(International Tables) Crystallography of biological macromolecules

International Tables for Crystallography
Volume F: Crystallography of biological macromolecules

First online edition (2006) ISBN: 978-0-7923-6857-1 doi: 10.1107/97809553602060000106 | 1 | 2 |

Edited by M. G. Rossmann and E. Arnold

Preface (p. xxiii) | html | pdf |
E. Arnold and M. G. Rossmann

Introduction
- 1.1. Overview (pp. 1-3) | html | pdf | chapter contents |
  E. Arnold and M. G. Rossmann
- 1.2. Historical background (pp. 4-9) | html | pdf | chapter contents |
  M. G. Rossmann
  - 1.2.1. Introduction (p. 4) | html | pdf |
  - 1.2.2. 1912 to the 1950s (pp. 4-5) | html | pdf |
  - 1.2.3. The first investigations of biological macromolecules (p. 5) | html | pdf |
  - 1.2.4. Globular proteins in the 1950s (pp. 5-7) | html | pdf |
  - 1.2.5. The first protein structures (1957 to the 1970s) (pp. 7-8) | html | pdf |
  - 1.2.6. Technological developments (1958 to the 1980s) (pp. 8-9) | html | pdf |
  - 1.2.7. Meetings (p. 9) | 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. 6) | html | pdf |
    - Fig. 1.2.5.1. A model of the myoglobin molecule at 6 Å resolution (p. 7) | html | pdf |
    - Fig. 1.2.5.2. Cylindrical sections through a helical segment of a myoglobin polypeptide chain (p. 7) | 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. 8) | html | pdf |
- 1.3. Macromolecular crystallography and medicine (pp. 10-25) | html | pdf | chapter contents |
  W. G. J. Hol and C. L. M. J. Verlinde
  - 1.3.1. Introduction (p. 10) | html | pdf |
  - 1.3.2. Crystallography and medicine (pp. 10-11) | html | pdf |
  - 1.3.3. Crystallography and genetic diseases (pp. 11-12) | html | pdf |
  - 1.3.4. Crystallography and development of novel pharmaceuticals (pp. 12-24) | html | pdf |
    - 1.3.4.1. Infectious diseases (pp. 13-15) | html | pdf |
      - 1.3.4.1.1. Viral diseases (p. 13) | html | pdf |
      - 1.3.4.1.2. Bacterial diseases (p. 13) | html | pdf |
      - 1.3.4.1.3. Protozoan infections (pp. 13-15) | html | pdf |
      - 1.3.4.1.4. Fungi (p. 15) | html | pdf |
      - 1.3.4.1.5. Helminths (p. 15) | html | pdf |
    - 1.3.4.2. Resistance (pp. 15-21) | html | pdf |
    - 1.3.4.3. Non-communicable diseases (pp. 21-24) | html | pdf |
      - 1.3.4.3.1. Cancers (p. 21) | html | pdf |
      - 1.3.4.3.2. Diabetes (p. 21) | html | pdf |
      - 1.3.4.3.3. Blindness (p. 21) | html | pdf |
      - 1.3.4.3.4. Cardiovascular disorders (p. 21) | html | pdf |
      - 1.3.4.3.5. Neurological disorders (p. 24) | html | pdf |
    - 1.3.4.4. Drug metabolism and crystallography (p. 24) | html | pdf |
    - 1.3.4.5. Drug manufacturing and crystallography (p. 24) | html | pdf |
  - 1.3.5. Vaccines, immunology and crystallography (pp. 24-25) | html | pdf |
  - 1.3.6. Outlook and dreams (p. 25) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 1.3.4.1. The structure-based drug design cycle (p. 13) | html | pdf |
  - Tables
    - Table 1.3.3.1. Crystal structures and genetic diseases (p. 11) | html | pdf |
    - Table 1.3.4.1. Important human pathogenic viruses and their proteins (pp. 14-15) | html | pdf |
    - Table 1.3.4.2. Protein structures of important human pathogenic bacteria (pp. 16-18) | html | pdf |
    - Table 1.3.4.3. Protein structures of important human pathogenic protozoa, fungi and helminths (pp. 19-20) | html | pdf |
    - Table 1.3.4.4. Mechanisms of resistance (p. 20) | html | pdf |
    - Table 1.3.4.5. Important human protein structures in drug design (pp. 22-23) | html | pdf |
- 1.4. Perspectives for the future (pp. 26-43) | html | pdf | chapter contents |
  E. Arnold and M. G. Rossmann
  - 1.4.1. Gazing into the crystal ball (pp. 26-27) | html | pdf |
    E. Arnold
    - 1.4.1.1. What can we expect to see in the future of science and technology in general? (p. 26) | html | pdf |
    - 1.4.1.2. How will crystallography change in the future? (pp. 26-27) | html | pdf |
  - 1.4.2. Brief comments on Gazing into the crystal ball (p. 27) | html | pdf |
    M. G. Rossmann

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 (p. 53) | html | pdf |
    - 2.1.4.3. Scattering by atoms (pp. 53-54) | html | pdf |
      - 2.1.4.3.1. Scattering by one atom (pp. 53-54) | html | pdf |
      - 2.1.4.3.2. Scattering by a plane of atoms (p. 54) | html | pdf |
    - 2.1.4.4. Anomalous dispersion (pp. 54-55) | 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. 58-59) | html | pdf |
  - 2.1.7. Calculation of electron density (pp. 59-60) | html | pdf |
  - 2.1.8. Symmetry in the diffraction pattern (pp. 60-61) | html | pdf |
  - 2.1.9. The Patterson function (pp. 61-62) | 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. 54) | 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. 58) | html | pdf |
    - Fig. 2.1.7.1. An Argand diagram for the structure factors of the two members of a Friedel pair (p. 60) | 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. 46) | 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. 51) | 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 |

Techniques of molecular biology
- 3.1. Preparing recombinant proteins for X-ray crystallography (pp. 65-80) | html | pdf | chapter contents |
  S. H. Hughes and A. M. Stock
  - 3.1.1. Introduction (p. 65) | html | pdf |
  - 3.1.2. Overview (p. 65) | html | pdf |
  - 3.1.3. Engineering an expression construct (pp. 66-67) | html | pdf |
    - 3.1.3.1. Choosing an expression system (p. 66) | html | pdf |
    - 3.1.3.2. Creating an expression construct (p. 66) | html | pdf |
    - 3.1.3.3. Addition of tags or domains (p. 67) | html | pdf |
  - 3.1.4. Expression systems (pp. 67-74) | html | pdf |
    - 3.1.4.1. E. coli (pp. 67-71) | html | pdf |
    - 3.1.4.2. Yeast (pp. 71-72) | html | pdf |
    - 3.1.4.3. Baculoviruses and insect cells (pp. 72-73) | html | pdf |
    - 3.1.4.4. Mammalian cells (pp. 73-74) | html | pdf |
  - 3.1.5. Protein purification (pp. 75-77) | html | pdf |
    - 3.1.5.1. Conventional protein purification (pp. 75-76) | html | pdf |
    - 3.1.5.2. Affinity purification (pp. 76-77) | html | pdf |
    - 3.1.5.3. Purifying and refolding denatured proteins (p. 77) | html | pdf |
  - 3.1.6. Characterization of the purified product (pp. 77-78) | html | pdf |
    - 3.1.6.1. Assessment of sample homogeneity (pp. 77-78) | html | pdf |
    - 3.1.6.2. Protein storage (p. 78) | html | pdf |
  - 3.1.7. Reprise (pp. 78-79) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 3.1.3.1. Creating an expression construct (p. 67) | html | pdf |
    - Fig. 3.1.5.1. Protein purification strategy (p. 75) | html | pdf |
  - Tables
    - Table 3.1.4.1. Strategies for improving expression in E. coli (p. 68) | html | pdf |

Crystallization
- 4.1. General methods (pp. 81-93) | html | pdf | chapter contents |
  R. Giegé and A. McPherson
  - 4.1.1. Introduction (p. 81) | html | pdf |
  - 4.1.2. Crystallization arrangements and methodologies (pp. 81-86) | html | pdf |
    - 4.1.2.1. General considerations (p. 81) | html | pdf |
    - 4.1.2.2. Batch crystallizations (pp. 81-82) | html | pdf |
    - 4.1.2.3. Dialysis methods (p. 82) | html | pdf |
    - 4.1.2.4. Vapour diffusion methods (pp. 82-84) | html | pdf |
    - 4.1.2.5. Interface diffusion and the gel acupuncture method (p. 84) | html | pdf |
    - 4.1.2.6. Crystallization in gelled media (pp. 84-86) | html | pdf |
    - 4.1.2.7. Miscellaneous crystallization methods (p. 86) | html | pdf |
    - 4.1.2.8. Seeding (p. 86) | html | pdf |
  - 4.1.3. Parameters that affect crystallization of macromolecules (pp. 86-88) | html | pdf |
    - 4.1.3.1. Crystallizing agents (pp. 86-87) | html | pdf |
    - 4.1.3.2. Other chemical, physical and biochemical variables (pp. 87-88) | html | pdf |
    - 4.1.3.3. Additives (p. 88) | html | pdf |
  - 4.1.4. How to crystallize a new macromolecule (pp. 88-89) | html | pdf |
    - 4.1.4.1. Rules and general principles (p. 88) | html | pdf |
    - 4.1.4.2. Purity and homogeneity (p. 88) | html | pdf |
    - 4.1.4.3. Sample preparation (pp. 88-89) | html | pdf |
    - 4.1.4.4. Strategic concerns: a summary (p. 89) | html | pdf |
  - 4.1.5. Techniques for physical characterization of crystallization (pp. 89-91) | html | pdf |
    - 4.1.5.1. Techniques for studying prenucleation and nucleation (pp. 89-90) | html | pdf |
    - 4.1.5.2. Techniques for studying growth mechanisms (pp. 90-91) | html | pdf |
    - 4.1.5.3. Techniques for evaluating crystal perfection (p. 91) | html | pdf |
  - 4.1.6. Use of microgravity (pp. 91-93) | html | pdf |
    - 4.1.6.1. Why microgravity? (p. 91) | html | pdf |
    - 4.1.6.2. Instrumentation (p. 91) | html | pdf |
    - 4.1.6.3. Present results: a summary (pp. 91-92) | html | pdf |
    - 4.1.6.4. Interpretation of data (pp. 92-93) | html | pdf |
    - 4.1.6.5. The future of crystallization under microgravity (p. 93) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 4.1.2.1. Principles of the major methods currently used to crystallize biological macromolecules (p. 82) | html | pdf |
    - Fig. 4.1.2.2. Two versions of boxes for vapour diffusion crystallization (p. 83) | html | pdf |
    - Fig. 4.1.2.3. Principle of the gel acupuncture method for the crystallization of proteins by counter-diffusion (p. 84) | html | pdf |
    - Fig. 4.1.5.1. Visualization of the surface of yeast tRNA^Phe crystals by AFM (p. 90) | html | pdf |
  - Tables
    - Table 4.1.2.1. Factors affecting crystallization (p. 83) | html | pdf |
    - Table 4.1.2.2. Crystallizing agents for protein crystallization (pp. 85-86) | html | pdf |
- 4.2. Crystallization of membrane proteins (pp. 94-99) | html | pdf | chapter contents |
  H. Michel
  - 4.2.1. Introduction (p. 94) | html | pdf |
  - 4.2.2. Principles of membrane-protein crystallization (p. 94) | html | pdf |
  - 4.2.3. General properties of detergents relevant to membrane-protein crystallization (pp. 94-98) | html | pdf |
  - 4.2.4. The `small amphiphile concept' (p. 98) | html | pdf |
  - 4.2.5. Membrane-protein crystallization with the help of antibody Fv fragments (pp. 98-99) | html | pdf |
  - 4.2.6. Membrane-protein crystallization using cubic bicontinuous lipidic phases (p. 99) | html | pdf |
  - 4.2.7. General recommendations (p. 99) | 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. 95-96) | 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. 97) | 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. 98) | html | pdf |
- 4.3. Application of protein engineering to improve crystal properties (pp. 100-110) | html | pdf | chapter contents |
  D. R. Davies and A. Burgess Hickman
  - 4.3.1. Introduction (p. 100) | html | pdf |
  - 4.3.2. Improving solubility (pp. 100-101) | html | pdf |
  - 4.3.3. Use of fusion proteins (p. 101) | html | pdf |
  - 4.3.4. Mutations to accelerate crystallization (p. 101) | html | pdf |
  - 4.3.5. Mutations to improve diffraction quality (pp. 101-102) | html | pdf |
  - 4.3.6. Avoiding protein heterogeneity (p. 102) | html | pdf |
  - 4.3.7. Engineering crystal contacts to enhance crystallization in a particular crystal form (pp. 102-103) | html | pdf |
  - 4.3.8. Engineering heavy-atom sites (p. 103) | html | pdf |
  - References | html | pdf |

Crystal properties and handling
- 5.1. Crystal morphology, optical properties of crystals and crystal mounting (pp. 111-116) | html | pdf | chapter contents |
  H. L. Carrell and J. P. Glusker
  - 5.1.1. Crystal morphology and optical properties (pp. 111-114) | html | pdf |
    - 5.1.1.1. Crystal growth habits (pp. 111-112) | html | pdf |
      - 5.1.1.1.1. The shape of a crystal – growth habits (p. 111) | html | pdf |
      - 5.1.1.1.2. Quality of protein crystals (p. 111) | html | pdf |
      - 5.1.1.1.3. Polymorphism (pp. 111-112) | html | pdf |
      - 5.1.1.1.4. Twinning (p. 112) | html | pdf |
    - 5.1.1.2. Properties of crystal faces (pp. 112-113) | html | pdf |
      - 5.1.1.2.1. Indexing crystal faces (pp. 112-113) | html | pdf |
      - 5.1.1.2.2. Measurement of crystal habit (p. 113) | html | pdf |
    - 5.1.1.3. Optical properties (p. 113) | html | pdf |
      - 5.1.1.3.1. Crystals between crossed polarizers (p. 113) | html | pdf |
      - 5.1.1.3.2. Refractive indices and what they tell us about structure (p. 113) | html | pdf |
    - 5.1.1.4. Packing of molecules in crystals (p. 114) | html | pdf |
  - 5.1.2. Crystal mounting (pp. 114-116) | html | pdf |
    - 5.1.2.1. Introduction to crystal mounting (p. 114) | html | pdf |
    - 5.1.2.2. Tools for crystal mounting (pp. 114-115) | html | pdf |
      - 5.1.2.2.1. Microscope (p. 114) | html | pdf |
      - 5.1.2.2.2. Capillaries (pp. 114-115) | html | pdf |
      - 5.1.2.2.3. Thumb pump (p. 115) | html | pdf |
      - 5.1.2.2.4. Heater (p. 115) | html | pdf |
    - 5.1.2.3. Capillary mounting (pp. 115-116) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 5.1.1.1. Crystal faces (p. 112) | html | pdf |
    - Fig. 5.1.2.1. Tools commonly used for mounting crystals (p. 114) | html | pdf |
    - Fig. 5.1.2.2. Mounting a crystal in a capillary (p. 115) | html | pdf |
- 5.2. Crystal-density measurements (pp. 117-123) | html | pdf | chapter contents |
  E. M. Westbrook
  - 5.2.1. Introduction (p. 117) | html | pdf |
  - 5.2.2. Solvent in macromolecular crystals (p. 117) | html | pdf |
  - 5.2.3. Matthews number (p. 117) | html | pdf |
  - 5.2.4. Algebraic concepts (pp. 117-118) | html | pdf |
  - 5.2.5. Experimental estimation of hydration (p. 118) | html | pdf |
  - 5.2.6. Methods for measuring crystal density (pp. 118-121) | html | pdf |
    - 5.2.6.1. Pycnometry (pp. 118-119) | html | pdf |
    - 5.2.6.2. Volumenometry (p. 119) | html | pdf |
    - 5.2.6.3. The method of Archimedes (p. 119) | html | pdf |
    - 5.2.6.4. Immersion microbalance (p. 119) | html | pdf |
    - 5.2.6.5. Flotation (p. 119) | html | pdf |
    - 5.2.6.6. Tomographic crystal-volume measurement (pp. 119-120) | html | pdf |
    - 5.2.6.7. Gradient-tube method (pp. 120-121) | html | pdf |
  - 5.2.7. How to handle the solvent density (p. 121) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 5.2.6.1. Organic liquids for density determinations (p. 120) | html | pdf |
    - Table 5.2.6.2. Inorganic salts for density determinations (p. 120) | html | pdf |

Radiation sources and optics
- 6.1. X-ray sources (pp. 125-132) | html | pdf | chapter contents |
  U. W. Arndt
  - 6.1.1. Overview (p. 125) | html | pdf |
  - 6.1.2. Generation of X-rays (pp. 125-127) | html | pdf |
    - 6.1.2.1. Stationary-target X-ray tubes (p. 125) | html | pdf |
    - 6.1.2.2. Rotating-anode X-ray tubes (pp. 125-126) | html | pdf |
    - 6.1.2.3. Microfocus X-ray tubes (p. 126) | html | pdf |
    - 6.1.2.4. Synchrotron-radiation sources (pp. 126-127) | html | pdf |
  - 6.1.3. Properties of the X-ray beam (pp. 127-129) | html | pdf |
    - 6.1.3.1. Beam size (p. 128) | html | pdf |
    - 6.1.3.2. X-ray wavelength (p. 128) | html | pdf |
    - 6.1.3.3. Spectral composition (p. 128) | html | pdf |
    - 6.1.3.4. Intensity (pp. 128-129) | html | pdf |
    - 6.1.3.5. Cross fire (p. 129) | html | pdf |
    - 6.1.3.6. Beam stability (p. 129) | html | pdf |
  - 6.1.4. Beam conditioning (pp. 129-132) | html | pdf |
    - 6.1.4.1. X-ray mirrors (pp. 129-131) | html | pdf |
    - 6.1.4.2. Focusing collimators for microfocus sources (p. 131) | html | pdf |
    - 6.1.4.3. Other focusing collimators (p. 131) | html | pdf |
    - 6.1.4.4. Crystal monochromators (pp. 131-132) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 6.1.2.1. Section through a sealed X-ray tube (p. 125) | html | pdf |
    - Fig. 6.1.2.2. Synchrotron radiation emitted by a relativistic electron travelling in a curved trajectory (p. 126) | html | pdf |
    - Fig. 6.1.2.3. Comparison of the spectra from the storage ring SPEAR (p. 127) | html | pdf |
    - Fig. 6.1.2.4. Main components of a dedicated electron storage-ring synchrotron-radiation source (p. 127) | html | pdf |
    - Fig. 6.1.2.5. Electron trajectory within a multipole wiggler or undulator (p. 127) | 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. 128) | html | pdf |
    - Fig. 6.1.4.1. Production of a point focus by successive reflections at two orthogonal curved mirrors (p. 130) | 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. 130) | html | pdf |
    - Fig. 6.1.4.3. Mirror bender (after Franks, 1955) (p. 130) | html | pdf |
    - Fig. 6.1.4.4. Triangular mirror bender as described by Lemonnier et al (p. 130) | html | pdf |
    - Fig. 6.1.4.5. Mirror holder with machined slots for two orthogonal pairs of curved mirrors (after Arndt, Duncumb et al (p. 130) | html | pdf |
    - Fig. 6.1.4.6. Ellipsoidal mirror for use with a microfocus X-ray tube, where x₁ is ∼15 mm (p. 131) | html | pdf |
    - Fig. 6.1.4.7. A polycapillary collimator (after Bly & Gibson, 1996) (p. 131) | html | pdf |
  - Tables
    - Table 6.1.2.1. Standard X-ray tube inserts (p. 125) | html | pdf |
- 6.2. Neutron sources (pp. 133-142) | html | pdf | chapter contents |
  B. P. Schoenborn and R. Knott
  - 6.2.1. Reactors (pp. 133-137) | html | pdf |
    - 6.2.1.1. Basic reactor physics (p. 133) | html | pdf |
    - 6.2.1.2. Moderators for neutron scattering (pp. 133-134) | html | pdf |
      - 6.2.1.2.1. Thermal moderators (p. 134) | html | pdf |
      - 6.2.1.2.2. Cold moderators (p. 134) | html | pdf |
    - 6.2.1.3. Beamline components (pp. 134-136) | html | pdf |
      - 6.2.1.3.1. Collimators and filters (p. 135) | html | pdf |
      - 6.2.1.3.2. Crystal monochromators (p. 135) | html | pdf |
      - 6.2.1.3.3. Multilayer monochromators and supermirrors (pp. 135-136) | html | pdf |
      - 6.2.1.3.4. Velocity selectors (p. 136) | html | pdf |
      - 6.2.1.3.5. Neutron guides (p. 136) | html | pdf |
    - 6.2.1.4. Detectors (pp. 136-137) | html | pdf |
      - 6.2.1.4.1. Multiwire proportional counters (p. 136) | html | pdf |
      - 6.2.1.4.2. Image plates (pp. 136-137) | html | pdf |
    - 6.2.1.5. Instrument resolution functions (p. 137) | html | pdf |
  - 6.2.2. Spallation neutron sources (pp. 137-139) | html | pdf |
    - 6.2.2.1. Spallation neutron production (pp. 137-138) | html | pdf |
    - 6.2.2.2. Moderators (pp. 138-139) | html | pdf |
    - 6.2.2.3. Beamline optics (p. 139) | html | pdf |
    - 6.2.2.4. Time-of-flight techniques (p. 139) | html | pdf |
    - 6.2.2.5. Data-collection considerations (p. 139) | html | pdf |
  - 6.2.3. Summary (p. 139) | 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. 133) | 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. 134) | html | pdf |
    - Fig. 6.2.1.3. (a) Schematic vector diagram for an elastic neutron-scattering event (p. 134) | 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. 135) | html | pdf |
    - Fig. 6.2.2.1. Schematic presentation of the various nuclear processes encountered in spallation (p. 137) | html | pdf |
    - Fig. 6.2.2.2. Schematic diagram of a spallation target module depicting the inner Be and outer Pb reflector (p. 138) | 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. 138) | html | pdf |

