Fig. 25.1.2.6. Absorption curve (p. 850) | html | pdf |
    - Fig. 25.1.2.7. Typical output from the linear diffractometer (p. 850) | html | pdf |
    - Fig. 25.1.2.8. Format of monitor output in which the computer lists reflections that fail the tests for format or significance (p. 850) | html | pdf |
    - Fig. 25.1.2.9. Three-dimensional $[|\Delta F|^{2}]$ syntheses for the PdCl₄ and MHTS derivatives (p. 851) | html | pdf |
    - Fig. 25.1.3.10. The amino-acid sequence of hen egg-white lysozyme (Canfield & Liu, 1965) (p. 864) | html | pdf |
    - Fig. 25.1.3.11. Schematic drawing of the main-chain conformation of lysozyme (p. 865) | html | pdf |
    - Fig. 25.1.3.12. Stereo-photographs of a model of the lysozyme molecule to a scale of 2 cm to 1 Å (p. 865) | html | pdf |
    - Fig. 25.1.3.1. Perspective drawing of the sphere of reflection showing inclination geometry with simultaneous reflections (reciprocal-lattice points P and Q) from levels symmetrically related by the flat-cone setting (p. 857) | html | pdf |
    - Fig. 25.1.3.2. The $[a^{*}b^{*}]$ plane of the reciprocal lattice oriented to rotate about the $[[\bar{1}10]]$ axis (p. 857) | html | pdf |
    - Fig. 25.1.3.3. Solid model of the electron density greater than about 0.5 e Å⁻³ in the second study of lysozyme at 6 Å resolution (p. 858) | html | pdf |
    - Fig. 25.1.3.4. Paper-tape output from the triple-counter linear diffractometer, showing the indices of the central reflection and the background, peak, background counts for the three reflections (p. 859) | html | pdf |
    - Fig. 25.1.3.5. Asymmetric mounting of a protein crystal with its mother liquor in a capillary tube (p. 860) | html | pdf |
    - Fig. 25.1.3.6. Plot of the ratio $[\textstyle\sum_{h}\displaystyle I(h)/ \textstyle\sum_{h}\displaystyle I(-h)]$ against h (p. 860) | html | pdf |
    - Fig. 25.1.3.7. (a) Phase probability curve for a Bijvoet pair of reflections (broken lines) with the joint probability curve (full line) derived by the method of Blow & Rossmann (1961) (p. 863) | html | pdf |
    - Fig. 25.1.3.8. Variation of the mean figure of $[\langle m\rangle]$ with $[\sin^{2}\theta / \lambda^{2}]$ (crosses represent acentric reflections, open circles represent centric reflections) (p. 863) | html | pdf |
    - Fig. 25.1.3.9. Photograph of sections z = 35/60 to 44/60 of the three-dimensional electron-density map of hen egg-white lysozyme at 2 Å resolution (p. 864) | html | pdf |
    - Fig. 25.1.4.1. The cell-wall tetrasaccharide with the $[\beta (1\!\rightarrow \!4)]$ glycosidic bond that is hydrolysed by lysozyme indicated (Blake et al., 1967) (p. 866) | html | pdf |
    - Fig. 25.1.4.2. Inhibitor molecules of lysozyme (Blake et al., 1967) (p. 867) | html | pdf |
    - Fig. 25.1.4.3. Contemporary drawings of the binding to lysozyme of: (a) β-N-acetylglucosamine and (b) α-N-acetylglucosamine (Blake et al., 1967) (p. 869) | html | pdf |
    - Fig. 25.1.4.4. Stereo-photographs of a model of the lysozyme molecule showing how a hexasaccharide substrate may bind to the enzyme (p. 869) | html | pdf |
    - Fig. 25.1.4.5. Draft sketch of the lysozyme–hexasaccharide substrate complex prepared by Irving Geis and annotated by David Phillips for an article published in Scientific American in 1966 (Phillips, 1966) (p. 870) | html | pdf |
  - Tables
    - Table 25.1.2.1. Heavy-atom parameters used in the final phase calculation for the lysozyme structure (p. 852) | html | pdf |
    - Table 25.1.3.1. Structure amplitudes of the $[11_{\prime}11_{\prime}L]$ reflections from crystal types I and II (p. 861) | html | pdf |
    - Table 25.1.3.2. Heavy-atom parameters for the 2 Å structure (p. 862) | html | pdf |
    - Table 25.1.3.3. Discrepancies in amino-acid sequences (excluding Asp/Asn) (p. 865) | html | pdf |