X-ray detectors
- 7.1. Comparison of X-ray detectors (pp. 143-147) | html | pdf | chapter contents |
  S. M. Gruner, E. F. Eikenberry and M. W. Tate
  - 7.1.1. Commonly used detectors: general considerations (pp. 143-144) | html | pdf |
  - 7.1.2. Evaluating and comparing detectors (pp. 144-145) | html | pdf |
  - 7.1.3. Characteristics of different detector approaches (pp. 145-147) | html | pdf |
    - 7.1.3.1. Point versus linear versus area detection (p. 145) | html | pdf |
    - 7.1.3.2. Counting and integrating detectors (pp. 145-147) | html | pdf |
      - 7.1.3.2.1. Photon-counting detectors (pp. 145-146) | html | pdf |
      - 7.1.3.2.2. Integrating detectors (pp. 146-147) | html | pdf |
  - 7.1.4. Future detectors (p. 147) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 7.1.1.1. X-ray detectors for crystallography (p. 143) | html | pdf |
- 7.2. CCD detectors (pp. 148-153) | html | pdf | chapter contents |
  M. W. Tate, E. F. Eikenberry and S. M. Gruner
  - 7.2.1. Overview (p. 148) | html | pdf |
  - 7.2.2. CCD detector assembly (pp. 148-149) | html | pdf |
  - 7.2.3. Calibration and correction (pp. 149-151) | html | pdf |
    - 7.2.3.1. Dark-current subtraction (p. 149) | html | pdf |
    - 7.2.3.2. Removal of radioactive decay events (pp. 149-150) | html | pdf |
    - 7.2.3.3. Geometric distortion (p. 150) | html | pdf |
    - 7.2.3.4. Flat-field corrections (pp. 150-151) | html | pdf |
    - 7.2.3.5. Obliquity correction (p. 151) | html | pdf |
    - 7.2.3.6. Modular images (p. 151) | html | pdf |
  - 7.2.4. Detector system integration (pp. 151-152) | html | pdf |
  - 7.2.5. Applications to macromolecular crystallography (p. 152) | html | pdf |
  - 7.2.6. Future of CCD detectors (p. 152) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 7.2.1.1. Schematic of a single-module CCD detector (p. 148) | html | pdf |

Synchrotron crystallography
- 8.1. Synchrotron-radiation instrumentation, methods and scientific utilization (pp. 155-166) | html | pdf | chapter contents |
  J. R. Helliwell
  - 8.1.1. Introduction (p. 155) | html | pdf |
  - 8.1.2. The physics of SR (p. 155) | html | pdf |
  - 8.1.3. Insertion devices (IDs) (pp. 155-156) | html | pdf |
  - 8.1.4. Beam characteristics delivered at the crystal sample (pp. 156-158) | html | pdf |
  - 8.1.5. Evolution of SR machines and experiments (pp. 158-161) | html | pdf |
    - 8.1.5.1. First-generation SR machines (pp. 158-159) | html | pdf |
    - 8.1.5.2. Second-generation dedicated machines (p. 160) | html | pdf |
    - 8.1.5.3. Third-generation high-brilliance machines (pp. 160-161) | html | pdf |
    - 8.1.5.4. New national SR machines (p. 161) | html | pdf |
    - 8.1.5.5. X-ray free electron laser (XFEL) (p. 161) | html | pdf |
  - 8.1.6. SR instrumentation (pp. 161-162) | html | pdf |
  - 8.1.7. SR monochromatic and Laue diffraction geometry (pp. 162-164) | html | pdf |
    - 8.1.7.1. Laue geometry: sources, optics, sample reflection bandwidth and spot size (p. 162) | html | pdf |
    - 8.1.7.2. Monochromatic SR beams: optical configurations and sample rocking width (pp. 162-164) | html | pdf |
      - 8.1.7.2.1. Curved single-crystal monochromator (pp. 162-163) | html | pdf |
      - 8.1.7.2.2. Double-crystal monochromator (p. 163) | html | pdf |
      - 8.1.7.2.3. Crystal sample rocking width (pp. 163-164) | html | pdf |
  - 8.1.8. Scientific utilization of SR in protein crystallography (pp. 164-166) | html | pdf |
    - 8.1.8.1. Atomic and ultra high resolution macromolecular crystallography (p. 165) | html | pdf |
    - 8.1.8.2. Small crystals (p. 165) | html | pdf |
    - 8.1.8.3. Time-resolved macromolecular crystallography (p. 165) | html | pdf |
    - 8.1.8.4. Multi-macromolecular complexes (p. 165) | html | pdf |
    - 8.1.8.5. Optimized anomalous dispersion (MAD), improved MIR data and `structural genomics' (pp. 165-166) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 8.1.2.1. (a) Evolution of X-ray source brilliance (p. 156) | html | pdf |
    - Fig. 8.1.2.2. Overall layout of the Daresbury SRS facility (p. 157) | html | pdf |
    - Fig. 8.1.2.3. The ring tunnel and part of the machine lattice at the ESRF, Grenoble, France (p. 158) | html | pdf |
    - Fig. 8.1.2.4. SR spectra (p. 158) | html | pdf |
    - Fig. 8.1.4.1. Common beamline optics modes (p. 159) | html | pdf |
    - Fig. 8.1.4.2. Single-crystal SR diffraction patterns (p. 159) | html | pdf |
    - Fig. 8.1.5.1. Anomalous dispersion (p. 160) | html | pdf |
    - Fig. 8.1.7.1. Single-crystal monochromator illuminated by SR (p. 163) | html | pdf |
    - Fig. 8.1.7.2. Double-crystal monochromator illuminated by SR (p. 163) | 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. 164) | 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. 164) | html | pdf |
    - Fig. 8.1.8.2. A view of SV40 virus (p. 164) | html | pdf |
    - Fig. 8.1.8.3. The protein crystal structure of F₁ ATPase (p. 164) | html | pdf |
  - Tables
    - Table 8.1.4.1. Internet addresses of SR facilities with macromolecular crystallography beamlines (p. 157) | html | pdf |
    - Table 8.1.5.1. A comparison of the parameter list for the 2 GeV SRS, 1997, and the new higher-energy machine for the UK, DIAMOND (p. 160) | html | pdf |
- 8.2. Laue crystallography: time-resolved studies (pp. 167-176) | html | pdf | chapter contents |
  K. Moffat
  - 8.2.1. Introduction (p. 167) | html | pdf |
  - 8.2.2. Principles of Laue diffraction (pp. 167-168) | html | pdf |
  - 8.2.3. Practical considerations in the Laue technique (pp. 168-170) | html | pdf |
  - 8.2.4. The time-resolved experiment (pp. 170-171) | html | pdf |
  - 8.2.5. Conclusions (p. 171) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 8.2.2.1. Laue diffraction geometry (p. 167) | html | pdf |
    - Fig. 8.2.3.1. Flow chart of typical Laue data processing (p. 169) | html | pdf |
  - Tables
    - Table 8.2.2.1. Advantages and disadvantages of the Laue technique (p. 169) | html | pdf |
    - Table 8.2.5.1. Time-resolved Laue diffraction experiments (p. 171) | html | pdf |

Monochromatic data collection
- 9.1. Principles of monochromatic data collection (pp. 177-195) | html | pdf | chapter contents |
  Z. Dauter and K. S. Wilson
  - 9.1.1. Introduction (p. 177) | html | pdf |
  - 9.1.2. The components of a monochromatic X-ray experiment (p. 177) | html | pdf |
  - 9.1.3. Data completeness (p. 177) | html | pdf |
  - 9.1.4. X-ray sources (pp. 177-178) | html | pdf |
    - 9.1.4.1. Conventional sources (pp. 177-178) | html | pdf |
    - 9.1.4.2. Synchrotron storage rings (p. 178) | html | pdf |
  - 9.1.5. Goniostat geometry (pp. 178-179) | html | pdf |
    - 9.1.5.1. Overview (p. 178) | html | pdf |
    - 9.1.5.2. Film methods: the precession and Weissenberg methods (p. 178) | html | pdf |
    - 9.1.5.3. Single-counter diffractometers (pp. 178-179) | html | pdf |
    - 9.1.5.4. 2D detectors (p. 179) | html | pdf |
  - 9.1.6. Basis of the rotation method (pp. 179-183) | html | pdf |
    - 9.1.6.1. Rotation geometry (p. 179) | html | pdf |
    - 9.1.6.2. Diffraction pattern at a single orientation: the `still' image (pp. 179-180) | html | pdf |
    - 9.1.6.3. Rocking curve: crystal mosaicity and beam divergence (p. 180) | html | pdf |
    - 9.1.6.4. Rotation images and lunes (pp. 180-181) | html | pdf |
    - 9.1.6.5. Partially and fully recorded reflections (p. 181) | html | pdf |
    - 9.1.6.6. The width of the rotation range per image: fine φ slicing (pp. 181-182) | html | pdf |
    - 9.1.6.7. Wide slicing (pp. 182-183) | html | pdf |
    - 9.1.6.8. The Weissenberg camera (p. 183) | html | pdf |
  - 9.1.7. Rotation method: geometrical completeness (pp. 183-188) | html | pdf |
    - 9.1.7.1. Total rotation range for non-anomalous data (pp. 183-186) | html | pdf |
    - 9.1.7.2. Total rotation range for anomalous-dispersion data (p. 186) | html | pdf |
    - 9.1.7.3. Blind region (pp. 186-187) | html | pdf |
    - 9.1.7.4. Alternative indexing (pp. 187-188) | html | pdf |
  - 9.1.8. Crystal-to-detector distance (p. 188) | html | pdf |
  - 9.1.9. Wavelength (pp. 188-189) | html | pdf |
  - 9.1.10. Lysozyme as an example (pp. 189-190) | html | pdf |
  - 9.1.11. Rotation method: qualitative factors (pp. 190-191) | html | pdf |
    - 9.1.11.1. Inspection of reflection profiles (p. 190) | html | pdf |
    - 9.1.11.2. Exposure time (p. 190) | html | pdf |
    - 9.1.11.3. Overloads (pp. 190-191) | html | pdf |
    - 9.1.11.4. R factor, I/σ(I) ratio and estimated uncertainties (p. 191) | html | pdf |
  - 9.1.12. Radiation damage (pp. 191-192) | html | pdf |
    - 9.1.12.1. Historical perspective (pp. 191-192) | html | pdf |
    - 9.1.12.2. Cryogenic freezing (p. 192) | html | pdf |
    - 9.1.12.3. Ultra high intensity SR sources (p. 192) | html | pdf |
  - 9.1.13. Relating data collection to the problem in hand (pp. 192-194) | html | pdf |
    - 9.1.13.1. Isomorphous-anomalous derivatives (pp. 192-193) | html | pdf |
    - 9.1.13.2. Anomalous scattering, MAD and SAD (p. 193) | html | pdf |
    - 9.1.13.3. Molecular replacement (p. 193) | html | pdf |
    - 9.1.13.4. Definitive data on relevant biological structures (p. 193) | html | pdf |
    - 9.1.13.5. A series of mutant or complex structures (pp. 193-194) | html | pdf |
    - 9.1.13.6. Atomic resolution applications (p. 194) | html | pdf |
  - 9.1.14. The importance of low-resolution data (p. 194) | html | pdf |
  - 9.1.15. Data quality over the whole resolution range (p. 194) | html | pdf |
  - 9.1.16. Final remarks (pp. 194-195) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 9.1.6.1. The Ewald-sphere construction (p. 179) | 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. 180) | html | pdf |
    - Fig. 9.1.6.3. Schematic representation of beam divergence (δ) and crystal mosaicity (η) (p. 180) | html | pdf |
    - Fig. 9.1.6.4. A single lune on two consecutive exposures (p. 181) | html | pdf |
    - Fig. 9.1.6.5. Appearance of a lune for (a) a crystal of low mosaicity and (b) a highly mosaic crystal (p. 181) | 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. 182) | 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. 183) | 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 (p. 183) | 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. 184) | html | pdf |
    - Fig. 9.1.7.2. Rotation of a triclinic crystal by 135° is not sufficient to obtain totally complete data (p. 184) | html | pdf |
    - Fig. 9.1.7.3. After a 90° rotation out of a required 180°, the overall completeness is higher than 50% (p. 185) | 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. 185) | 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. 185) | 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. 186) | 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. 186) | 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. 187) | html | pdf |
    - Fig. 9.1.7.9. For shorter wavelengths the blind region is narrower, since the Ewald sphere is flatter (p. 187) | 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. 187) | html | pdf |
    - Fig. 9.1.10.1. Images recorded from a crystal of lysozyme (p. 189) | html | pdf |
  - Tables
    - Table 9.1.1.1. Size of the unit cell and number of reflections (p. 177) | 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. 184) | html | pdf |
    - Table 9.1.7.2. Rotation range (°) required in different crystal classes (p. 186) | html | pdf |
    - Table 9.1.7.3. Space groups with alternative, non-equivalent indexing schemes (p. 188) | html | pdf |

Cryocrystallography
- 10.1. Introduction to cryocrystallography (pp. 197-201) | html | pdf | chapter contents |
  H. Hope
  - 10.1.1. Utility of low-temperature data collection (p. 197) | html | pdf |
    - 10.1.1.1. Prevention of radiation damage (p. 197) | html | pdf |
    - 10.1.1.2. Mechanical stability of the crystal mount (p. 197) | html | pdf |
    - 10.1.1.3. Effect on resolution (p. 197) | html | pdf |
  - 10.1.2. Cooling of biocrystals (pp. 197-199) | html | pdf |
    - 10.1.2.1. Physical chemistry of biocrystals (pp. 197-198) | html | pdf |
    - 10.1.2.2. Internal ice or phase transition (p. 198) | html | pdf |
    - 10.1.2.3. Removal of the solvent layer (p. 198) | html | pdf |
    - 10.1.2.4. Cooling rates (pp. 198-199) | html | pdf |
  - 10.1.3. Principles of cooling equipment (p. 199) | html | pdf |
    - 10.1.3.1. Cold gas supply (p. 199) | html | pdf |
    - 10.1.3.2. Frost prevention (p. 199) | html | pdf |
  - 10.1.4. Operational considerations (pp. 199-201) | html | pdf |
    - 10.1.4.1. Dual-stream instruments (pp. 199-200) | html | pdf |
    - 10.1.4.2. Electrically heated nozzle (pp. 200-201) | html | pdf |
    - 10.1.4.3. Temperature calibration (p. 201) | html | pdf |
    - 10.1.4.4. Transfer of the crystal to the diffractometer (p. 201) | html | pdf |
  - 10.1.5. Concluding note (p. 201) | 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. 199) | 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. 200) | html | pdf |
    - Fig. 10.1.4.3. Schematic drawing of a single-stream setup with the stream parallel to the diffractometer φ axis (p. 200) | 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. 200) | html | pdf |
- 10.2. Cryocrystallography techniques and devices (pp. 202-208) | html | pdf | chapter contents |
  D. W. Rodgers
  - 10.2.1. Introduction (p. 202) | html | pdf |
  - 10.2.2. Crystal preparation (pp. 202-203) | html | pdf |
  - 10.2.3. Crystal mounting (pp. 203-204) | html | pdf |
  - 10.2.4. Flash cooling (pp. 205-206) | html | pdf |
  - 10.2.5. Transfer and storage (pp. 206-207) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 10.2.2.1. Recommended pathway for optimizing cryoprotectant conditions and flash cooling (p. 203) | html | pdf |
    - Fig. 10.2.3.1. Different crystal mounts for flash cooling and cryogenic data collection (p. 204) | html | pdf |
    - Fig. 10.2.3.2. Mounting a crystal in a loop (p. 204) | html | pdf |
    - Fig. 10.2.3.3. Photograph of a flash-cooled crystal mounted in a nylon loop (p. 204) | html | pdf |
    - Fig. 10.2.3.4. Arrangement for using the loop-mounting technique at non-cryogenic temperatures (p. 204) | html | pdf |
    - Fig. 10.2.4.1. Flash cooling a crystal in the cold gas stream from a cryostat (p. 205) | html | pdf |
    - Fig. 10.2.4.2. Flash cooling in a liquid cryogen (p. 205) | html | pdf |
    - Fig. 10.2.5.1. Transfer of the flash-cooled crystal and loop assembly to a goniometer using a cryovial (p. 206) | html | pdf |
    - Fig. 10.2.5.2. Transfer using an alternative device for achieving the correct magnetic mount orientation (p. 207) | html | pdf |
    - Fig. 10.2.5.3. Transfer using tongs (p. 207) | html | pdf |
  - Tables
    - Table 10.2.2.1. List of cryoprotectants used successfully for flash cooling macromolecular crystals (p. 202) | html | pdf |
    - Table 10.2.2.2. Methods for introducing the cryoprotectants needed for flash cooling (p. 202) | html | pdf |

Data processing
- 11.1. Automatic indexing of oscillation images (pp. 209-211) | html | pdf | chapter contents |
  M. G. Rossmann
  - 11.1.1. Introduction (p. 209) | html | pdf |
  - 11.1.2. The crystal orientation matrix (p. 209) | html | pdf |
  - 11.1.3. Fourier analysis of the reciprocal-lattice vector distribution when projected onto a chosen direction (pp. 209-210) | html | pdf |
  - 11.1.4. Exploring all possible directions to find a good set of basis vectors (p. 210) | html | pdf |
  - 11.1.5. The program (p. 211) | 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 (Tao et al (p. 210) | html | pdf |
    - Fig. 11.1.3.2. Fourier analysis of the distribution shown in Fig. 11.1.3.1 (p. 210) | html | pdf |
- 11.2. Integration of macromolecular diffraction data (pp. 212-217) | html | pdf | chapter contents |
  A. G. W. Leslie
  - 11.2.1. Introduction (p. 212) | html | pdf |
  - 11.2.2. Prerequisites for accurate integration (p. 212) | html | pdf |
    - 11.2.2.1. Crystal parameters (p. 212) | html | pdf |
    - 11.2.2.2. Detector parameters (p. 212) | html | pdf |
  - 11.2.3. Methods of integration (p. 212) | html | pdf |
  - 11.2.4. The measurement box (pp. 212-213) | html | pdf |
  - 11.2.5. Integration by simple summation (pp. 213-214) | html | pdf |
    - 11.2.5.1. Determination of the best background plane (p. 213) | html | pdf |
      - 11.2.5.1.1. Outlier rejection (p. 213) | html | pdf |
    - 11.2.5.2. Evaluating the integrated intensity and standard deviation (pp. 213-214) | html | pdf |
    - 11.2.5.3. The effect of instrument or detector errors (p. 214) | html | pdf |
  - 11.2.6. Integration by profile fitting (pp. 214-217) | html | pdf |
    - 11.2.6.1. Forming the standard profiles (pp. 214-215) | html | pdf |
    - 11.2.6.2. Evaluation of the profile-fitted intensity (p. 215) | html | pdf |
    - 11.2.6.3. Modifications for very close spots (pp. 215-216) | html | pdf |
    - 11.2.6.4. Profile fitting very strong reflections (p. 216) | html | pdf |
    - 11.2.6.5. Profile fitting very weak reflections (p. 216) | html | pdf |
    - 11.2.6.6. Improvement provided by profile fitting weak reflections (p. 216) | html | pdf |
    - 11.2.6.7. Other benefits of profile fitting (pp. 216-217) | html | pdf |
      - 11.2.6.7.1. Incompletely resolved spots (p. 216) | html | pdf |
      - 11.2.6.7.2. Elimination of peak pixel outliers (p. 216) | html | pdf |
      - 11.2.6.7.3. Estimation of overloaded reflections (pp. 216-217) | html | pdf |
    - 11.2.6.8. Profile fitting partially recorded reflections (p. 217) | html | pdf |
    - 11.2.6.9. Systematic errors in profile-fitted intensities (p. 217) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.2.4.1. The measurement-box definition used in MOSFLM (p. 213) | html | pdf |
- 11.3. Integration, scaling, space-group assignment and post refinement (pp. 218-225) | html | pdf | chapter contents |
  W. Kabsch
  - 11.3.1. Introduction (p. 218) | html | pdf |
  - 11.3.2. Modelling rotation images (pp. 218-221) | html | pdf |
    - 11.3.2.1. Coordinate systems and parameters (p. 218) | html | pdf |
    - 11.3.2.2. Spot prediction (pp. 218-219) | html | pdf |
    - 11.3.2.3. Standard spot shape (p. 219) | html | pdf |
    - 11.3.2.4. Spot centroids and partiality (p. 219) | html | pdf |
    - 11.3.2.5. Localizing diffraction spots (pp. 219-220) | html | pdf |
    - 11.3.2.6. Basis extraction (p. 220) | html | pdf |
    - 11.3.2.7. Indexing (p. 220) | html | pdf |
    - 11.3.2.8. Refinement (pp. 220-221) | html | pdf |
  - 11.3.3. Integration (pp. 221-222) | html | pdf |
    - 11.3.3.1. Spot extraction (p. 221) | html | pdf |
    - 11.3.3.2. Background (pp. 221-222) | html | pdf |
    - 11.3.3.3. Standard profiles (p. 222) | html | pdf |
    - 11.3.3.4. Intensity estimation (p. 222) | html | pdf |
  - 11.3.4. Scaling (pp. 222-223) | html | pdf |
  - 11.3.5. Post refinement (pp. 223-224) | html | pdf |
  - 11.3.6. Space-group assignment (pp. 224-225) | html | pdf |
    - 11.3.6.1. Determination of the Bravais lattice (p. 224) | html | pdf |
    - 11.3.6.2. Finding possible space groups (pp. 224-225) | html | pdf |
  - References | html | pdf |
  - Tables
    - Table 11.3.6.1. Rating of lattice types implied by a given reduced cell (p. 225) | html | pdf |
- 11.4. DENZO and SCALEPACK (pp. 226-235) | html | pdf | chapter contents |
  Z. Otwinowski and W. Minor
  - 11.4.1. Introduction (p. 226) | html | pdf |
  - 11.4.2. Diffraction from a perfect crystal lattice (pp. 226-227) | html | pdf |
  - 11.4.3. Autoindexing (pp. 227-228) | html | pdf |
    - 11.4.3.1. Lattice symmetry (p. 227) | html | pdf |
    - 11.4.3.2. Lattice pseudosymmetry (p. 227) | html | pdf |
    - 11.4.3.3. Data-collection requirements (pp. 227-228) | html | pdf |
    - 11.4.3.4. Misindexing (p. 228) | html | pdf |
    - 11.4.3.5. Twins (p. 228) | html | pdf |
  - 11.4.4. Coordinate systems (pp. 228-229) | html | pdf |
    - 11.4.4.1. Beam–gravity (p. 228) | html | pdf |
    - 11.4.4.2. Data (p. 228) | html | pdf |
    - 11.4.4.3. Beam–spindle (p. 228) | html | pdf |
    - 11.4.4.4. Beam–2θ (pp. 228-229) | html | pdf |
  - 11.4.5. Experimental assumptions (pp. 229-231) | html | pdf |
    - 11.4.5.1. Crystal diffraction (p. 229) | html | pdf |
    - 11.4.5.2. Data model (p. 229) | html | pdf |
    - 11.4.5.3. Data-model refinement (pp. 229-230) | html | pdf |
    - 11.4.5.4. Correlation between parameters (p. 230) | html | pdf |
    - 11.4.5.5. Single- and multiframe refinement (p. 230) | html | pdf |
    - 11.4.5.6. Active area (p. 230) | html | pdf |
    - 11.4.5.7. Flood field (p. 230) | html | pdf |
    - 11.4.5.8. Absolute configuration (p. 230) | html | pdf |
    - 11.4.5.9. Correcting diffraction images (p. 230) | html | pdf |
    - 11.4.5.10. Detector goniostat (pp. 230-231) | html | pdf |
    - 11.4.5.11. Crystal goniostat (p. 231) | html | pdf |
    - 11.4.5.12. Crystal orthogonalization convention (p. 231) | html | pdf |
    - 11.4.5.13. Refinement and calibration (p. 231) | html | pdf |
  - 11.4.6. Prediction of the diffraction pattern (pp. 231-232) | html | pdf |
    - 11.4.6.1. Refinement of crystal and detector parameters (p. 232) | html | pdf |
    - 11.4.6.2. Bragg's law for non-ideal conditions: mosaicity (p. 232) | html | pdf |
    - 11.4.6.3. Detector distortions (p. 232) | html | pdf |
  - 11.4.7. Detector diagnostics (p. 233) | html | pdf |
  - 11.4.8. Multiplicative corrections (scaling) (p. 233) | html | pdf |
    - 11.4.8.1. Polarization (p. 233) | html | pdf |
  - 11.4.9. Global refinement or post refinement (p. 233) | html | pdf |
  - 11.4.10. Graphical command centre (pp. 233-235) | html | pdf |
  - 11.4.11. Final note (p. 235) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 11.4.5.1. The transformations in DENZO applied to APS-1 detector data (p. 231) | html | pdf |
    - Fig. 11.4.10.1. The strategy program as implemented in the HKL package (p. 234) | html | pdf |
    - Fig. 11.4.10.2. The scaling window of the graphical user interface (p. 234) | html | pdf |
- 11.5. The use of partially recorded reflections for post refinement, scaling and averaging X-ray diffraction data (pp. 236-245) | html | pdf | chapter contents |
  C. G. van Beek, R. Bolotovsky and M. G. Rossmann
  - 11.5.1. Introduction (p. 236) | html | pdf |
  - 11.5.2. Generalization of the Hamilton, Rollett and Sparks equations to take into account partial reflections (pp. 236-237) | html | pdf |
  - 11.5.3. Selection of reflections useful for scaling (p. 237) | html | pdf |
  - 11.5.4. Restraints and constraints (p. 237) | html | pdf |
  - 11.5.5. Generalization of the procedure for averaging reflection intensities (p. 238) | html | pdf |
  - 11.5.6. Estimating the quality of data scaling and averaging (p. 238) | html | pdf |
  - 11.5.7. Experimental results (pp. 238-241) | html | pdf |
    - 11.5.7.1. Variation of scale factors versus frame number (pp. 238-239) | html | pdf |
    - 11.5.7.2. R factor as a function of `sum-of-partialities' (method 1) (p. 239) | html | pdf |
    - 11.5.7.3. Statistics for rejecting reflections and data quality as a function of frame number (p. 240) | html | pdf |
    - 11.5.7.4. Observed versus calculated partiality (p. 240) | html | pdf |
    - 11.5.7.5. Anisotropic mosaicity (p. 240) | html | pdf |
    - 11.5.7.6. Anomalous dispersion (p. 241) | html | pdf |
  - 11.5.8. Conclusions (p. 241) | html | pdf |
  - Appendix 11.5.1. Partiality model (Rossmann, 1979; Rossmann et al., 1979) (pp. 241-242) | 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 (Dokland et al (p. 239) | html | pdf |
    - Fig. 11.5.7.2. Linear scale factor as a function of frame number for an HRV14 data set (Rossmann et al (p. 239) | 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 (Choi et al (p. 239) | 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 (Dokland et al (p. 240) | html | pdf |
    - Fig. 11.5.7.5. R factor per frame as a function of frame number for a φX174 data set (Dokland et al (p. 240) | html | pdf |
    - Fig. 11.5.7.6. The observed partialities plotted against calculated partialities for a φX174 data set (Dokland et al (p. 240) | html | pdf |
    - Fig. 11.5.7.7. Variation of (unconstrained) mosaicity for a monoclinic crystal of the bacterial virus alpha3 (Bernal et al (p. 240) | html | pdf |
    - Fig. 11.5.7.8. Quality of anomalous-dispersion data for an SeMet derivative of dioxygenase Rieske ferredoxin (Colbert & Bolin, 1999) (p. 240) | html | pdf |
    - Fig. A11.5.1.1. Penetration of a reciprocal-lattice point P into the sphere of reflection by rotation around Oy (p. 241) | html | pdf |
    - Fig. A11.5.1.2. Relationship between the fraction of the path travelled, q, by a reciprocal-lattice point across an Ewald sphere of finite thickness and the fraction of the total scattered intensity, p (p. 242) | html | pdf |
    - Fig. A11.5.1.3. The four conditions 1, 2, 3 and 4 for partial reflections corresponding to Table A11.5.1.1 (p. 242) | html | pdf |
  - Tables
    - Table 11.5.3.1. Hierarchy of criteria for selecting reflections for scaling and averaging procedures (p. 237) | html | pdf |
    - Table A11.5.1.1. Calculation of the degree of penetration of the Ewald sphere, q (p. 242) | 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. 247-255) | html | pdf | chapter contents |
  D. Carvin, S. A. Islam, M. J. E. Sternberg and T. L. Blundell
  - 12.1.1. Introduction (p. 247) | html | pdf |
  - 12.1.2. Heavy-atom data bank (pp. 247-248) | html | pdf |
  - 12.1.3. Properties of heavy-atom compounds and their complexes (pp. 248-250) | html | pdf |
    - 12.1.3.1. Stability (p. 248) | html | pdf |
    - 12.1.3.2. Lability (p. 248) | html | pdf |
    - 12.1.3.3. Oxidation state of metal ions in protein crystals (p. 248) | html | pdf |
    - 12.1.3.4. Effect of pH (pp. 248-249) | html | pdf |
    - 12.1.3.5. Effect of precipitants and buffers on heavy-atom binding (p. 249) | html | pdf |
    - 12.1.3.6. Solubility of heavy-atom compounds (p. 249) | html | pdf |
    - 12.1.3.7. Effect of concentration, time of soak and temperature on heavy-atom binding (p. 250) | html | pdf |
  - 12.1.4. Amino acids as ligands (p. 250) | html | pdf |
  - 12.1.5. Protein chemistry of heavy-atom reagents (pp. 250-254) | html | pdf |
    - 12.1.5.1. Hard cations (p. 251) | html | pdf |
    - 12.1.5.2. Thallium and lead ions (p. 251) | html | pdf |
    - 12.1.5.3. B-metal reagents (pp. 251-253) | html | pdf |
    - 12.1.5.4. Electrostatic binding of heavy-atom anions (p. 253) | html | pdf |
    - 12.1.5.5. Hydrophobic heavy-atom reagents (pp. 253-254) | html | pdf |
    - 12.1.5.6. Iodine (p. 254) | html | pdf |
    - 12.1.5.7. Polynuclear reagents (p. 254) | html | pdf |
  - 12.1.6. Metal-ion replacement in metalloproteins (pp. 254-255) | html | pdf |
  - 12.1.7. Analogues of amino acids (p. 255) | html | pdf |
  - 12.1.8. Use of the heavy-atom data bank to select derivatives (p. 255) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 12.1.5.1. The binding site for uranyl ions in cytochrome b5 (oxidized: 3B5C) (p. 252) | html | pdf |
    - Fig. 12.1.5.2. Mercuric ions replace zinc in thermolysin (3TLN) (p. 252) | html | pdf |
    - Fig. 12.1.5.3. The binding of a silver ion to immunoglobulin Fab (2FB4) (p. 252) | html | pdf |
    - Fig. 12.1.5.4. The binding of $[\hbox{PtCl}_{4}^{2-}]$ through a methionine in azurin (1AZU) (p. 252) | 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. 252) | 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. 253) | html | pdf |
    - Fig. 12.1.5.7. The binding of $[\hbox{Pt(CN)}_{4}^{2-}]$ to aldose dehydrogenase (8ADH) (p. 253) | html | pdf |
    - Fig. 12.1.6.1. The displacement of calcium by samarium in thermolysin (p. 254) | html | pdf |
  - Tables
    - Table 12.1.3.1. Useful pH ranges of some heavy-atom reagents derived from the heavy-atom data bank (p. 249) | html | pdf |
    - Table 12.1.5.1. The 23 most commonly used heavy-atom reagents (p. 251) | html | pdf |
    - Table 12.1.5.2. The five most popular uranium derivatives (p. 251) | html | pdf |
    - Table 12.1.5.3. The five most popular mercury derivatives (p. 251) | html | pdf |
    - Table 12.1.5.4. The five most popular platinum derivatives (p. 253) | html | pdf |
- 12.2. Locating heavy-atom sites (pp. 256-262) | html | pdf | chapter contents |
  M. T. Stubbs and R. Huber
  - 12.2.1. The origin of the phase problem (pp. 256-257) | html | pdf |
  - 12.2.2. The Patterson function (pp. 257-258) | html | pdf |
  - 12.2.3. The difference Fourier (p. 258) | html | pdf |
  - 12.2.4. Reality (pp. 258-259) | html | pdf |
    - 12.2.4.1. Treatment of errors (pp. 258-259) | html | pdf |
    - 12.2.4.2. Automated search procedures (p. 259) | html | pdf |
  - 12.2.5. Special complications (pp. 259-260) | html | pdf |
    - 12.2.5.1. Lack of isomorphism (pp. 259-260) | html | pdf |
    - 12.2.5.2. Space-group problems (p. 260) | html | pdf |
    - 12.2.5.3. High levels of substitution; noncrystallographic symmetry (p. 260) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 12.2.1.1. Relationships in diffraction space (p. 256) | html | pdf |
    - Fig. 12.2.1.2. The effect of introducing a heavy atom or anomalous scatterer (p. 257) | html | pdf |
    - Fig. 12.2.2.1. The Patterson map with symmetry (p. 257) | html | pdf |
    - Fig. 12.2.2.2. The vector superposition method (p. 258) | html | pdf |
    - Fig. 12.2.4.1. The treatment of phase errors (p. 258) | html | pdf |

Molecular replacement
- 13.1. Noncrystallographic symmetry (pp. 263-268) | html | pdf | chapter contents |
  D. M. Blow
  - 13.1.1. Introduction (p. 263) | html | pdf |
  - 13.1.2. Definition of noncrystallographic symmetry (p. 263) | html | pdf |
    - 13.1.2.1. Standard noncrystallographic symmetry (p. 263) | html | pdf |
    - 13.1.2.2. Generalized noncrystallographic symmetry (p. 263) | html | pdf |
    - 13.1.2.3. Exploitation of noncrystallographic symmetry (p. 263) | html | pdf |
  - 13.1.3. Use of the Patterson function to interpret noncrystallographic symmetry (pp. 263-265) | html | pdf |
    - 13.1.3.1. Rotation operations (pp. 263-264) | html | pdf |
    - 13.1.3.2. Translation operations (pp. 264-265) | html | pdf |
  - 13.1.4. Interpretation of generalized noncrystallographic symmetry where the molecular structure is partially known (pp. 265-266) | html | pdf |
    - 13.1.4.1. The cross-rotation function (p. 265) | html | pdf |
    - 13.1.4.2. The cross-translation function (p. 265) | html | pdf |
    - 13.1.4.3. Structure determination (pp. 265-266) | html | pdf |
  - 13.1.5. The power of noncrystallographic symmetry in structure analysis (pp. 266-268) | html | pdf |
    - 13.1.5.1. Relevant parameters: standard case (p. 266) | html | pdf |
    - 13.1.5.2. Information gain from ideal noncrystallographic symmetry (pp. 266-267) | html | pdf |
    - 13.1.5.3. Information gain in the non-ideal case (p. 267) | html | pdf |
    - 13.1.5.4. Relevant parameters: generalized case (p. 267) | html | pdf |
    - 13.1.5.5. Noncrystallographic symmetry in atomic coordinate refinement (pp. 267-268) | 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. 264) | html | pdf |
  - Tables
    - Table 13.1.2.1. Noncrystallographic symmetry in crystals (p. 263) | html | pdf |
    - Table 13.1.4.1. Structure determination using noncrystallographic symmetry (p. 265) | html | pdf |
- 13.2. Rotation functions (pp. 269-274) | html | pdf | chapter contents |
  J. Navaza
  - 13.2.1. Overview (p. 269) | html | pdf |
  - 13.2.2. Rotations in three-dimensional Euclidean space (pp. 269-270) | html | pdf |
    - 13.2.2.1. The metric of the rotation group (pp. 269-270) | html | pdf |
  - 13.2.3. The rotation function (pp. 270-272) | html | pdf |
    - 13.2.3.1. Computing the rotation function (p. 271) | html | pdf |
    - 13.2.3.2. Plotting and sampling the rotation function (p. 271) | html | pdf |
    - 13.2.3.3. Strategies (p. 272) | html | pdf |
    - 13.2.3.4. Symmetry properties of the rotation function (p. 272) | html | pdf |
  - 13.2.4. The locked rotation function (pp. 272-273) | html | pdf |
  - 13.2.5. Other rotation functions (p. 273) | html | pdf |
  - 13.2.6. Concluding remarks (p. 273) | html | pdf |
  - Appendix 13.2.1. Formulae for the derivation and computation of the fast rotation function (pp. 273-274) | html | pdf |
    - A13.2.1.1. Euler parameterization (p. 273) | html | pdf |
    - A13.2.1.2. The $[D^{\ell}_{m, \, m'}]$ matrices (pp. 273-274) | html | pdf |
    - A13.2.1.3. Spherical harmonics (p. 274) | html | pdf |
    - A13.2.1.4. Spherical Bessel functions (p. 274) | html | pdf |
    - A13.2.1.5. Expansion of $[\exp (2\pi i{\bf sr})]$ (p. 274) | html | pdf |
    - A13.2.1.6. Expansion of the interference function (p. 274) | 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. 269) | html | pdf |
- 13.3. Translation functions (pp. 275-278) | html | pdf | chapter contents |
  L. Tong
  - 13.3.1. Introduction (p. 275) | html | pdf |
  - 13.3.2. R-factor and correlation-coefficient translation functions (pp. 275-276) | html | pdf |
  - 13.3.3. Patterson-correlation translation function (p. 276) | html | pdf |
  - 13.3.4. Phased translation function (pp. 276-277) | html | pdf |
  - 13.3.5. Packing check in translation functions (p. 277) | html | pdf |
  - 13.3.6. The unique region of a translation function (the Cheshire group) (p. 277) | html | pdf |
  - 13.3.7. Combined molecular replacement (p. 277) | html | pdf |
  - 13.3.8. The locked translation function (pp. 277-278) | html | pdf |
  - 13.3.9. Miscellaneous translation functions (p. 278) | html | pdf |
  - References | html | pdf |
- 13.4. Noncrystallographic symmetry averaging of electron density for molecular-replacement phase refinement and extension (pp. 279-292) | html | pdf | chapter contents |
  M. G. Rossmann and E. Arnold
  - 13.4.1. Introduction (p. 279) | html | pdf |
  - 13.4.2. Noncrystallographic symmetry (NCS) (pp. 279-280) | html | pdf |
  - 13.4.3. Phase determination using NCS (pp. 280-281) | html | pdf |
  - 13.4.4. The p- and h-cells (pp. 281-282) | html | pdf |
  - 13.4.5. Combining crystallographic and noncrystallographic symmetry (pp. 282-283) | html | pdf |
    - 13.4.5.1. General considerations (p. 282) | html | pdf |
    - 13.4.5.2. Averaging with the p-cell (pp. 282-283) | html | pdf |
    - 13.4.5.3. Averaging the p-cell and placing the results into the h-cell (p. 283) | html | pdf |
  - 13.4.6. Determining the molecular envelope (pp. 283-284) | html | pdf |
  - 13.4.7. Finding the averaged density (pp. 284-285) | html | pdf |
  - 13.4.8. Interpolation (p. 285) | html | pdf |
  - 13.4.9. Combining different crystal forms (p. 285) | html | pdf |
  - 13.4.10. Phase extension and refinement of the NCS parameters (pp. 285-286) | html | pdf |
  - 13.4.11. Convergence (p. 286) | html | pdf |
  - 13.4.12. Ab initio phasing starts (pp. 286-287) | html | pdf |
  - 13.4.13. Recent salient examples in low-symmetry cases: multidomain averaging and systematic applications of multiple-crystal-form averaging (pp. 287-288) | html | pdf |
  - 13.4.14. Programs (p. 288) | 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. 279) | html | pdf |
    - Fig. 13.4.2.2. (a) NCS in a triclinic cell (p. 280) | html | pdf |
    - Fig. 13.4.2.3. The position of the twofold rotation axis which relates the two piglets is completely arbitrary (p. 280) | html | pdf |
    - Fig. 13.4.4.1. Stereographic projections showing alternative definitions of the `standard orientation' of an icosahedron in the h-cell (p. 281) | 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. 284) | 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. 285) | 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. 286) | 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. 287) | html | pdf |
  - Tables
    - Table 13.4.7.1. Mean root-mean-square scatter between noncrystallographically related points (p. 284) | html | pdf |

Anomalous dispersion
- 14.1. Heavy-atom location and phase determination with single-wavelength diffraction data (pp. 293-298) | html | pdf | chapter contents |
  B. W. Matthews
  - 14.1.1. Introduction (p. 293) | html | pdf |
  - 14.1.2. The isomorphous-replacement method (pp. 293-294) | html | pdf |
  - 14.1.3. The method of multiple isomorphous replacement (p. 294) | html | pdf |
  - 14.1.4. The method of Blow & Crick (pp. 294-295) | html | pdf |
  - 14.1.5. The best Fourier (p. 295) | html | pdf |
  - 14.1.6. Anomalous scattering (p. 295) | html | pdf |
  - 14.1.7. Theory of anomalous scattering (pp. 295-296) | html | pdf |
  - 14.1.8. The phase probability distribution for anomalous scattering (p. 296) | html | pdf |
  - 14.1.9. Anomalous scattering without isomorphous replacement (p. 297) | html | pdf |
  - 14.1.10. Location of heavy-atom sites (p. 297) | html | pdf |
  - 14.1.11. Use of anomalous-scattering data in heavy-atom location (p. 297) | html | pdf |
  - 14.1.12. Use of difference Fourier syntheses (p. 297) | html | pdf |
  - 14.1.13. Single isomorphous replacement (pp. 297-298) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 14.1.2.1. (a) Harker construction for a single isomorphous replacement (p. 293) | html | pdf |
    - Fig. 14.1.3.1. (a) Harker construction for a double isomorphous replacement (p. 294) | html | pdf |
    - Fig. 14.1.4.1. Vector diagram illustrating the lack of closure, ɛ, of an isomorphous-replacement phase triangle (p. 294) | html | pdf |
    - Fig. 14.1.7.1. (a) Vector diagrams illustrating anomalous scattering for the reflections hkl and $[\overline{hkl}]$ (p. 295) | html | pdf |
    - Fig. 14.1.7.2. Harker construction for a single isomorphous replacement with anomalous scattering, in the absence of errors (p. 296) | html | pdf |
    - Fig. 14.1.8.1. Vector diagrams illustrating lack of closure in the anomalous-scattering method (p. 296) | html | pdf |
    - Fig. 14.1.8.2. Combination of isomorphous replacement and anomalous-scattering phase probabilities for a single isomorphous replacement (p. 296) | html | pdf |
    - Fig. 14.1.13.1. The consequences of using the incorrect hand for the heavy-atom arrangement in phase determination (p. 297) | html | pdf |
- 14.2. MAD and MIR (pp. 299-309) | html | pdf | chapter contents |
  J. L. Smith, W. A. Hendrickson, T. C. Terwilliger and J. Berendzen
  - 14.2.1. Multiwavelength anomalous diffraction (pp. 299-303) | html | pdf |
    J. L. Smith and W. A. Hendrickson
    - 14.2.1.1. Anomalous scattering factors (pp. 299-300) | html | pdf |
    - 14.2.1.2. A phase equation for MAD (p. 300) | html | pdf |
    - 14.2.1.3. Diffraction ratios for estimating the MAD phasing signal (p. 301) | html | pdf |
    - 14.2.1.4. Experimental considerations (pp. 301-302) | html | pdf |
    - 14.2.1.5. Data handling (p. 302) | html | pdf |
    - 14.2.1.6. Approaches to MAD phasing (pp. 302-303) | html | pdf |
    - 14.2.1.7. Determination of the anomalous-scatterer partial structure (p. 303) | html | pdf |
    - 14.2.1.8. General anomalous-scatterer labels for biological macromolecules (p. 303) | html | pdf |
  - 14.2.2. Automated MAD and MIR structure solution (pp. 303-307) | html | pdf |
    T. C. Terwilliger and J. Berendzen
    - 14.2.2.1. Introduction (p. 303) | html | pdf |
    - 14.2.2.2. MAD and MIR structure solution (pp. 303-304) | html | pdf |
    - 14.2.2.3. Decision making and structure solution (p. 304) | html | pdf |
    - 14.2.2.4. The need for rapid refinement and phasing during automated structure solution (p. 304) | html | pdf |
    - 14.2.2.5. Conversion of MAD data to a pseudo-SIRAS form (pp. 304-305) | html | pdf |
    - 14.2.2.6. Scoring of trial heavy-atom solutions (pp. 305-306) | html | pdf |
    - 14.2.2.7. Automated MIR and MAD structure determination (p. 306) | html | pdf |
    - 14.2.2.8. Generation of model X-ray data sets (pp. 306-307) | html | pdf |
    - 14.2.2.9. Conclusions (p. 307) | html | pdf |
    - 14.2.2.10. Software availability (p. 307) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 14.2.1.1. Anomalous scattering factors for Se in a protein labelled with selenomethionine (p. 300) | html | pdf |

Density modification and phase combination
- 15.1. Phase improvement by iterative density modification (pp. 311-324) | html | pdf | chapter contents |
  K. Y. J. Zhang, K. D. Cowtan and P. Main
  - 15.1.1. Introduction (p. 311) | html | pdf |
  - 15.1.2. Density-modification methods (pp. 311-318) | html | pdf |
    - 15.1.2.1. Solvent flattening (pp. 311-314) | html | pdf |
      - 15.1.2.1.1. Introduction (pp. 311-313) | html | pdf |
      - 15.1.2.1.2. The automated convolution method for molecular-boundary identification (p. 313) | html | pdf |
      - 15.1.2.1.3. The solvent-flattening procedure (p. 314) | html | pdf |
    - 15.1.2.2. Histogram matching (pp. 314-316) | html | pdf |
      - 15.1.2.2.1. Introduction (p. 314) | html | pdf |
      - 15.1.2.2.2. The prediction of the ideal histogram (pp. 314-315) | html | pdf |
      - 15.1.2.2.3. The process of histogram matching (pp. 315-316) | html | pdf |
      - 15.1.2.2.4. Scaling the observed structure-factor amplitudes according to the ideal density histogram (p. 316) | html | pdf |
    - 15.1.2.3. Averaging (pp. 316-317) | html | pdf |
      - 15.1.2.3.1. Introduction (p. 316) | html | pdf |
      - 15.1.2.3.2. The determination of noncrystallographic symmetry (pp. 316-317) | html | pdf |
      - 15.1.2.3.3. The refinement of noncrystallographic symmetry (p. 317) | html | pdf |
      - 15.1.2.3.4. The averaging of NCS-related molecules (p. 317) | html | pdf |
    - 15.1.2.4. Skeletonization (pp. 317-318) | html | pdf |
    - 15.1.2.5. Sayre's equation (p. 318) | html | pdf |
      - 15.1.2.5.1. Sayre's equation in real and reciprocal space (p. 318) | 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. 318) | html | pdf |
    - 15.1.2.6. Atomization (p. 318) | html | pdf |
  - 15.1.3. Reciprocal-space interpretation of density modification (p. 319) | html | pdf |
  - 15.1.4. Phase combination (pp. 319-321) | html | pdf |
    - 15.1.4.1. Sim and $[\sigma_{a}]$ weighting (p. 320) | html | pdf |
    - 15.1.4.2. Reflection omit (p. 320) | html | pdf |
    - 15.1.4.3. The γ correction and solvent flipping (pp. 320-321) | html | pdf |
  - 15.1.5. Combining constraints for phase improvement (pp. 321-323) | html | pdf |
    - 15.1.5.1. The system of nonlinear constraint equations (p. 321) | html | pdf |
    - 15.1.5.2. Least-squares solution to the system of nonlinear constraint equations (pp. 321-323) | html | pdf |
      - 15.1.5.2.1. The conjugate-gradient method (p. 322) | html | pdf |
      - 15.1.5.2.2. The full-matrix solution (pp. 322-323) | html | pdf |
      - 15.1.5.2.3. The diagonal approximation (p. 323) | html | pdf |
  - 15.1.6. Example (pp. 323-324) | 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. 311) | html | pdf |
    - Fig. 15.1.2.2. Solvent mask determined from a map by Wang's method (p. 313) | html | pdf |
    - Fig. 15.1.2.3. Transformation of density ρ to $[\rho'_{\rm mod}]$ by histogram matching (p. 315) | html | pdf |
    - Fig. 15.1.2.4. Types of noncrystallographic symmetry and averaging calculation (p. 316) | html | pdf |
    - Fig. 15.1.3.1. The functions $[g({\bf x})]$ and $[G({\bf h})]$ for solvent flattening, histogram matching and averaging (p. 319) | html | pdf |
    - Fig. 15.1.6.1. Phase correlations after different combinations of density modifications (p. 323) | html | pdf |
  - Tables
    - Table 15.1.2.1. Constraints used in density modification (p. 312) | html | pdf |
- 15.2. Model phases: probabilities, bias and maps (pp. 325-331) | html | pdf | chapter contents |
  R. J. Read
  - 15.2.1. Introduction (p. 325) | html | pdf |
  - 15.2.2. Model bias: importance of phase (p. 325) | html | pdf |
    - 15.2.2.1. Parseval's theorem (p. 325) | html | pdf |
  - 15.2.3. Structure-factor probability relationships (pp. 325-327) | html | pdf |
    - 15.2.3.1. Wilson and Sim structure-factor distributions in P1 (pp. 325-326) | html | pdf |
    - 15.2.3.2. Probability distributions for variable coordinate errors (p. 326) | html | pdf |
    - 15.2.3.3. General treatment of the structure-factor distribution (pp. 326-327) | html | pdf |
    - 15.2.3.4. Estimating $[\sigma_{A}]$ (p. 327) | html | pdf |
  - 15.2.4. Figure-of-merit weighting for model phases (p. 327) | html | pdf |
  - 15.2.5. Map coefficients to reduce model bias (pp. 327-328) | html | pdf |
    - 15.2.5.1. Model bias in figure-of-merit weighted maps (pp. 327-328) | html | pdf |
    - 15.2.5.2. Model bias in combined phase maps (p. 328) | html | pdf |
  - 15.2.6. Estimation of overall coordinate error (p. 328) | html | pdf |
  - 15.2.7. Difference-map coefficients (p. 328) | html | pdf |
  - 15.2.8. Refinement bias (pp. 328-329) | html | pdf |
  - 15.2.9. Maximum-likelihood structure refinement (p. 329) | 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. 325) | html | pdf |
    - Fig. 15.2.3.1. Centroid of the structure-factor contribution from a single atom (p. 326) | 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. 327) | 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. 327) | html | pdf |

Direct methods
- 16.1. Ab initio phasing (pp. 333-345) | html | pdf | chapter contents |
  G. M. Sheldrick, H. A. Hauptman, C. M. Weeks, R. Miller and I. Usón
  - 16.1.1. Introduction (p. 333) | html | pdf |
  - 16.1.2. Normalized structure-factor magnitudes (pp. 333-334) | html | pdf |
    - 16.1.2.1. SIR differences (p. 334) | html | pdf |
    - 16.1.2.2. SAS differences (p. 334) | html | pdf |
  - 16.1.3. Starting the phasing process (pp. 334-335) | html | pdf |
    - 16.1.3.1. Structure invariants (p. 334) | html | pdf |
    - 16.1.3.2. `Multisolution' methods and trial structures (pp. 334-335) | html | pdf |
  - 16.1.4. Reciprocal-space phase refinement or expansion (shaking) (pp. 335-336) | html | pdf |
    - 16.1.4.1. The tangent formula (p. 335) | html | pdf |
    - 16.1.4.2. The minimal function (p. 335) | html | pdf |
    - 16.1.4.3. Parameter shift (pp. 335-336) | html | pdf |
  - 16.1.5. Real-space constraints (baking) (p. 336) | html | pdf |
    - 16.1.5.1. Simple peak picking (p. 336) | html | pdf |
    - 16.1.5.2. Iterative peaklist optimization (p. 336) | html | pdf |
    - 16.1.5.3. Random omit maps (p. 336) | html | pdf |
  - 16.1.6. Fourier refinement (twice baking) (pp. 336-337) | html | pdf |
  - 16.1.7. Computer programs for dual-space phasing (pp. 337-339) | html | pdf |
    - 16.1.7.1. Flowchart and program comparison (p. 337) | html | pdf |
    - 16.1.7.2. Parameters and procedures (pp. 337-338) | html | pdf |
    - 16.1.7.3. Recognizing solutions (pp. 338-339) | html | pdf |
  - 16.1.8. Applying dual-space programs successfully (pp. 339-344) | html | pdf |
    - 16.1.8.1. Utilizing Pattersons for better starts (p. 340) | html | pdf |
    - 16.1.8.2. Avoiding false minima (pp. 340-341) | html | pdf |
    - 16.1.8.3. Data resolution and completeness (p. 341) | html | pdf |
    - 16.1.8.4. Choosing a refinement strategy (pp. 342-343) | html | pdf |
    - 16.1.8.5. Expansion to P1 (p. 343) | html | pdf |
    - 16.1.8.6. Substructure applications (pp. 343-344) | html | pdf |
  - 16.1.9. Extending the power of direct methods (pp. 344-345) | html | pdf |
    - 16.1.9.1. Integration with isomorphous replacement (p. 344) | html | pdf |
    - 16.1.9.2. Integration with anomalous dispersion (pp. 344-345) | html | pdf |
    - 16.1.9.3. Integration with multiple-beam diffraction (p. 345) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 16.1.3.1. The conditional probability distribution of the three-phase structure invariants (p. 334) | html | pdf |
    - Fig. 16.1.7.1. A flowchart for the Shake-and-Bake procedure, which is implemented in both SnB and SHELXD (p. 337) | html | pdf |
    - Fig. 16.1.7.2. A histogram of figure-of-merit values (minimal function) for 378 scorpion toxin II trials (p. 338) | html | pdf |
    - Fig. 16.1.7.3. Tracing the history of a solution and a nonsolution trial for scorpion toxin II as a function of Shake-and-Bake cycle (p. 338) | html | pdf |
    - Fig. 16.1.8.1. Success rates for triclinic lysozyme are strongly influenced by the size of the parameter-shift angle (p. 341) | html | pdf |
    - Fig. 16.1.8.2. (a) Mean phase error as a function of resolution for the two independent ab initio SHELXD solutions of the previously unsolved protein hirustasin (p. 341) | html | pdf |
    - Fig. 16.1.8.3. (a) Success rates and (b) cost effectiveness for several dual-space strategies as applied to a 148-atom P1 structure (p. 342) | html | pdf |
    - Fig. 16.1.8.4. Success rates for the 317-atom $[P2_{1}2_{1}2_{1}]$ structure of gramicidin A (p. 343) | html | pdf |
  - Tables
    - Table 16.1.2.1. Theoretical values pertaining to 's (p. 334) | html | pdf |
    - Table 16.1.7.1. Recommended parameter values for the SnB program (p. 338) | html | pdf |
    - Table 16.1.8.1. Some large structures solved by the Shake-and-Bake method (p. 339) | html | pdf |
    - Table 16.1.8.2. Overall success rates for full structure solution for hirustasin using different two-atom search vectors chosen from the Patterson peak list (p. 340) | html | pdf |
    - Table 16.1.8.3. Success rates for three P1 structures illustrate the importance of using complete data to the highest possible resolution (p. 342) | html | pdf |
    - Table 16.1.8.4. Improving success rates by `completing' the vancomycin data (p. 342) | html | pdf |
- 16.2. The maximum-entropy method (pp. 346-351) | html | pdf | chapter contents |
  G. Bricogne
  - 16.2.1. Introduction (p. 346) | html | pdf |
  - 16.2.2. The maximum-entropy principle in a general context (pp. 346-348) | html | pdf |
    - 16.2.2.1. Sources of random symbols and the notion of source entropy (p. 346) | html | pdf |
    - 16.2.2.2. The meaning of entropy: Shannon's theorems (p. 346) | html | pdf |
    - 16.2.2.3. Jaynes' maximum-entropy principle (pp. 346-347) | html | pdf |
    - 16.2.2.4. Jaynes' maximum-entropy formalism (pp. 347-348) | html | pdf |
  - 16.2.3. Adaptation to crystallography (p. 348) | html | pdf |
    - 16.2.3.1. The random-atom model (p. 348) | html | pdf |
    - 16.2.3.2. Conventional direct methods and their limitations (p. 348) | html | pdf |
    - 16.2.3.3. The notion of recentring and the maximum-entropy criterion (p. 348) | html | pdf |
    - 16.2.3.4. The crystallographic maximum-entropy formalism (p. 348) | html | pdf |
    - 16.2.3.5. Connection with the saddlepoint method (p. 348) | html | pdf |
  - References | html | pdf |

Model building and computer graphics
- 17.1. Around O (pp. 353-356) | html | pdf | chapter contents |
  G. J. Kleywegt, J.-Y. Zou, M. Kjeldgaard and T. A. Jones
  - 17.1.1. Introduction (p. 353) | html | pdf |
  - 17.1.2. O (pp. 353-354) | html | pdf |
  - 17.1.3. RAVE (pp. 354-355) | html | pdf |
  - 17.1.4. Structure analysis (p. 355) | html | pdf |
  - 17.1.5. Utilities (pp. 355-356) | html | pdf |
  - 17.1.6. Other services (p. 356) | html | pdf |
  - References | html | pdf |
- 17.2. Molecular graphics and animation (pp. 357-368) | html | pdf | chapter contents |
  A. J. Olson
  - 17.2.1. Introduction (p. 357) | html | pdf |
  - 17.2.2. Background – the evolution of molecular graphics hardware and software (pp. 357-358) | html | pdf |
  - 17.2.3. Representation and visualization of molecular data and models (pp. 358-363) | html | pdf |
    - 17.2.3.1. Geometric representation (pp. 359-360) | html | pdf |
    - 17.2.3.2. Volumetric representation (pp. 360-362) | html | pdf |
    - 17.2.3.3. Information visualization (pp. 362-363) | html | pdf |
  - 17.2.4. Presentation graphics (pp. 363-365) | html | pdf |
    - 17.2.4.1. Illustration (pp. 363-364) | html | pdf |
    - 17.2.4.2. Animation (pp. 364-365) | html | pdf |
    - 17.2.4.3. The return of physical models (p. 365) | html | pdf |
  - 17.2.5. Looking ahead (pp. 365-366) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 17.2.1.1. Model of a crystal structure proposed by René Häuy (p. 357) | html | pdf |
    - Fig. 17.2.2.1. One bay of X-RAC showing coefficient panels and the display oscilloscope (p. 357) | html | pdf |
    - Fig. 17.2.3.1. ORTEP plot of phenylhydroxynorbornanone showing atomic thermal ellipsoids (p. 358) | html | pdf |
    - Fig. 17.2.3.2. Ribbon diagram of actin monomer (PDB code: 1atn) (Kabsch et al (p. 359) | html | pdf |
    - Fig. 17.2.3.3. Simple bonding diagram of a DNA structure (PDB code: 140D) (Mujeeb et al (p. 359) | html | pdf |
    - Fig. 17.2.3.4. CPK representation of the same DNA structure as in Fig. 17.2.3.3 (p. 360) | html | pdf |
    - Fig. 17.2.3.5. Solvent-excluded surface of the DNA structure using a water probe radius of 1.5 Å (p. 360) | html | pdf |
    - Fig. 17.2.3.6. Hydrophobicity mapped onto a molecular surface (p. 361) | html | pdf |
    - Fig. 17.2.3.7. Crystallographic electron-density isosurfaces, showing details of a protein iron–sulfur cluster (p. 362) | html | pdf |
    - Fig. 17.2.3.8. A difference-electron-density map of a minor-groove drug binding in DNA (p. 362) | 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. 363) | html | pdf |
    - Fig. 17.2.4.1. Line-art molecular illustration (p. 364) | html | pdf |
    - Fig. 17.2.4.2. A stereolithographic model of betalactamase inhibitory protein (BLIP) (p. 364) | html | pdf |
    - Fig. 17.2.5.1. This image represents a volume of blood plasma 750 Å on a side (p. 365) | html | pdf |

Refinement
- 18.1. Introduction to refinement (pp. 369-374) | html | pdf | chapter contents |
  L. F. Ten Eyck and K. D. Watenpaugh
  - 18.1.1. Overview (p. 369) | html | pdf |
  - 18.1.2. Background (p. 369) | html | pdf |
  - 18.1.3. Objectives (p. 369) | html | pdf |
  - 18.1.4. Least squares and maximum likelihood (pp. 369-370) | html | pdf |
  - 18.1.5. Optimization (p. 370) | html | pdf |
  - 18.1.6. Data (p. 370) | html | pdf |
  - 18.1.7. Models (pp. 370-372) | html | pdf |
  - 18.1.8. Optimization methods (pp. 372-373) | html | pdf |
    - 18.1.8.1. Solving the refinement equations (p. 372) | html | pdf |
    - 18.1.8.2. Normal equations (p. 372) | html | pdf |
    - 18.1.8.3. Choice of optimization method (p. 373) | html | pdf |
    - 18.1.8.4. Singularity in refinement (p. 373) | html | pdf |
  - 18.1.9. Evaluation of the model (pp. 373-374) | html | pdf |
    - 18.1.9.1. Examination of outliers in the model (p. 373) | html | pdf |
    - 18.1.9.2. Examination of model electron density (pp. 373-374) | html | pdf |
    - 18.1.9.3. R and R_free (p. 374) | html | pdf |
  - 18.1.10. Conclusion (p. 374) | html | pdf |
  - References | html | pdf |
- 18.2. Enhanced macromolecular refinement by simulated annealing (pp. 375-381) | html | pdf | chapter contents |
  A. T. Brunger, P. D. Adams and L. M. Rice
  - 18.2.1. Introduction (p. 375) | html | pdf |
  - 18.2.2. Cross validation (p. 375) | html | pdf |
  - 18.2.3. The target function (pp. 375-377) | html | pdf |
    - 18.2.3.1. X-ray diffraction data versus model (pp. 376-377) | html | pdf |
    - 18.2.3.2. A priori chemical information (p. 377) | html | pdf |
  - 18.2.4. Searching conformational space (pp. 377-379) | html | pdf |
    - 18.2.4.1. Molecular dynamics (p. 378) | html | pdf |
    - 18.2.4.2. Temperature control (p. 378) | html | pdf |
    - 18.2.4.3. Annealing schedules (pp. 378-379) | html | pdf |
    - 18.2.4.4. An intuitive explanation of simulated annealing (p. 379) | html | pdf |
  - 18.2.5. Examples (pp. 379-380) | html | pdf |
  - 18.2.6. Multi-start refinement and structure-factor averaging (p. 380) | html | pdf |
  - 18.2.7. Ensemble models (p. 380) | html | pdf |
  - 18.2.8. Conclusions (p. 381) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.2.2.1. Effect of resolution on coordinate-error estimates (p. 376) | html | pdf |
    - Fig. 18.2.3.1. The Gaussian probability distribution forms the basis of maximum-likelihood targets in crystallographic refinement (p. 376) | html | pdf |
    - Fig. 18.2.4.1. Illustration of simulated annealing for minimization of a one-dimensional function (p. 378) | html | pdf |
    - Fig. 18.2.5.1. Simulated annealing produces better models than extensive conjugate-gradient minimization (p. 379) | html | pdf |
    - Fig. 18.2.5.2. Maximum-likelihood targets significantly decrease model bias in simulated-annealing refinement (p. 380) | html | pdf |
- 18.3. Structure quality and target parameters (pp. 382-392) | html | pdf | chapter contents |
  R. A. Engh and R. Huber
  - 18.3.1. Purpose of restraints (p. 382) | html | pdf |
    - 18.3.1.1. Utility of restraints: protein/special geometries (p. 382) | html | pdf |
    - 18.3.1.2. Risk of restraints: bias, lack of cross validation (p. 382) | html | pdf |
  - 18.3.2. Formulation of refinement restraints (pp. 382-392) | html | pdf |
    - 18.3.2.1. Choice of properties for restraint (p. 383) | html | pdf |
    - 18.3.2.2. Simple derivation of force constants from parameter distributions (pp. 383-384) | html | pdf |
      - 18.3.2.2.1. Clustering (p. 383) | html | pdf |
      - 18.3.2.2.2. Treatment of outliers (pp. 383-384) | html | pdf |
    - 18.3.2.3. Bonds and angles (pp. 384-390) | html | pdf |
      - 18.3.2.3.1. Peptide parameters: proline, glycine, alanine and CB substitution (p. 384) | html | pdf |
      - 18.3.2.3.2. Aromatic residues: tryptophan, phenylalanine, tyrosine, histidine (p. 384) | html | pdf |
      - 18.3.2.3.3. Aliphatic residues: leucine, isoleucine, valine (p. 384) | html | pdf |
      - 18.3.2.3.4. Neutral polar residues: serine, threonine, glutamine, asparagine (p. 384) | html | pdf |
      - 18.3.2.3.5. Acidic residues: glutamate, aspartate (pp. 384-387) | html | pdf |
      - 18.3.2.3.6. Basic residues: arginine, lysine (p. 387) | html | pdf |
      - 18.3.2.3.7. Sulfur-containing residues: methionine, cysteine, disulfides (pp. 387-390) | html | pdf |
    - 18.3.2.4. Planarity restraints (p. 390) | html | pdf |
    - 18.3.2.5. Torsion angles (pp. 390-391) | html | pdf |
    - 18.3.2.6. Non-bonded interactions (p. 391) | html | pdf |
    - 18.3.2.7. Effects of hydrogen atoms in parameterization (p. 391) | html | pdf |
    - 18.3.2.8. Special geometries: cofactors, ligands, metals etc. (p. 391) | html | pdf |
    - 18.3.2.9. Addition of tailored information sources (p. 392) | html | pdf |
  - 18.3.3. Strategy of application during building/refinement (p. 392) | html | pdf |
    - 18.3.3.1. Confidence in restraints versus information from diffraction (p. 392) | html | pdf |
  - 18.3.4. Future perspectives (p. 392) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 18.3.2.1. Torsion dependence of proline angle geometry (p. 387) | html | pdf |
    - Fig. 18.3.2.2. Bimodal distributions for tyrosine (p. 387) | html | pdf |
    - Fig. 18.3.2.3. Tryptophan $[\chi_{2}]$ dihedral angle distribution (p. 390) | html | pdf |
  - Tables
    - Table 18.3.2.1. Bond lengths of standard amino-acid side chains (pp. 385-386) | html | pdf |
    - Table 18.3.2.2. Bond angles of standard amino-acid side chains (pp. 388-390) | html | pdf |
    - Table 18.3.2.3. Bond lengths (Å) and angles (°) of peptide backbone fragments (p. 391) | html | pdf |
- 18.4. Refinement at atomic resolution (pp. 393-402) | html | pdf | chapter contents |
  Z. Dauter, G. N. Murshudov and K. S. Wilson
  - 18.4.1. Definition of atomic resolution (pp. 393-395) | html | pdf |
    - 18.4.1.1. Ab initio phasing and atomic resolution (p. 395) | html | pdf |
  - 18.4.2. Data (p. 395) | html | pdf |
    - 18.4.2.1. Data quality (p. 395) | html | pdf |
    - 18.4.2.2. Anisotropic scaling (p. 395) | html | pdf |
  - 18.4.3. Computational algorithms and strategies (p. 396) | html | pdf |
    - 18.4.3.1. Classical least-squares refinement of small molecules (p. 396) | html | pdf |
    - 18.4.3.2. Least-squares refinement of large structures (p. 396) | html | pdf |
    - 18.4.3.3. Fast Fourier transform (p. 396) | html | pdf |
    - 18.4.3.4. Maximum likelihood (p. 396) | html | pdf |
    - 18.4.3.5. Computer power (p. 396) | html | pdf |
  - 18.4.4. Computational options and tactics (pp. 396-398) | html | pdf |
    - 18.4.4.1. Use of F or F² (pp. 396-397) | html | pdf |
    - 18.4.4.2. Restraints and/or constraints on coordinates and ADPs (p. 397) | html | pdf |
    - 18.4.4.3. Partial occupancy (p. 397) | html | pdf |
    - 18.4.4.4. Validation of extra parameters during the refinement process (pp. 397-398) | html | pdf |
    - 18.4.4.5. Practical strategies (p. 398) | html | pdf |
  - 18.4.5. Features in the refined model (pp. 398-401) | html | pdf |
    - 18.4.5.1. Hydrogen atoms (pp. 398-399) | html | pdf |
    - 18.4.5.2. Anisotropic atomic displacement parameters (p. 399) | html | pdf |
    - 18.4.5.3. Alternative conformations (p. 399) | html | pdf |
    - 18.4.5.4. Ordered solvent water (pp. 399-400) | html | pdf |
    - 18.4.5.5. Automatic location of water sites (p. 400) | html | pdf |
    - 18.4.5.6. Bulk solvent and the low-resolution reflections (pp. 400-401) | html | pdf |
    - 18.4.5.7. Metal ions and other ligands in the solvent (p. 401) | html | pdf |
    - 18.4.5.8. Deformation density (p. 401) | html | pdf |
  - 18.4.6. Quality assessment of the model (p. 401) | html | pdf |
  - 18.4.7. Relation to biological chemistry (pp. 401-402) | 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. 393) | html | pdf |
    - Fig. 18.4.1.2. Histograms of B values for a protein structure, Micrococcus lysodecticus catalase (Murshudov et al (p. 394) | 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 (p. 398) | html | pdf |
    - Fig. 18.4.5.2. Schematic representation of the bulk-solvent models described in the text (p. 400) | html | pdf |
  - Tables
    - Table 18.4.1.1. The parameters of an atomic model (p. 393) | html | pdf |
    - Table 18.4.1.2. Features which can be seen in the electron density at different resolutions (p. 394) | html | pdf |
- 18.5. Coordinate uncertainty (pp. 403-418) | html | pdf | chapter contents |
  D. W. J. Cruickshank
  - 18.5.1. Introduction (p. 403) | html | pdf |
    - 18.5.1.1. Background (p. 403) | html | pdf |
    - 18.5.1.2. Accuracy and precision (p. 403) | html | pdf |
    - 18.5.1.3. Effect of atomic displacement parameters (or `temperature factors') (p. 403) | html | pdf |
  - 18.5.2. The least-squares method (pp. 404-405) | html | pdf |
    - 18.5.2.1. The normal equations (p. 404) | html | pdf |
    - 18.5.2.2. Weights (p. 404) | html | pdf |
    - 18.5.2.3. Statistical descriptors and goodness of fit (pp. 404-405) | html | pdf |
  - 18.5.3. Restrained refinement (pp. 405-406) | html | pdf |
    - 18.5.3.1. Residual function (p. 405) | html | pdf |
    - 18.5.3.2. A very simple protein model (pp. 405-406) | html | pdf |
    - 18.5.3.3. Relative weighting of diffraction and restraint terms (p. 406) | html | pdf |
  - 18.5.4. Two examples of full-matrix inversion (pp. 406-409) | html | pdf |
    - 18.5.4.1. Unrestrained and restrained inversions for concanavalin A (pp. 406-408) | html | pdf |
    - 18.5.4.2. Unrestrained inversion for an immunoglobulin (p. 408) | html | pdf |
    - 18.5.4.3. Comments on restrained refinement (p. 408) | html | pdf |
    - 18.5.4.4. Full-matrix estimates of precision (pp. 408-409) | html | pdf |
  - 18.5.5. Approximate methods (p. 409) | html | pdf |
    - 18.5.5.1. Block calculations (p. 409) | html | pdf |
    - 18.5.5.2. The modified Fourier method (p. 409) | html | pdf |
    - 18.5.5.3. Application of the modified Fourier method (p. 409) | html | pdf |
  - 18.5.6. The diffraction-component precision index (p. 410) | html | pdf |
    - 18.5.6.1. Statistical expectation of error dependence (p. 410) | html | pdf |
    - 18.5.6.2. A simple error formula (p. 410) | html | pdf |
    - 18.5.6.3. Extension for low-resolution structures and use of R_free (p. 410) | html | pdf |
    - 18.5.6.4. Position error (p. 410) | html | pdf |
  - 18.5.7. Examples of the diffraction-component precision index (pp. 411-412) | html | pdf |
    - 18.5.7.1. Full-matrix comparison with the diffraction-component precision index (p. 411) | html | pdf |
    - 18.5.7.2. Further examples of the DPI using R (p. 411) | html | pdf |
    - 18.5.7.3. Examples of the DPI using R_free (pp. 411-412) | html | pdf |
    - 18.5.7.4. Comments on the diffraction-component precision index (p. 412) | html | pdf |
  - 18.5.8. Luzzati plots (pp. 412-414) | html | pdf |
    - 18.5.8.1. Luzzati's theory (pp. 412-413) | html | pdf |
    - 18.5.8.2. Statistical reinterpretation of Luzzati plots (pp. 413-414) | html | pdf |
    - 18.5.8.3. Comments on Luzzati plots (p. 414) | 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. 407) | 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. 407) | 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. 408) | 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. 408) | 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. 413) | 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. 411) | html | pdf |
    - Table 18.5.7.2. Examples of diffraction-component precision indices (DPIs) (p. 411) | html | pdf |
    - Table 18.5.7.3. Comparison of DPIs using R and R_free (p. 412) | 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. 413) | html | pdf |

Other experimental techniques
- 19.1. Neutron crystallography: methods and information content (pp. 419-422) | html | pdf | chapter contents |
  A. A. Kossiakoff
  - 19.1.1. Introduction (p. 419) | html | pdf |
  - 19.1.2. Diffraction geometries (p. 419) | html | pdf |
    - 19.1.2.1. Quasi-Laue diffractometry (p. 419) | html | pdf |
  - 19.1.3. Neutron density maps – information content (pp. 419-420) | html | pdf |
  - 19.1.4. Phasing models and evaluation of correctness (p. 420) | html | pdf |
  - 19.1.5. Evaluation of correctness (pp. 420-421) | html | pdf |
  - 19.1.6. Refinement (p. 421) | html | pdf |
  - 19.1.7. D₂O − H₂O solvent difference maps (pp. 421-422) | html | pdf |
  - 19.1.8. Applications of D₂O − H₂O solvent difference maps (p. 422) | html | pdf |
    - 19.1.8.1. Orientation of water molecules (p. 422) | html | pdf |
    - 19.1.8.2. H/D exchange (p. 422) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.1.3.1. Information content in neutron density maps (p. 420) | html | pdf |
    - Fig. 19.1.3.2. Sections of a neutron difference Fourier map showing methyl hydrogen densities for several representative methyl groups (p. 420) | html | pdf |
    - Fig. 19.1.5.1. Difference map of Asn34 in the trypsin structure (p. 421) | html | pdf |
    - Fig. 19.1.8.1. Sections of neutron density maps taken in the plane of the peptide group (p. 421) | html | pdf |
  - Tables
    - Table 19.1.1.1. Scattering lengths for atom types (p. 419) | html | pdf |
- 19.2. Electron diffraction of protein crystals (pp. 423-427) | html | pdf | chapter contents |
  W. Chiu
  - 19.2.1. Electron scattering (p. 423) | html | pdf |
  - 19.2.2. The electron microscope (p. 423) | html | pdf |
  - 19.2.3. Data collection (pp. 423-424) | html | pdf |
    - 19.2.3.1. Specimen preparation (p. 423) | html | pdf |
    - 19.2.3.2. Radiation damage (p. 424) | html | pdf |
    - 19.2.3.3. Other technical factors (p. 424) | html | pdf |
  - 19.2.4. Data processing (pp. 425-427) | html | pdf |
    - 19.2.4.1. Data sampling (pp. 425-426) | html | pdf |
    - 19.2.4.2. Amplitudes and phases (pp. 426-427) | html | pdf |
    - 19.2.4.3. 3D map (p. 427) | html | pdf |
    - 19.2.4.4. Refinement (p. 427) | html | pdf |
  - 19.2.5. Future development (p. 427) | 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. 424) | html | pdf |
    - Fig. 19.2.4.1. Schematic diagram of data distribution in Fourier space for a two-dimensional crystal (p. 424) | 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. 425) | html | pdf |
    - Fig. 19.2.4.3. Ribbon diagram of a tubulin dimer, whose structure has been solved to 3.7 Å resolution (p. 426) | html | pdf |
- 19.3. Small-angle X-ray scattering (pp. 428-437) | html | pdf | chapter contents |
  H. Tsuruta and J. E. Johnson
  - 19.3.1. Introduction (p. 428) | html | pdf |
  - 19.3.2. Small-angle single-crystal X-ray diffraction studies (pp. 428-429) | html | pdf |
  - 19.3.3. Solution X-ray scattering studies (pp. 429-437) | html | pdf |
    - 19.3.3.1. Information content of solution scattering (pp. 429-432) | html | pdf |
      - 19.3.3.1.1. Solution scattering and crystal structures (pp. 431-432) | html | pdf |
      - 19.3.3.1.2. Low-resolution model determination using solution scattering (p. 432) | html | pdf |
    - 19.3.3.2. Instrumentation for small-angle X-ray scattering (pp. 432-433) | html | pdf |
      - 19.3.3.2.1. Instruments on conventional sources (p. 433) | html | pdf |
      - 19.3.3.2.2. Synchrotron instruments (p. 433) | html | pdf |
    - 19.3.3.3. Experimental considerations (pp. 434-436) | html | pdf |
      - 19.3.3.3.1. Sample preparation (p. 434) | html | pdf |
      - 19.3.3.3.2. Sample-handling devices (pp. 434-435) | html | pdf |
      - 19.3.3.3.3. Designing experiments (p. 435) | html | pdf |
      - 19.3.3.3.4. Data-collection practices (p. 435) | html | pdf |
      - 19.3.3.3.5. Data processing and analysis (pp. 435-436) | html | pdf |
    - 19.3.3.4. Recent applications of solution X-ray scattering in structural molecular biology (pp. 436-437) | html | pdf |
      - 19.3.3.4.1. Studies of proteins in solution that complement high-resolution structures (pp. 436-437) | html | pdf |
      - 19.3.3.4.2. Time-resolved studies (p. 437) | html | pdf |
      - 19.3.3.4.3. Protein-folding studies (p. 437) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.3.2.1. A cross section of the electron-density map of sFHV at 14 Å resolution (p. 428) | 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. 429) | html | pdf |
    - Fig. 19.3.3.1. Definition of electron-density contrast (p. 430) | 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. 430) | html | pdf |
    - Fig. 19.3.3.3. (a) Interparticle interference in biological small-angle scattering (p. 431) | html | pdf |
    - Fig. 19.3.3.4. Definition of the electron pair distance distribution function $[P({\bf r})]$ (p. 432) | 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. 433) | 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. 434) | html | pdf |
  - Tables
    - Table 19.3.3.1. List of commonly used software for solution scattering (p. 436) | html | pdf |
- 19.4. Small-angle neutron scattering (pp. 438-443) | html | pdf | chapter contents |
  D. M. Engelman and P. B. Moore
  - 19.4.1. Introduction (p. 438) | html | pdf |
  - 19.4.2. Fundamental relationships (pp. 438-439) | html | pdf |
  - 19.4.3. Contrast variation (pp. 439-441) | html | pdf |
    - 19.4.3.1. Variation of solvent density (pp. 439-440) | html | pdf |
    - 19.4.3.2. Variation of internal contrast (p. 440) | html | pdf |
    - 19.4.3.3. Relationship of contrasting regions (pp. 440-441) | html | pdf |
    - 19.4.3.4. The triple isotopic substitution method (p. 441) | html | pdf |
    - 19.4.3.5. Nuclear spin contrast variation (p. 441) | html | pdf |
    - 19.4.3.6. Interpretation of small-angle scattering using models (p. 441) | html | pdf |
    - 19.4.3.7. Use of forward scattering to measure molecular weights (p. 441) | html | pdf |
  - 19.4.4. Distance measurements (p. 442) | html | pdf |
    - 19.4.4.1. Theory and background (p. 442) | html | pdf |
    - 19.4.4.2. Neutron distance measurements (p. 442) | html | pdf |
    - 19.4.4.3. The statistical labelling method (p. 442) | html | pdf |
  - 19.4.5. Practical considerations (pp. 442-443) | html | pdf |
    - 19.4.5.1. Feasibility (pp. 442-443) | html | pdf |
    - 19.4.5.2. Homogeneity and stability (p. 443) | html | pdf |
    - 19.4.5.3. Solvent conditions (p. 443) | html | pdf |
  - 19.4.6. Examples (p. 443) | html | pdf |
    - 19.4.6.1. Contrast variation (p. 443) | html | pdf |
    - 19.4.6.2. Contrast matching (p. 443) | html | pdf |
    - 19.4.6.3. Spin contrast variation (p. 443) | html | pdf |
    - 19.4.6.4. Specific deuteration, combination with X-ray measurements (p. 443) | html | pdf |
    - 19.4.6.5. Distance measurements and triangulation (p. 443) | html | pdf |
  - References | html | pdf |
- 19.5. Fibre diffraction (pp. 444-450) | html | pdf | chapter contents |
  R. Chandrasekaran and G. Stubbs
  - 19.5.1. Introduction (p. 444) | html | pdf |
  - 19.5.2. Types of fibres (pp. 444-445) | html | pdf |
  - 19.5.3. Diffraction by helical molecules (pp. 445-446) | html | pdf |
    - 19.5.3.1. Fibre diffraction patterns (p. 445) | html | pdf |
    - 19.5.3.2. Helical symmetry (p. 445) | html | pdf |
    - 19.5.3.3. Structure factors (p. 445) | html | pdf |
    - 19.5.3.4. Fourier–Bessel syntheses (p. 445) | html | pdf |
    - 19.5.3.5. Diffracted intensities: noncrystalline fibres (p. 445) | html | pdf |
    - 19.5.3.6. Diffracted intensities: polycrystalline fibres (pp. 445-446) | html | pdf |
  - 19.5.4. Fibre preparation (p. 446) | html | pdf |
  - 19.5.5. Data collection (p. 446) | html | pdf |
  - 19.5.6. Data processing (pp. 446-447) | html | pdf |
    - 19.5.6.1. Coordinate transformation (p. 446) | html | pdf |
    - 19.5.6.2. Intensity correction (p. 446) | html | pdf |
    - 19.5.6.3. Background subtraction (pp. 446-447) | html | pdf |
    - 19.5.6.4. Integration of crystalline fibre data (p. 447) | html | pdf |
    - 19.5.6.5. Integration of continuous data (p. 447) | html | pdf |
  - 19.5.7. Determination of structures (pp. 447-449) | html | pdf |
    - 19.5.7.1. Initial models: small unit cells (p. 447) | html | pdf |
    - 19.5.7.2. Refinement: small unit cells (pp. 447-448) | html | pdf |
    - 19.5.7.3. Data-to-parameter ratio (p. 448) | html | pdf |
    - 19.5.7.4. Initial models: large unit cells (p. 448) | html | pdf |
    - 19.5.7.5. Refinement: large unit cells (p. 448) | html | pdf |
    - 19.5.7.6. Difference Fourier methods (pp. 448-449) | html | pdf |
    - 19.5.7.7. Evaluation (p. 449) | html | pdf |
  - 19.5.8. Structures determined by X-ray fibre diffraction (pp. 449-450) | html | pdf |
    - 19.5.8.1. Polypeptides (p. 449) | html | pdf |
    - 19.5.8.2. Polynucleotides (p. 449) | html | pdf |
    - 19.5.8.3. Polysaccharides (pp. 449-450) | html | pdf |
    - 19.5.8.4. Helical viruses and bacteriophages (p. 450) | html | pdf |
    - 19.5.8.5. Other large assemblies (p. 450) | 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. 444) | 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. 447) | html | pdf |
    - Fig. 19.5.8.1. X-ray diffraction pattern from an oriented sol of the U2 strain of tobacco mosaic virus (p. 450) | html | pdf |
- 19.6. Electron cryomicroscopy (pp. 451-463) | html | pdf | chapter contents |
  T. S. Baker and R. Henderson
  - 19.6.1. Abbreviations used (p. 451) | html | pdf |
  - 19.6.2. The role of electron microscopy in macromolecular structure determination (pp. 451-452) | html | pdf |
  - 19.6.3. Electron scattering and radiation damage (pp. 452-453) | html | pdf |
    - 19.6.3.1. Elastic and inelastic scattering (p. 452) | html | pdf |
    - 19.6.3.2. Radiation damage (pp. 452-453) | html | pdf |
    - 19.6.3.3. Required properties of the illuminating electron beam (p. 453) | html | pdf |
  - 19.6.4. Three-dimensional electron cryomicroscopy of macromolecules (pp. 453-463) | html | pdf |
    - 19.6.4.1. Overview of conceptual steps (pp. 453-454) | html | pdf |
    - 19.6.4.2. Classification of macromolecules (pp. 454-455) | html | pdf |
    - 19.6.4.3. Specimen preparation (pp. 455-456) | html | pdf |
    - 19.6.4.4. Microscopy (pp. 456-458) | html | pdf |
    - 19.6.4.5. Selection and preprocessing of digitized images (pp. 458-459) | html | pdf |
    - 19.6.4.6. Image processing and 3D reconstruction (pp. 459-461) | html | pdf |
      - 19.6.4.6.1. 2D crystals (pp. 459-460) | html | pdf |
      - 19.6.4.6.2. Helical particles (pp. 460-461) | html | pdf |
      - 19.6.4.6.3. Icosahedral particles (p. 461) | html | pdf |
    - 19.6.4.7. Visualization, modelling and interpretation of results (pp. 461-462) | html | pdf |
    - 19.6.4.8. Solving the X-ray phase problem with cryo EM maps (pp. 462-463) | html | pdf |
  - 19.6.5. Recent trends (p. 463) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 19.6.2.1. Schematic diagram showing the principle of image formation and diffraction in the transmission electron microscope (p. 451) | html | pdf |
    - Fig. 19.6.4.1. Flow diagram showing all the procedures involved in electron cryomicroscopy from sample preparation to map interpretation (p. 453) | 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. 454) | html | pdf |
    - Fig. 19.6.4.3. Schematic diagram to illustrate the principle of 3D reconstruction (p. 454) | html | pdf |
    - Fig. 19.6.4.4. Representative plots of the microscope contrast-transfer function (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. 458) | html | pdf |
    - Fig. 19.6.5.1. Examples of macromolecules studied by cryo EM and 3D image reconstruction and the resulting 3D structures (bottom row) after cryo EM analysis (p. 463) | html | pdf |
  - Tables
    - Table 19.6.4.1. Classification of macromolecules according to periodic order and symmetry (p. 455) | html | pdf |
    - Table 19.6.4.2. Methods of three-dimensional image reconstruction (p. 460) | html | pdf |
- 19.7. Nuclear magnetic resonance (NMR) spectroscopy (pp. 464-479) | html | pdf | chapter contents |
  K. Wüthrich
  - 19.7.1. Complementary roles of NMR in solution and X-ray crystallography in structural biology (p. 464) | html | pdf |
  - 19.7.2. A standard protocol for NMR structure determination of proteins and nucleic acids (pp. 464-466) | html | pdf |
  - 19.7.3. Combined use of single-crystal X-ray diffraction and solution NMR for structure determination (p. 466) | html | pdf |
  - 19.7.4. NMR studies of solvation in solution (p. 466) | html | pdf |
  - 19.7.5. NMR studies of rate processes and conformational equilibria in three-dimensional macromolecular structures (pp. 466-467) | 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. 464) | html | pdf |
    - Fig. 19.7.2.2. (a) Sequential resonance assignment based on sequential ¹H–¹H NOEs (p. 465) | 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. 466) | html | pdf |
    - Fig. 19.7.5.1. 180° ring flips of tyrosine and phenylalanine about the C^β—C¹ bond (p. 467) | html | pdf |

Energy calculations and molecular dynamics
- 20.1. Molecular-dynamics simulation of protein crystals: convergence of molecular properties of ubiquitin (pp. 481-488) | html | pdf | chapter contents |
  U. Stocker and W. F. van Gunsteren
  - 20.1.1. Introduction (p. 481) | html | pdf |
  - 20.1.2. Methods (pp. 481-482) | html | pdf |
  - 20.1.3. Results (pp. 482-488) | html | pdf |
    - 20.1.3.1. Energetic properties (p. 482) | html | pdf |
    - 20.1.3.2. Structural properties (pp. 482-483) | html | pdf |
    - 20.1.3.3. Effect of the translational and rotational fitting procedure (pp. 483-486) | html | pdf |
    - 20.1.3.4. Effect of the averaging period (pp. 486-487) | html | pdf |
    - 20.1.3.5. Internal motions of the proteins (p. 487) | html | pdf |
    - 20.1.3.6. Dihedral-angle fluctuations and transitions (pp. 487-488) | html | pdf |
    - 20.1.3.7. Water diffusion (p. 488) | html | pdf |
  - 20.1.4. Conclusions (p. 488) | 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. 482) | 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. 482) | 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. 483) | 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. 486) | 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. 486) | 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. 486) | 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. 487) | 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. 487) | 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. 488) | html | pdf |
  - Tables
    - Table 20.1.3.1. Occurrence of intramolecular hydrogen bonds (%) during the final 1.6 ns of the simulation (pp. 484-485) | html | pdf |
    - Table 20.1.3.2. Occurrence of intermolecular hydrogen bonds (%) during the final 1.6 ns of the simulation (p. 485) | 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. 488) | 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. 488) | html | pdf |
- 20.2. Molecular-dynamics simulations of biological macromolecules (pp. 489-495) | html | pdf | chapter contents |
  C. B. Post and V. M. Dadarlat
  - 20.2.1. Introduction (p. 489) | html | pdf |
  - 20.2.2. The simulation method (p. 489) | html | pdf |
  - 20.2.3. Potential-energy function (pp. 489-491) | html | pdf |
    - 20.2.3.1. Empirical energy (pp. 489-490) | html | pdf |
    - 20.2.3.2. Particle mesh Ewald (p. 490) | html | pdf |
    - 20.2.3.3. Experimental restraints in the energy function (pp. 490-491) | html | pdf |
  - 20.2.4. Empirical parameterization of the force field (p. 491) | html | pdf |
  - 20.2.5. Modifications in the force field for structure determination (p. 491) | html | pdf |
  - 20.2.6. Internal dynamics and average structures (p. 491) | html | pdf |
  - 20.2.7. Assessment of the simulation procedure (p. 492) | html | pdf |
  - 20.2.8. Effect of crystallographic atomic resolution on structural stability during molecular dynamics (pp. 492-494) | 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. 492) | html | pdf |
    - Fig. 20.2.8.1. Cα tracings of BPTI (p. 493) | 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. 493) | html | pdf |
  - Tables
    - Table 20.2.8.1. R.m.s. coordinate differences between crystallographic structures and average MD structures (p. 493) | html | pdf |

Structure validation
- 21.1. Validation of protein crystal structures (pp. 497-506) | html | pdf | chapter contents |
  G. J. Kleywegt
  - 21.1.1. Introduction (p. 497) | html | pdf |
  - 21.1.2. Types of error (pp. 497-498) | html | pdf |
  - 21.1.3. Detecting outliers (pp. 498-499) | html | pdf |
    - 21.1.3.1. Classes of quality indicators (p. 498) | html | pdf |
    - 21.1.3.2. Local statistics (pp. 498-499) | html | pdf |
    - 21.1.3.3. Global statistics (p. 499) | html | pdf |
  - 21.1.4. Fixing errors (p. 499) | html | pdf |
  - 21.1.5. Preventing errors (pp. 499-500) | html | pdf |
  - 21.1.6. Final model (p. 500) | html | pdf |
  - 21.1.7. A compendium of quality criteria (pp. 500-505) | html | pdf |
    - 21.1.7.1. Data quality (pp. 500-501) | html | pdf |
      - 21.1.7.1.1. Merging R values (pp. 500-501) | html | pdf |
      - 21.1.7.1.2. Completeness (p. 501) | html | pdf |
      - 21.1.7.1.3. Redundancy (p. 501) | html | pdf |
      - 21.1.7.1.4. Signal strength (p. 501) | html | pdf |
      - 21.1.7.1.5. Resolution (p. 501) | html | pdf |
      - 21.1.7.1.6. Unit-cell parameters (p. 501) | html | pdf |
      - 21.1.7.1.7. Symmetry (p. 501) | html | pdf |
    - 21.1.7.2. Model quality, coordinates (pp. 501-504) | html | pdf |
      - 21.1.7.2.1. Geometry and stereochemistry (pp. 501-502) | html | pdf |
      - 21.1.7.2.2. Torsion angles (dihedrals) (pp. 502-503) | html | pdf |
      - 21.1.7.2.3. C^α-only models (p. 503) | html | pdf |
      - 21.1.7.2.4. Contacts and environments (p. 503) | html | pdf |
      - 21.1.7.2.5. Noncrystallographic symmetry (p. 503) | html | pdf |
      - 21.1.7.2.6. Solvent molecules (p. 503) | html | pdf |
      - 21.1.7.2.7. Miscellaneous (pp. 503-504) | html | pdf |
    - 21.1.7.3. Model quality, temperature factors (p. 504) | html | pdf |
    - 21.1.7.4. Model versus experimental data (pp. 504-505) | html | pdf |
      - 21.1.7.4.1. R values (pp. 504-505) | html | pdf |
      - 21.1.7.4.2. Real-space fits (p. 505) | html | pdf |
      - 21.1.7.4.3. Coordinate error estimates (p. 505) | html | pdf |
      - 21.1.7.4.4. Noncrystallographic symmetry (p. 505) | html | pdf |
      - 21.1.7.4.5. Difference density quality (p. 505) | html | pdf |
    - 21.1.7.5. Accountancy (p. 505) | html | pdf |
  - 21.1.8. Future (p. 506) | html | pdf |
  - References | html | pdf |
- 21.2. Assessing the quality of macromolecular structures (pp. 507-519) | 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. 507) | html | pdf |
  - 21.2.2. Validating the geometric and stereochemical parameters of the model (pp. 507-509) | html | pdf |
    - 21.2.2.1. Comparisons against standard values derived from crystals of small molecules (pp. 507-508) | html | pdf |
    - 21.2.2.2. Comparisons against standard values derived from surveys of other macromolecules (pp. 508-509) | html | pdf |
      - 21.2.2.2.1. Validation of stereochemical and non-bonded parameters (p. 508) | html | pdf |
      - 21.2.2.2.2. Validation using knowledge-based interaction potentials and profiles (pp. 508-509) | html | pdf |
      - 21.2.2.2.3. Deviations from standard atomic volumes as a quality measure for protein crystal structures (p. 509) | html | pdf |
  - 21.2.3. Validation of a model versus experimental data (pp. 509-517) | html | pdf |
    - 21.2.3.1. A systematic approach using the SFCHECK software (pp. 510-517) | html | pdf |
      - 21.2.3.1.1. Tasks performed by SFCHECK  (pp. 510-511) | html | pdf |
        21.2.3.1.1.1. Treatment of structure-factor data and scaling  (pp. 510-511) | html | pdf |
        21.2.3.1.1.2. Global agreement between the model and experimental data  (p. 511) | html | pdf |
        21.2.3.1.1.3. Estimations of errors in atomic positions  (p. 511) | html | pdf |
        21.2.3.1.1.4. Local agreement between the model and the experimental data  (p. 511) | html | pdf |
      - 21.2.3.1.2. Evaluation of individual structures (pp. 511-513) | html | pdf |
      - 21.2.3.1.3. Quality assessment based on surveys across structures  (pp. 513-517) | html | pdf |
        21.2.3.1.3.1. Assessing the quality of a structure as a whole  (pp. 513-514) | html | pdf |
        21.2.3.1.3.2. Assessing the quality in specific regions of a model  (pp. 514-517) | html | pdf |
  - 21.2.4. Atomic resolution structures (pp. 517-518) | html | pdf |
  - 21.2.5. Concluding remarks (p. 518) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 21.2.2.1. The Voronoi polyhedron (p. 509) | 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. 510) | 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 (p. 513) | 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. 514) | 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. 515-516) | html | pdf |
    - Fig. 21.2.3.4. Variation of global quality indicators with the nominal resolution (d spacing) of the crystallographic data (p. 517) | html | pdf |
    - Fig. 21.2.3.5. Pairwise correlations between the various local quality indicators computed by SFCHECK (p. 518) | html | pdf |
    - Fig. 21.2.3.6. B factors and density indices for residues across different structures (p. 519) | html | pdf |
  - Tables
    - Table 21.2.3.1. Parameters computed for the analysis of the structure-factor data (p. 511) | html | pdf |
    - Table 21.2.3.2. Estimation of errors in atomic coordinates (p. 512) | html | pdf |
    - Table 21.2.3.3. Parameters computed by SFCHECK to assess the quality of the model in specific regions (p. 512) | html | pdf |
- 21.3. Detection of errors in protein models (pp. 520-530) | html | pdf | chapter contents |
  O. Dym, D. Eisenberg and T. O. Yeates
  - 21.3.1. Motivation and introduction (p. 520) | html | pdf |
  - 21.3.2. Separating evaluation from refinement (p. 520) | html | pdf |
  - 21.3.3. Algorithms for the detection of errors in protein models and the types of errors they detect (pp. 520-521) | html | pdf |
    - 21.3.3.1. PROCHECK (pp. 520-521) | html | pdf |
    - 21.3.3.2. WHAT IF (p. 521) | html | pdf |
    - 21.3.3.3. VERIFY3D (p. 521) | html | pdf |
    - 21.3.3.4. ERRAT (p. 521) | html | pdf |
  - 21.3.4. Selection of database (p. 521) | html | pdf |
  - 21.3.5. Examples: detection of errors in structures (pp. 521-525) | html | pdf |
    - 21.3.5.1. Specific examples (pp. 521-524) | html | pdf |
    - 21.3.5.2. Survey of old and revised structures (pp. 524-525) | html | pdf |
  - 21.3.6. Summary (p. 525) | html | pdf |
  - 21.3.7. Availability of software (p. 525) | 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. 522) | 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. 523) | 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. 524) | 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. 524) | html | pdf |
    - Fig. 21.3.5.5. Evaluation of old and revised models in a database survey by ERRAT (p. 525) | html | pdf |

Molecular geometry and features
- 22.1. Protein surfaces and volumes: measurement and use (pp. 531-545) | html | pdf | chapter contents |
  M. Gerstein, F. M. Richards, M. S. Chapman and M. L. Connolly
  - 22.1.1. Protein geometry: volumes, areas and distances (pp. 531-539) | html | pdf |
    M. Gerstein and F. M. Richards
    - 22.1.1.1. Introduction (p. 531) | html | pdf |
    - 22.1.1.2. Definitions of protein volume (pp. 531-533) | html | pdf |
      - 22.1.1.2.1. Volume in terms of Voronoi polyhedra: overview (p. 531) | html | pdf |
      - 22.1.1.2.2. The basic Voronoi construction  (pp. 531-532) | html | pdf |
        22.1.1.2.2.1. Integrating on a grid  (pp. 531-532) | html | pdf |
        22.1.1.2.2.2. Finding polyhedron vertices  (p. 532) | html | pdf |
        22.1.1.2.2.3. Collecting vertices and calculating volumes   (p. 532) | html | pdf |
      - 22.1.1.2.3. Adapting Voronoi polyhedra to proteins  (pp. 532-533) | html | pdf |
        22.1.1.2.3.1. Method B and a simplification of it: the ratio method  (pp. 532-533) | html | pdf |
        22.1.1.2.3.2. Vertex error  (p. 533) | html | pdf |
        22.1.1.2.3.3. `Chopping-down' method of finding vertices  (p. 533) | html | pdf |
        22.1.1.2.3.4. Radical-plane method  (p. 533) | html | pdf |
      - 22.1.1.2.4. Delaunay triangulation (p. 533) | html | pdf |
    - 22.1.1.3. Definitions of protein surface (pp. 534-536) | html | pdf |
      - 22.1.1.3.1. The problem of the protein surface (p. 534) | html | pdf |
      - 22.1.1.3.2. Definitions of surface in terms of Voronoi polyhedra (the convex hull) (p. 534) | html | pdf |
      - 22.1.1.3.3. Definitions of surface in terms of a probe sphere  (pp. 534-536) | html | pdf |
        22.1.1.3.3.1. van der Waals surface (VDWS)  (p. 535) | html | pdf |
        22.1.1.3.3.2. Solvent-accessible surface (SAS)  (p. 535) | html | pdf |
        22.1.1.3.3.3. Molecular surface as the sum of the contact and re-entrant surfaces (MS = CS + RS)  (p. 535) | html | pdf |
        22.1.1.3.3.4. Further points  (pp. 535-536) | html | pdf |
    - 22.1.1.4. Definitions of atomic radii (pp. 536-537) | html | pdf |
      - 22.1.1.4.1. van der Waals radii (pp. 536-537) | html | pdf |
      - 22.1.1.4.2. The probe radius (p. 537) | html | pdf |
    - 22.1.1.5. Application of geometry calculations: the measurement of packing (pp. 537-539) | html | pdf |
      - 22.1.1.5.1. Using volume to measure packing efficiency (pp. 537-538) | html | pdf |
      - 22.1.1.5.2. The tight packing of the protein core (p. 538) | html | pdf |
      - 22.1.1.5.3. Looser packing on the surface (pp. 538-539) | html | pdf |
  - 22.1.2. Molecular surfaces: calculations, uses and representations (pp. 539-545) | html | pdf |
    M. S. Chapman and M. L. Connolly
    - 22.1.2.1. Introduction (pp. 539-540) | html | pdf |
      - 22.1.2.1.1. Uses of surface-area calculations (p. 539) | html | pdf |
      - 22.1.2.1.2. Molecular, solvent-accessible and occluded surface areas (pp. 539-540) | html | pdf |
      - 22.1.2.1.3. Hydration surface (p. 540) | html | pdf |
      - 22.1.2.1.4. Hydrophobicity (p. 540) | html | pdf |
    - 22.1.2.2. Calculation of surface area and energies of interaction (pp. 540-541) | html | pdf |
      - 22.1.2.2.1. Introduction (pp. 540-541) | html | pdf |
      - 22.1.2.2.2. Lee & Richards planar slices (p. 541) | html | pdf |
      - 22.1.2.2.3. Connolly dot surface algorithm (p. 541) | html | pdf |
      - 22.1.2.2.4. Marching-cube algorithm (p. 541) | html | pdf |
      - 22.1.2.2.5. Complete and connected rolling algorithms (p. 541) | html | pdf |
      - 22.1.2.2.6. Analytic surface calculations and the Gauss–Bonnet theorem (p. 541) | html | pdf |
      - 22.1.2.2.7. Approximations to the surface (p. 541) | html | pdf |
      - 22.1.2.2.8. Extended atoms account for missing hydrogen atoms (p. 541) | html | pdf |
    - 22.1.2.3. Estimation of binding energies (pp. 542-543) | html | pdf |
      - 22.1.2.3.1. Hydrophobicity (p. 542) | html | pdf |
      - 22.1.2.3.2. Estimates of binding energies (p. 542) | html | pdf |
      - 22.1.2.3.3. Other non-graphical interpretive methods using surface area (pp. 542-543) | html | pdf |
    - 22.1.2.4. Graphical representations of shape and properties (pp. 543-545) | html | pdf |
      - 22.1.2.4.1. Realistic  (pp. 543-544) | html | pdf |
        22.1.2.4.1.1. Shaded backbone  (p. 543) | html | pdf |
        22.1.2.4.1.2. `Connolly' and solid polyhedral surfaces  (p. 543) | html | pdf |
        22.1.2.4.1.3. Photorealistic rendering  (p. 543) | html | pdf |
        22.1.2.4.1.4. GRASP surfaces  (pp. 543-544) | html | pdf |
        22.1.2.4.1.5. Implementations in popular packages  (p. 544) | html | pdf |
      - 22.1.2.4.2. Schematic and two-dimensional representations such as `roadmap' (pp. 544-545) | html | pdf |
    - 22.1.2.5. Conclusion (p. 545) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.1.1.1. The Voronoi construction in two and three dimensions (p. 531) | html | pdf |
    - Fig. 22.1.1.2. Labelling parts of Voronoi polyhedra (p. 532) | html | pdf |
    - Fig. 22.1.1.3. Positioning of the dividing plane (p. 532) | html | pdf |
    - Fig. 22.1.1.4. The `chopping-down' method of polyhedra construction (p. 533) | html | pdf |
    - Fig. 22.1.1.5. Delaunay triangulation and its relation to the Voronoi construction (p. 534) | html | pdf |
    - Fig. 22.1.1.6. The problem of the protein surface (p. 534) | html | pdf |
    - Fig. 22.1.1.7. Definitions of the protein surface (p. 535) | html | pdf |
    - Fig. 22.1.1.8. Packing efficiency (p. 537) | html | pdf |
    - Fig. 22.1.2.1. Surfaces in a plane cut through a hypothetical molecule (p. 540) | html | pdf |
    - Fig. 22.1.2.2. GRASP example (p. 543) | html | pdf |
    - Fig. 22.1.2.3. (a) Solvent-accessible surface topology of a rhinovirus 14–drug complex (Kim et al (p. 544) | html | pdf |
    - Fig. 22.1.2.4. Different projections illustrated with lysozyme (p. 545) | html | pdf |
  - Tables
    - Table 22.1.1.1. Standard atomic radii (Å) (p. 536) | html | pdf |
    - Table 22.1.1.2. Probe radii and their relation to surface definition (p. 537) | html | pdf |
    - Table 22.1.1.3. Standard residue volumes (p. 538) | html | pdf |
    - Table 22.1.1.4. Standard atomic volumes (p. 539) | html | pdf |
    - Table 22.1.2.1. The atomic solvation parameters of Eisenberg & McLachlan (1986) (p. 542) | html | pdf |
- 22.2. Hydrogen bonding in biological macromolecules (pp. 546-552) | html | pdf | chapter contents |
  E. N. Baker
  - 22.2.1. Introduction (p. 546) | html | pdf |
  - 22.2.2. Nature of the hydrogen bond (p. 546) | html | pdf |
  - 22.2.3. Hydrogen-bonding groups (pp. 546-547) | html | pdf |
    - 22.2.3.1. Proteins (p. 546) | html | pdf |
    - 22.2.3.2. Nucleic acids (pp. 546-547) | html | pdf |
  - 22.2.4. Identification of hydrogen bonds: geometrical considerations (p. 547) | html | pdf |
  - 22.2.5. Hydrogen bonding in proteins (pp. 547-551) | html | pdf |
    - 22.2.5.1. Contribution to protein folding and stability (pp. 547-548) | html | pdf |
    - 22.2.5.2. Saturation of hydrogen-bond potential (p. 548) | html | pdf |
    - 22.2.5.3. Secondary structures (pp. 548-549) | html | pdf |
      - 22.2.5.3.1. Helices (p. 548) | html | pdf |
      - 22.2.5.3.2. β-sheets (pp. 548-549) | html | pdf |
      - 22.2.5.3.3. Turns (p. 549) | html | pdf |
      - 22.2.5.3.4. Aspects of in-plane geometry (p. 549) | html | pdf |
    - 22.2.5.4. Side-chain hydrogen bonding (pp. 549-550) | html | pdf |
    - 22.2.5.5. Hydrogen bonds with water molecules (pp. 550-551) | html | pdf |
  - 22.2.6. Hydrogen bonding in nucleic acids (p. 551) | html | pdf |
    - 22.2.6.1. DNA (p. 551) | html | pdf |
    - 22.2.6.2. RNA (p. 551) | html | pdf |
  - 22.2.7. Non-conventional hydrogen bonds (pp. 551-552) | html | pdf |
    - 22.2.7.1. C—H···O hydrogen bonds (pp. 551-552) | html | pdf |
    - 22.2.7.2. Hydrogen bonds involving sulfur atoms (p. 552) | html | pdf |
    - 22.2.7.3. Amino-aromatic hydrogen bonding (p. 552) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.2.2.1. Hydrogen-bonding configurations (p. 546) | html | pdf |
    - Fig. 22.2.3.1. Hydrogen-bonding potential of protein functional groups (p. 547) | html | pdf |
    - Fig. 22.2.3.2. Hydrogen-bonding potential of nucleic acid bases guanine (G), adenine (A), cytosine (C) and thymine (T) in their normal canonical forms. (p. 547) | html | pdf |
    - Fig. 22.2.4.1. Suggested criteria for identifying likely hydrogen bonds (p. 547) | html | pdf |
    - Fig. 22.2.5.1. 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. 549) | html | pdf |
    - Fig. 22.2.5.2. Schematic representations of common classes of side-chain–main-chain hydrogen bonds (a) in turns and (b) at helix N-termini (p. 549) | html | pdf |
    - Fig. 22.2.5.3. Typical scatter plots showing the distribution of hydrogen-bonding partners around protein side chains, shown for (a) Asn or Gln and (b) Tyr (p. 550) | html | pdf |
    - Fig. 22.2.6.1. Hydrogen-bonding interactions in RNA tertiary structure (p. 551) | html | pdf |
- 22.3. Electrostatic interactions in proteins (pp. 553-557) | html | pdf | chapter contents |
  K. A. Sharp
  - 22.3.1. Introduction (p. 553) | html | pdf |
  - 22.3.2. Theory (pp. 553-555) | html | pdf |
    - 22.3.2.1. The response of the system to electrostatic fields (pp. 553-554) | html | pdf |
    - 22.3.2.2. Dependence of the potential on the charge distribution (p. 554) | html | pdf |
    - 22.3.2.3. The concepts of screening, reaction potentials, solvation, dielectric, polarity and polarizability (pp. 554-555) | html | pdf |
    - 22.3.2.4. Calculation of energies and forces (p. 555) | html | pdf |
    - 22.3.2.5. Numerical methods (p. 555) | html | pdf |
  - 22.3.3. Applications (pp. 555-556) | html | pdf |
    - 22.3.3.1. Electrostatic potential distributions (p. 555) | html | pdf |
    - 22.3.3.2. Charge-transfer equilibria (pp. 555-556) | html | pdf |
    - 22.3.3.3. Electrostatic contributions to binding energy (p. 556) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.3.3.1. (a) The proteolytic enzyme thrombin (yellow backbone worm) complexed with an inhibitor, hirudin (blue backbone worm) (p. 557) | html | pdf |
- 22.4. The relevance of the Cambridge Structural Database in protein crystallography (pp. 558-574) | html | pdf | chapter contents |
  F. H. Allen, J. C. Cole and M. L. Verdonk
  - 22.4.1. Introduction (p. 558) | html | pdf |
  - 22.4.2. The CSD and the PDB: data acquisition and data quality (pp. 558-559) | html | pdf |
    - 22.4.2.1. Statistical inferences (p. 558) | html | pdf |
    - 22.4.2.2. Data acquisition and completeness (pp. 558-559) | html | pdf |
    - 22.4.2.3. Standard formats: CIF and mmCIF (p. 559) | html | pdf |
    - 22.4.2.4. Structure validation (p. 559) | html | pdf |
  - 22.4.3. Structural knowledge from the CSD (pp. 559-560) | html | pdf |
    - 22.4.3.1. The CSD software system (p. 559) | html | pdf |
    - 22.4.3.2. CSD structures and substructures of relevance to protein studies (pp. 559-560) | html | pdf |
    - 22.4.3.3. Geometrical parameters of relevance to protein studies (p. 560) | html | pdf |
  - 22.4.4. Intramolecular geometry (pp. 560-562) | html | pdf |
    - 22.4.4.1. Mean molecular dimensions (p. 560) | html | pdf |
    - 22.4.4.2. Conformational information (pp. 560-561) | html | pdf |
    - 22.4.4.3. Crystallographic conformations and energies (p. 561) | html | pdf |
    - 22.4.4.4. Conformational libraries (pp. 561-562) | html | pdf |
    - 22.4.4.5. Metal coordination geometry (p. 562) | html | pdf |
  - 22.4.5. Intermolecular data (pp. 562-567) | html | pdf |
    - 22.4.5.1. van der Waals radii (p. 562) | html | pdf |
    - 22.4.5.2. Hydrogen-bond geometry and directionality (p. 562) | html | pdf |
    - 22.4.5.3. C—H···X hydrogen bonds (p. 563) | html | pdf |
    - 22.4.5.4. O—H···π and N—H···π hydrogen bonds (pp. 563-564) | html | pdf |
    - 22.4.5.5. Other non-covalent interactions (p. 564) | html | pdf |
    - 22.4.5.6. Intermolecular motif formation in small-molecule crystal structures (p. 564) | html | pdf |
    - 22.4.5.7. The answer `no' (pp. 564-565) | html | pdf |
    - 22.4.5.8. IsoStar: a library of non-bonded interactions (p. 565) | html | pdf |
    - 22.4.5.9. Protein–ligand binding (pp. 565-566) | html | pdf |
    - 22.4.5.10. Modelling applications that use CSD data (pp. 566-567) | html | pdf |
  - 22.4.6. Conclusion (p. 567) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 22.4.2.1. (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. 558) | html | pdf |
    - Fig. 22.4.4.1. Distribution of torsion angles in C(sp³)—S—S—C(sp³) substructures located in the CSD (p. 561) | html | pdf |
    - Fig. 22.4.5.1. 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. 563) | html | pdf |
    - Fig. 22.4.5.2. Distribution of O—H donors around ether oxygen acceptors (CSD data from the IsoStar library, see text) (p. 563) | html | pdf |
    - Fig. 22.4.5.3. Distribution of oxygen atoms around C(aromatic)—I (CSD data from the IsoStar library, see text) (p. 564) | html | pdf |
    - Fig. 22.4.5.4. Pairwise comparison of intermolecular-interaction density maps from the CSD and the PDB (p. 566) | html | pdf |
  - Tables
    - Table 22.4.3.1. Summary of amino-acid and peptide structures available in the CSD (April 1998, 181 309 entries) (p. 559) | html | pdf |
    - Table 22.4.3.2. CSD entry statistics for selected metal-containing structures (p. 560) | html | pdf |
    - Table 22.4.5.1. Residual densities for carboxylic acid groups (p. 566) | html | pdf |

Structural analysis and classification
- 23.1. Protein folds and motifs: representation, comparison and classification (pp. 575-578) | html | pdf | chapter contents |
  C. Orengo, J. Thornton, L. Holm and C. Sander
  - 23.1.1. Protein-fold classification (pp. 575-576) | html | pdf |
    C. Orengo and J. Thornton
  - 23.1.2. Locating domains in 3D structures (pp. 577-578) | html | pdf |
    L. Holm and C. Sander
    - 23.1.2.1. Introduction (p. 577) | html | pdf |
    - 23.1.2.2. Compactness (p. 577) | html | pdf |
    - 23.1.2.3. Recurrence (pp. 577-578) | html | pdf |
    - 23.1.2.4. Conclusion (p. 578) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.1.1.1. Schematic representation of the (C)lass, (A)rchitecture and (T)opology/fold levels in the CATH database (p. 575) | html | pdf |
    - Fig. 23.1.1.2. `CATHerine wheel' plot showing the distribution of non-homologous structures (p. 576) | html | pdf |
    - Fig. 23.1.2.1. The structure of diphtheria toxin (Bennett & Eisenberg, 1994) beautifully illustrates domains as structural, functional and evolutionary units (p. 577) | html | pdf |
- 23.2. Protein–ligand interactions (pp. 579-587) | html | pdf | chapter contents |
  A. E. Hodel and F. A. Quiocho
  - 23.2.1. Introduction (p. 579) | html | pdf |
  - 23.2.2. Protein–carbohydrate interactions (pp. 579-580) | html | pdf |
    - 23.2.2.1. Carbohydrate recognition at the atomic level (pp. 579-580) | html | pdf |
  - 23.2.3. Metals (pp. 580-581) | html | pdf |
    - 23.2.3.1. Metals important in protein function and structure (pp. 580-581) | html | pdf |
  - 23.2.4. Protein–nucleic acid interactions (pp. 581-585) | html | pdf |
    - 23.2.4.1. The DNA double helix (pp. 581-583) | html | pdf |
    - 23.2.4.2. Single-stranded sequence-nonspecific DNA–protein interactions (p. 583) | html | pdf |
    - 23.2.4.3. RNA (p. 583) | html | pdf |
    - 23.2.4.4. Transfer RNA (pp. 583-584) | html | pdf |
    - 23.2.4.5. Stem loops (p. 584) | html | pdf |
    - 23.2.4.6. Single-stranded sequence-nonspecific RNA–protein interactions (p. 584) | html | pdf |
    - 23.2.4.7. The recognition of alkylated bases (pp. 584-585) | html | pdf |
  - 23.2.5. Phosphate and sulfate (pp. 585-587) | html | pdf |
    - 23.2.5.1. Dominant role of local dipoles in stabilization of isolated charges (p. 586) | html | pdf |
    - 23.2.5.2. Short hydrogen bonds (p. 586) | html | pdf |
    - 23.2.5.3. Non-complementary negative electrostatic surface potential of protein sites specific for anions (pp. 586-587) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.2.2.1. The atomic recognition of carbohydrates by a protein (p. 579) | html | pdf |
    - Fig. 23.2.4.1. 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. 581) | html | pdf |
    - Fig. 23.2.4.2. (a) A space-filling model of B-DNA showing the relative accessibility of the major and minor grooves (p. 582) | html | pdf |
    - Fig. 23.2.4.3. A comparison of the orientations of α-helices bound in the major groove (p. 582) | html | pdf |
    - Fig. 23.2.4.4. The sequence-nonspecific recognition of single-stranded nucleic acid (p. 583) | html | pdf |
    - Fig. 23.2.4.5. The specific recognition of the messenger RNA 7-methylguanosine cap (p. 584) | html | pdf |
    - Fig. 23.2.5.1. 12 hydrogen-bonding interactions between the phosphate-binding protein (PBP) and phosphate (p. 585) | html | pdf |
    - Fig. 23.2.5.2. Seven hydrogen-bonding interactions between the sulfate-binding protein (SBP) and sulfate (p. 586) | html | pdf |
    - Fig. 23.2.5.3. Electrostatic surface potential of (a) the phosphate-binding protein and (b) flavodoxin (p. 587) | html | pdf |
  - Tables
    - Table 23.2.3.1. Metal ions associated with proteins (p. 580) | html | pdf |
- 23.3. Nucleic acids (pp. 588-622) | html | pdf | chapter contents |
  R. E. Dickerson
  - 23.3.1. Introduction (p. 588) | html | pdf |
  - 23.3.2. Helix parameters (pp. 588-596) | html | pdf |
    - 23.3.2.1. Backbone geometry (p. 588) | html | pdf |
    - 23.3.2.2. Sugar ring conformations (pp. 588-589) | html | pdf |
    - 23.3.2.3. Base pairing (pp. 589-592) | html | pdf |
    - 23.3.2.4. Helix parameters (pp. 592-593) | html | pdf |
    - 23.3.2.5. Syn/anti glycosyl bond geometry (p. 596) | html | pdf |
  - 23.3.3. Comparison of A, B and Z helices (pp. 596-602) | html | pdf |
    - 23.3.3.1. x displacement and groove depth (pp. 596-597) | html | pdf |
    - 23.3.3.2. Glycosyl bond geometry (p. 597) | html | pdf |
    - 23.3.3.3. Sugar ring conformations (pp. 597-598) | html | pdf |
    - 23.3.3.4. Helical twist and rise, and propeller twist (pp. 598-600) | html | pdf |
    - 23.3.3.5. Allowable RNA helices (p. 600) | html | pdf |
    - 23.3.3.6. Biological applications of A, B and Z helices (pp. 600-601) | html | pdf |
    - 23.3.3.7. `Watson–Crick' Z-DNA (pp. 601-602) | html | pdf |
  - 23.3.4. Sequence–structure relationships in B-DNA (pp. 602-609) | html | pdf |
    - 23.3.4.1. Sequence-dependent deformability (pp. 603-607) | html | pdf |
      - 23.3.4.1.1. Minor groove width (p. 603) | html | pdf |
      - 23.3.4.1.2. Helix bending (pp. 603-607) | html | pdf |
    - 23.3.4.2. A-tract bending (pp. 607-609) | html | pdf |
  - 23.3.5. Summary (p. 609) | html | pdf |
  - Appendix 23.3.1. X-ray analyses of A, B and Z helices (pp. 609-622) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.3.1.1. `Hot wire' painting of A-DNA by Irving Geis (p. 589) | html | pdf |
    - Fig. 23.3.1.2. Infinite A-DNA helix (p. 590) | html | pdf |
    - Fig. 23.3.1.3. Infinite B-DNA helix (p. 590) | html | pdf |
    - Fig. 23.3.1.4. Infinite Z-DNA helix (p. 591) | html | pdf |
    - Fig. 23.3.2.1. Unrolled schematic of A- or B-DNA, viewed into the minor groove (p. 591) | html | pdf |
    - Fig. 23.3.2.2. Sugar–phosphate backbone of RNA and DNA polynucleotides (p. 592) | html | pdf |
    - Fig. 23.3.2.3. Definition of torsion angles (p. 592) | html | pdf |
    - Fig. 23.3.2.4. The three most common furanose ring geometries (p. 592) | html | pdf |
    - Fig. 23.3.2.5. Potential plot of all furanose ring conformations (p. 593) | html | pdf |
    - Fig. 23.3.2.6. Plot of observed sugar conformations in 296 nucleotides of A-DNA (crosses) and 280 of B-DNA (open circles) (p. 594) | html | pdf |
    - Fig. 23.3.2.7. A·T and G·C base pairs with minor groove edge below and major groove edge above (p. 594) | html | pdf |
    - Fig. 23.3.2.8. Alternative purines and pyrimidines, and possible base pairings (p. 594) | html | pdf |
    - Fig. 23.3.2.9. 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. 594) | html | pdf |
    - Fig. 23.3.2.10. Definitions of local reference axes (x, y, z) at the first two base pairs of an n-base-pair double helix (p. 595) | html | pdf |
    - Fig. 23.3.2.11. Local helix parameters involving rotations (p. 595) | html | pdf |
    - Fig. 23.3.2.12. Local helix parameters involving translations (p. 595) | html | pdf |
    - Fig. 23.3.2.13. Syn versus anti orientation about the glycosyl bond connecting sugar and base (p. 595) | html | pdf |
    - Fig. 23.3.3.1. The A-DNA stereo pair drawing from which Fig. 23.3.1.2 was derived (p. 596) | html | pdf |
    - Fig. 23.3.3.2. The B-DNA stereo pair drawing from which Fig. 23.3.1.3 was derived (p. 597) | html | pdf |
    - Fig. 23.3.3.3. The Z-DNA stereo pair drawing from which Fig. 23.3.1.4 was derived (p. 598) | html | pdf |
    - Fig. 23.3.3.4. Glycosyl conformation and chain sense (p. 599) | html | pdf |
    - Fig. 23.3.3.5. The role of the C2′-OH in RNA helix geometry (p. 600) | html | pdf |
    - Fig. 23.3.3.6. Interconversion of a B to a Z helix (p. 601) | html | pdf |
    - Fig. 23.3.3.7. Z(WC)-DNA, or `Watson–Crick Z-DNA' (p. 601) | html | pdf |
    - Fig. 23.3.4.1. Structure of C-A-A-A-G-A-A-A-A-G (p. 602) | html | pdf |
    - Fig. 23.3.4.2. Relationship between minor groove width and propeller twist (p. 602) | html | pdf |
    - Fig. 23.3.4.3. Structure of the 1:1 complex of netropsin with C-G-C-G-A-A-T-T-C-G-C-G (p. 603) | html | pdf |
    - Fig. 23.3.4.4. Structure of the 2:1 complex of a di-imidazole lexitropsin with C-A-T-G-G-C-C-A-T-G (p. 604) | html | pdf |
    - Fig. 23.3.4.5. DNA duplex (red and blue strands) looped around IHF or integration host factor (p. 604) | html | pdf |
    - Fig. 23.3.4.6. Roll-angle plots for sequence-specific DNA–protein complexes with lacI (top) and purR (bottom) (p. 606) | html | pdf |
    - Fig. 23.3.4.7. Bending via roll at T-A steps in TBP or the TATA-binding protein (top) and in γδ-resolvase (bottom) (p. 606) | html | pdf |
    - Fig. 23.3.4.8. Representative base-pair steps from B-DNA single-crystal X-ray analyses (p. 607) | html | pdf |
    - Fig. 23.3.4.9. Slide versus roll plots for six of the ten possible base-pair steps (p. 608) | html | pdf |
  - Tables
    - Table 23.3.2.1. Average torsion-angle properties of A-, B- and Z-DNA (°) (p. 593) | html | pdf |
    - Table 23.3.2.2. Sugar ring conformations, pseudorotation angles and torsion angle δ (p. 593) | html | pdf |
    - Table 23.3.3.1. Comparison of structures of A, B and Z helices (p. 599) | html | pdf |
    - Table 23.3.4.1. Sequence-dependent differential deformability in B-DNA. I. The Major Canon (p. 605) | html | pdf |
    - Table 23.3.4.2. Sequence-dependent differential deformability in B-DNA. II. The Minor Canon (p. 606) | html | pdf |
    - Table A23.3.1.1. X-ray analyses of A helices, DNA and RNA (pp. 609-613) | html | pdf |
    - Table A23.3.1.2. X-ray analyses of B-DNA helices and their complexes with minor-groove-binding drug molecules (pp. 613-619) | html | pdf |
    - Table A23.3.1.3. X-ray analyses of Z helices (pp. 619-622) | html | pdf |
- 23.4. Solvent structure (pp. 623-647) | html | pdf | chapter contents |
  C. Mattos and D. Ringe
  - 23.4.1. Introduction (pp. 623-624) | html | pdf |
  - 23.4.2. Determination of water molecules (pp. 624-625) | html | pdf |
  - 23.4.3. Structural features of protein–water interactions derived from database analysis (pp. 625-630) | html | pdf |
    - 23.4.3.1. Water distribution around the individual amino-acid residues in protein structures (pp. 625-627) | html | pdf |
    - 23.4.3.2. The effect of secondary structure on protein–water interactions (pp. 627-629) | html | pdf |
    - 23.4.3.3. The effect of tertiary structure on protein–water interactions (p. 629) | html | pdf |
    - 23.4.3.4. Water mediation of protein–ligand interactions (pp. 629-630) | html | pdf |
  - 23.4.4. Water structure in groups of well studied proteins (pp. 630-637) | html | pdf |
    - 23.4.4.1. Crystal structures of homologous proteins (pp. 630-631) | html | pdf |
      - 23.4.4.1.1. Serine proteases of the trypsin family (pp. 630-631) | html | pdf |
      - 23.4.4.1.2. Legume lectin family (p. 631) | html | pdf |
    - 23.4.4.2. Multiple crystal structures of the same protein (pp. 631-636) | html | pdf |
      - 23.4.4.2.1. Elastase (pp. 632-634) | html | pdf |
      - 23.4.4.2.2. T4 lysozyme (pp. 634-635) | html | pdf |
      - 23.4.4.2.3. Ribonuclease T1 (p. 635) | html | pdf |
      - 23.4.4.2.4. Ribonuclease A (pp. 635-636) | html | pdf |
      - 23.4.4.2.5. Protein kinase A (p. 636) | html | pdf |
    - 23.4.4.3. Summary (pp. 636-637) | html | pdf |
  - 23.4.5. The classic models: small proteins with high-resolution crystal structures (pp. 637-638) | html | pdf |
    - 23.4.5.1. Crambin (p. 637) | html | pdf |
    - 23.4.5.2. Bovine pancreatic trypsin inhibitor (p. 637) | html | pdf |
    - 23.4.5.3. Summary (pp. 637-638) | html | pdf |
  - 23.4.6. Water molecules as mediators of complex formation (pp. 638-640) | html | pdf |
    - 23.4.6.1. Antigen–antibody association (p. 638) | html | pdf |
    - 23.4.6.2. Protein–DNA recognition (pp. 638-639) | html | pdf |
    - 23.4.6.3. Cooperativity in dimeric haemoglobin (pp. 639-640) | html | pdf |
    - 23.4.6.4. Summary (p. 640) | html | pdf |
  - 23.4.7. Conclusions and future perspectives (p. 640) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 23.4.3.1. Distribution of water-molecule sites (p. 626) | html | pdf |
    - Fig. 23.4.3.2. Distribution of atomic hydration values (p. 627) | html | pdf |
    - Fig. 23.4.3.3. Diagram of edge (W1), end (W2) and middle (W3) categories of interactions of water molecules with main-chain atoms in antiparallel β-sheets (p. 628) | html | pdf |
    - Fig. 23.4.3.4. Diagram of the hydrogen bonds in the α-helical structure in actinidin (p. 628) | html | pdf |
    - Fig. 23.4.3.5. Schematic illustration of water molecules bound in different types of grooves between protein and ligand (p. 630) | html | pdf |
    - Fig. 23.4.4.1. Stereoview of the set of 21 highly conserved buried waters in eukaryotic serine proteases (p. 631) | html | pdf |
    - Fig. 23.4.4.2. View of the 33 conserved hydration sites in the lentil lectin crystal structures superimposed on the backbone of the lentil lectin dimer (p. 631) | html | pdf |
    - Fig. 23.4.4.3. 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. 632) | html | pdf |
    - Fig. 23.4.4.4. Crystal structure of porcine pancreatic elastase represented as a ribbon diagram using MOLSCRIPT (Kraulis, 1991) (p. 633) | html | pdf |
    - Fig. 23.4.4.5. Elastase structure represented as in Fig. 23.4.4.4. The crystallographic water molecules found in channels in 11 superimposed elastase structures solved in a variety of solvents are shown in yellow (p. 633) | html | pdf |
    - Fig. 23.4.4.6. Elastase structure represented as in Fig. 23.4.4.4. The crystallographic water molecules involved in crystal contacts in 11 superimposed elastase structures solved in a variety of solvents are shown in green (p. 634) | html | pdf |
    - Fig. 23.4.4.7. Elastase structure represented as in Fig. 23.4.4.4. The surface crystallographic water molecules found in 11 superimposed elastase structures solved in a variety of solvents are shown in blue (p. 634) | html | pdf |
    - Fig. 23.4.4.8. Elastase structure represented as in Fig. 23.4.4.4. The 1661 water molecules found in 11 superimposed elastase structures of elastase are colour-coded as in Figs. 23.4.4.4 –23.4.4.7 (p. 634) | html | pdf |
    - Fig. 23.4.4.9. Distribution of solvent-binding sites in 18 mutant T4 lysozymes from ten refined crystal structures (p. 635) | html | pdf |
    - Fig. 23.4.4.10. Three-dimensional structure of RNase T1 (p. 636) | html | pdf |
    - Fig. 23.4.4.11. Overall structure of RNase A (p. 636) | html | pdf |
    - Fig. 23.4.5.1. van der Waals surface diagram of the water pentagons A, C, D and E in crambin viewed in the negative a direction (p. 637) | html | pdf |
    - Fig. 23.4.6.1. Scapharca HbI interface water molecules (p. 639) | html | pdf |
  - Tables
    - Table 23.4.3.1. Specific hydrophilicity values for protein atoms (p. 627) | html | pdf |
    - Table 23.4.4.1. Multiple-solvent crystal structures of elastase (p. 632) | html | pdf |

Crystallographic databases
- 24.1. The Protein Data Bank at Brookhaven (pp. 649-656) | html | pdf | chapter contents |
  J. L. Sussman, D. Lin, J. Jiang, N. O. Manning, J. Prilusky and E. E. Abola
  - 24.1.1. Introduction (p. 649) | html | pdf |
  - 24.1.2. Background and significance of the resource (pp. 649-650) | html | pdf |
    - 24.1.2.1. The early years: 1971–1988 (p. 649) | html | pdf |
    - 24.1.2.2. The data explosion: 1989–1992 (pp. 649-650) | html | pdf |
  - 24.1.3. The PDB in 1999 (pp. 650-654) | html | pdf |
    - 24.1.3.1. Contents and access to the PDB archives (pp. 650-653) | html | pdf |
    - 24.1.3.2. Data deposition (pp. 653-654) | html | pdf |
  - 24.1.4. Examples of the impact of the PDB (pp. 654-656) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.1.2.1. PDB coordinate entries available per year (p. 650) | html | pdf |
    - Fig. 24.1.3.1. 3DB Browser as a tool to visualize recently published structures (p. 651) | html | pdf |
    - Fig. 24.1.3.2. Schematic diagram of the PDB WWW mirror system (p. 652) | html | pdf |
    - Fig. 24.1.3.3. PDB WWW-based submission via AutoDep (p. 653) | html | pdf |
    - Fig. 24.1.4.1. Crystal structure of a complex of a peptide from an HIV-1 protein bound to the human class I MHC molecule HLA-A2 (p. 655) | html | pdf |
    - Fig. 24.1.4.2. Crystal structure, at 3 Å resolution, of the E. coli catabolite gene activator protein (CAP) complexed with a 30-base-pair DNA sequence (p. 655) | html | pdf |
  - Tables
    - Table 24.1.3.1. PDB archive contents as of May 1999 (p. 650) | html | pdf |
    - Table 24.1.3.2. PDB mirror sites as of May 1999 (p. 650) | html | pdf |
    - Table 24.1.3.3. 3DB Browser's linked external data sources (p. 652) | html | pdf |
    - Table 24.1.3.4. Search fields of 3DB Browser (p. 652) | html | pdf |
    - Table 24.1.3.5. Search engines used by 3DB Browser (p. 652) | html | pdf |
    - Table 24.1.3.6. PDB data-validation checks (p. 653) | html | pdf |
    - Table 24.1.3.7. PDB structure-factor submissions, as of November 1998 (p. 654) | html | pdf |
    - Table 24.1.4.1. Key web sites related to three-dimensional structures of biological macromolecules (p. 655) | html | pdf |
- 24.2. The Nucleic Acid Database (NDB) (pp. 657-662) | html | pdf | chapter contents |
  H. M. Berman, Z. Feng, B. Schneider, J. Westbrook and C. Zardecki
  - 24.2.1. Introduction (p. 657) | html | pdf |
  - 24.2.2. Information content of the NDB (p. 657) | html | pdf |
  - 24.2.3. Data processing (pp. 657-659) | html | pdf |
  - 24.2.4. The database (p. 659) | html | pdf |
  - 24.2.5. Data distribution (pp. 659-662) | html | pdf |
    - 24.2.5.1. Archives (p. 659) | html | pdf |
    - 24.2.5.2. Atlas (p. 659) | html | pdf |
    - 24.2.5.3. NDB searches (pp. 659-662) | html | pdf |
    - 24.2.5.4. Mirror sites (p. 662) | html | pdf |
  - 24.2.6. Outreach (p. 662) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.2.3.1. Flow chart showing the organization of the Nucleic Acid Database Project (p. 657) | html | pdf |
    - Fig. 24.2.4.1. Flow chart demonstrating the two steps involved in searching the NDB: structure selection and report generation (p. 658) | html | pdf |
    - Fig. 24.2.4.2. Examples of reports generated from the NDB about torsion angles (p. 658) | html | pdf |
    - Fig. 24.2.5.1. NDB Atlas page for URX035 (p. 660) | html | pdf |
    - Fig. 24.2.5.2. Examples of quick reports (p. 661) | html | pdf |
  - Tables
    - Table 24.2.2.1. The information content of the NDB (p. 657) | html | pdf |
    - Table 24.2.5.1. Quick reports available from the NDB (p. 659) | html | pdf |
- 24.3. The Cambridge Structural Database (CSD) (pp. 663-668) | html | pdf | chapter contents |
  F. H. Allen and V. J. Hoy
  - 24.3.1. Introduction and historical perspective (p. 663) | html | pdf |
  - 24.3.2. Information content of the CSD (pp. 663-665) | html | pdf |
    - 24.3.2.1. Acquisition of information (p. 663) | html | pdf |
    - 24.3.2.2. Data organization (pp. 663-664) | html | pdf |
    - 24.3.2.3. 1D bibliographic and chemical data (p. 664) | html | pdf |
    - 24.3.2.4. 2D chemical connectivity data (p. 664) | html | pdf |
    - 24.3.2.5. 3D crystal structure data (p. 664) | html | pdf |
    - 24.3.2.6. Derived data and bit-encoded information (pp. 664-665) | html | pdf |
    - 24.3.2.7. Data validation (p. 665) | html | pdf |
    - 24.3.2.8. The CSD-Use database (p. 665) | html | pdf |
  - 24.3.3. The CSD software system (pp. 665-666) | html | pdf |
    - 24.3.3.1. Overview (p. 665) | html | pdf |
    - 24.3.3.2. PreQuest (p. 665) | html | pdf |
    - 24.3.3.3. Searching the CSD: Quest3D and ConQuest (p. 665) | html | pdf |
    - 24.3.3.4. Quest3D (pp. 665-666) | html | pdf |
    - 24.3.3.5. ConQuest (p. 666) | html | pdf |
    - 24.3.3.6. Vista (p. 666) | html | pdf |
    - 24.3.3.7. Pluto (p. 666) | html | pdf |
    - 24.3.3.8. Use of the CSD software system: an example (p. 666) | html | pdf |
  - 24.3.4. Knowledge engineering from the CSD (pp. 667-668) | html | pdf |
    - 24.3.4.1. Databases versus knowledge bases (pp. 667-668) | html | pdf |
    - 24.3.4.2. IsoStar: a library of knowledge about intermolecular interactions (p. 668) | html | pdf |
  - 24.3.5. Accessing the CSD system and IsoStar (p. 668) | html | pdf |
    - 24.3.5.1. Release mechanisms (p. 668) | html | pdf |
    - 24.3.5.2. Information about the CCDC (p. 668) | html | pdf |
  - 24.3.6. Conclusion (p. 668) | html | pdf |
  - Figures
    - Fig. 24.3.1.1. Growth of the CSD since 1970 expressed in terms of the number of structures published per annum (p. 663) | html | pdf |
    - Fig. 24.3.2.1. Information content of the Cambridge Structural Database (CSD) (p. 664) | html | pdf |
    - Fig. 24.3.2.2. 2D chemical connectivity data for a simple organic molecule (p. 664) | html | pdf |
    - Fig. 24.3.3.1. Summary of the software components of the Cambridge Structural Database system (CSDS) (p. 665) | html | pdf |
    - Fig. 24.3.3.2. The keto···hydroxyl fragment described in the example of CSDS usage (p. 666) | html | pdf |
    - Fig. 24.3.3.3. A typical Quest3D graphics screen showing how search hits are visualized and manipulated (p. 667) | html | pdf |
    - Fig. 24.3.3.4. A Vista histogram of the hydrogen-bond distance (p. 667) | html | pdf |
    - Fig. 24.3.3.5. A Vista scatterplot of the hydrogen-bond length (DOH) versus the O—H···O angle (AH) (p. 667) | html | pdf |
    - Fig. 24.3.3.6. A Vista polar scatterplot of THETA versus PHI (p. 668) | html | pdf |
  - Tables
    - Table 24.3.1.1. CSD statistics (August 2000) (p. 663) | html | pdf |
- 24.4. The Biological Macromolecule Crystallization Database (pp. 669-674) | html | pdf | chapter contents |
  G. L. Gilliland, M. Tung and J. E. Ladner
  - 24.4.1. Introduction (p. 669) | html | pdf |
  - 24.4.2. History of the BMCD (p. 669) | html | pdf |
  - 24.4.3. BMCD data (p. 669) | html | pdf |
  - 24.4.4. BMCD implementation – web interface (p. 670) | html | pdf |
  - 24.4.5. Reproducing published crystallization procedures (pp. 670-671) | html | pdf |
  - 24.4.6. Crystallization screens (p. 671) | html | pdf |
  - 24.4.7. A general crystallization procedure (pp. 671-674) | html | pdf |
  - 24.4.8. The future of the BMCD (p. 674) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.4.3.1. A representative example of a biological macromolecule, subtilisin BPN′: prodomain, entry M1MT in the BMCD (p. 670) | html | pdf |
    - Fig. 24.4.3.2. A representative example of a crystal entry C2CK for the subtilsin BPN′: prodomain, entry M1MT in the BMCD (p. 670) | html | pdf |
    - Fig. 24.4.5.1. Crystal of recombinant rat liver glutathione S-transferase (Ji et al (p. 671) | html | pdf |
    - Fig. 24.4.7.1. A general crystallization strategy based on the data contained in the BMCD (p. 671) | html | pdf |
  - Tables
    - Table 24.4.6.1. Crystallization conditions for endonucleases (pp. 672-673) | html | pdf |
- 24.5. The Protein Data Bank, 1999– (pp. 675-684) | html | pdf | chapter contents |
  H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov and P. E. Bourne
  - 24.5.1. Introduction (p. 675) | html | pdf |
  - 24.5.2. Data acquisition and processing (pp. 675-677) | html | pdf |
    - 24.5.2.1. Content of the data collected by the PDB (pp. 675-676) | html | pdf |
    - 24.5.2.2. Validation (pp. 676-677) | html | pdf |
    - 24.5.2.3. NMR data (p. 677) | html | pdf |
    - 24.5.2.4. Data-processing statistics (p. 677) | html | pdf |
  - 24.5.3. The PDB database resource (pp. 677-678) | html | pdf |
    - 24.5.3.1. The database architecture (pp. 677-678) | html | pdf |
    - 24.5.3.2. Database queries (p. 678) | html | pdf |
  - 24.5.4. Data distribution (p. 679) | html | pdf |
  - 24.5.5. Data archiving (pp. 679-680) | html | pdf |
  - 24.5.6. Maintenance of the legacy of the BNL system (p. 680) | html | pdf |
  - 24.5.7. Current developments (p. 680) | html | pdf |
  - 24.5.8. PDB advisory boards (p. 680) | html | pdf |
  - 24.5.9. Further information (pp. 680-681) | html | pdf |
  - 24.5.10. Conclusion (p. 681) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 24.5.2.1. The steps in PDB data processing (p. 675) | html | pdf |
    - Fig. 24.5.2.2. The integrated tools of the PDB data-processing system (p. 676) | html | pdf |
    - Fig. 24.5.3.1. The integrated query interface to the PDB (p. 677) | html | pdf |
    - Fig. 24.5.3.2. The various query options that are available for the PDB (p. 678) | html | pdf |
  - Tables
    - Table 24.5.2.1. Content of data in the PDB (p. 676) | html | pdf |
    - Table 24.5.2.2. Demographics of the released data in the PDB as of 14 September 1999 (p. 677) | html | pdf |
    - Table 24.5.3.1. Current query capabilities of the PDB (p. 678) | html | pdf |
    - Table 24.5.3.2. Static cross-links to other data resources currently provided by the PDB (p. 679) | html | pdf |
    - Table 24.5.3.3. Web query statistics for the primary RCSB site (www.rcsb.org ) (p. 679) | html | pdf |
    - Table 24.5.9.1. PDB information sources (p. 680) | html | pdf |

Macromolecular crystallography programs
- 25.1. Survey of programs for crystal structure determination and analysis of macromolecules (pp. 685-694) | html | pdf | chapter contents |
  J. Ding and E. Arnold
  - 25.1.1. Introduction (p. 685) | html | pdf |
  - 25.1.2. Multipurpose crystallographic program systems (pp. 685-687) | html | pdf |
    - 25.1.2.1. Biological software from the EBI (p. 685) | html | pdf |
    - 25.1.2.2. BIOMOL (p. 685) | html | pdf |
    - 25.1.2.3. BLANC (p. 686) | html | pdf |
    - 25.1.2.4. CCP4 program suite (p. 686) | html | pdf |
    - 25.1.2.5. CNS (p. 686) | html | pdf |
    - 25.1.2.6. MAIN (p. 686) | html | pdf |
    - 25.1.2.7. PHASES (p. 686) | html | pdf |
    - 25.1.2.8. PROTEIN (p. 686) | html | pdf |
    - 25.1.2.9. The Purdue University XTAL Program Library (pp. 686-687) | html | pdf |
    - 25.1.2.10. SOLVE (p. 687) | html | pdf |
    - 25.1.2.11. USF (p. 687) | html | pdf |
    - 25.1.2.12. X-PLOR (p. 687) | html | pdf |
    - 25.1.2.13. Xtal (p. 687) | html | pdf |
    - 25.1.2.14. XtalView (p. 687) | html | pdf |
  - 25.1.3. Data collection and processing (pp. 687-688) | html | pdf |
    - 25.1.3.1. DPS (p. 687) | html | pdf |
    - 25.1.3.2. HKL (p. 687) | html | pdf |
    - 25.1.3.3. LOCSCL (p. 687) | html | pdf |
    - 25.1.3.4. MOSFLM (p. 687) | html | pdf |
    - 25.1.3.5. SCALA (p. 688) | html | pdf |
    - 25.1.3.6. STRATEGY (p. 688) | html | pdf |
  - 25.1.4. Phase determination and structure solution (pp. 688-689) | html | pdf |
    - 25.1.4.1. AMoRe (p. 688) | html | pdf |
    - 25.1.4.2. GLRF (p. 688) | html | pdf |
    - 25.1.4.3. HEAVY (p. 688) | html | pdf |
    - 25.1.4.4. MADSYS (p. 688) | html | pdf |
    - 25.1.4.5. MLPHARE (p. 688) | html | pdf |
    - 25.1.4.6. Shake-and-Bake (p. 688) | html | pdf |
    - 25.1.4.7. SHARP (pp. 688-689) | html | pdf |
  - 25.1.5. Structure refinement (p. 689) | html | pdf |
    - 25.1.5.1. ARP/wARP (p. 689) | html | pdf |
    - 25.1.5.2. MULTAN88 (p. 689) | html | pdf |
    - 25.1.5.3. PROLSQ (p. 689) | html | pdf |
    - 25.1.5.4. REFMAC (p. 689) | html | pdf |
    - 25.1.5.5. RSRef (p. 689) | html | pdf |
    - 25.1.5.6. SHELX97 (p. 689) | html | pdf |
    - 25.1.5.7. SIR97 (p. 689) | html | pdf |
    - 25.1.5.8. TNT (p. 689) | html | pdf |
  - 25.1.6. Phase improvement and density-map modification (pp. 689-690) | html | pdf |
    - 25.1.6.1. BUSTER (p. 690) | html | pdf |
    - 25.1.6.2. DM/DMMULTI (p. 690) | html | pdf |
    - 25.1.6.3. FINDNCS (p. 690) | html | pdf |
    - 25.1.6.4. RAVE (p. 690) | html | pdf |
    - 25.1.6.5. SOLOMON (p. 690) | html | pdf |
    - 25.1.6.6. SQUASH (p. 690) | html | pdf |
  - 25.1.7. Graphics and model building (pp. 690-691) | html | pdf |
    - 25.1.7.1. AMBER (p. 690) | html | pdf |
    - 25.1.7.2. CHARMM (p. 690) | html | pdf |
    - 25.1.7.3. Insight II (p. 690) | html | pdf |
    - 25.1.7.4. MidasPlus (pp. 690-691) | html | pdf |
    - 25.1.7.5. MODELLER (p. 691) | html | pdf |
    - 25.1.7.6. MOLMOL (p. 691) | html | pdf |
    - 25.1.7.7. O (p. 691) | html | pdf |
    - 25.1.7.8. QUANTA (p. 691) | html | pdf |
    - 25.1.7.9. SYBYL (p. 691) | html | pdf |
    - 25.1.7.10. Turbo FRODO (p. 691) | html | pdf |
  - 25.1.8. Structure analysis and verification (pp. 691-693) | html | pdf |
    - 25.1.8.1. DSSP (pp. 691-692) | html | pdf |
    - 25.1.8.2. HBPLUS (p. 692) | html | pdf |
    - 25.1.8.3. Molecular Surface (p. 692) | html | pdf |
    - 25.1.8.4. MSMS (p. 692) | html | pdf |
    - 25.1.8.5. NACCESS (p. 692) | html | pdf |
    - 25.1.8.6. NAOMI (p. 692) | html | pdf |
    - 25.1.8.7. PASS (p. 692) | html | pdf |
    - 25.1.8.8. PROCHECK (p. 692) | html | pdf |
    - 25.1.8.9. ProFit (pp. 692-693) | html | pdf |
    - 25.1.8.10. PROSA (p. 693) | html | pdf |
    - 25.1.8.11. SARF (p. 693) | html | pdf |
    - 25.1.8.12. SQUID (p. 693) | html | pdf |
    - 25.1.8.13. STAMP (p. 693) | html | pdf |
    - 25.1.8.14. SURFNET (p. 693) | html | pdf |
    - 25.1.8.15. WHAT CHECK (p. 693) | html | pdf |
    - 25.1.8.16. WHAT IF (p. 693) | html | pdf |
  - 25.1.9. Structure presentation (pp. 693-694) | html | pdf |
    - 25.1.9.1. GRASP (p. 693) | html | pdf |
    - 25.1.9.2. LIGPLOT (p. 693) | html | pdf |
    - 25.1.9.3. MOLSCRIPT (pp. 693-694) | html | pdf |
    - 25.1.9.4. NUCPLOT (p. 694) | html | pdf |
    - 25.1.9.5. ORTEP (p. 694) | html | pdf |
    - 25.1.9.6. RasMol (p. 694) | html | pdf |
    - 25.1.9.7. Raster3D (p. 694) | html | pdf |
    - 25.1.9.8. Ribbons (p. 694) | html | pdf |
    - 25.1.9.9. SETOR (p. 694) | html | pdf |
    - 25.1.9.10. VMD (p. 694) | html | pdf |
  - References | html | pdf |
- 25.2. Programs and program systems in wide use (pp. 695-743) | html | pdf | chapter contents |
  W. Furey, K. D. Cowtan, K. Y. J. Zhang, P. Main, 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, T. Simonson, D. E. Tronrud, L. F. Ten Eyck, V. S. Lamzin, A. Perrakis, K. S. Wilson, R. A. Laskowski, M. W. MacArthur, J. M. Thornton, P. J. Kraulis, D. C. Richardson, J. S. Richardson, W. Kabsch and G. M. Sheldrick
  - 25.2.1. PHASES (pp. 695-705) | html | pdf |
    W. Furey
    - 25.2.1.1. Overall scope of the package (pp. 695-696) | html | pdf |
      - 25.2.1.1.1. Isomorphous replacement, anomalous scattering and MAD phasing (p. 695) | html | pdf |
      - 25.2.1.1.2. Solvent flattening and negative-density truncation (p. 695) | html | pdf |
      - 25.2.1.1.3. Noncrystallographic symmetry averaging (p. 695) | html | pdf |
      - 25.2.1.1.4. Partial structure phase combination and phase extension (p. 696) | html | pdf |
    - 25.2.1.2. Design principles (p. 696) | html | pdf |
      - 25.2.1.2.1. General program structure and data flow (p. 696) | html | pdf |
      - 25.2.1.2.2. Parameter and cumulative log files (p. 696) | html | pdf |
    - 25.2.1.3. Merging and scaling native and derivative data (pp. 696-697) | html | pdf |
      - 25.2.1.3.1. Relative Wilson scaling (p. 696) | html | pdf |
      - 25.2.1.3.2. Global anisotropic scaling (p. 697) | html | pdf |
      - 25.2.1.3.3. Local scaling (p. 697) | html | pdf |
      - 25.2.1.3.4. Outlier rejection (p. 697) | html | pdf |
    - 25.2.1.4. Fourier-map calculations (p. 697) | html | pdf |
      - 25.2.1.4.1. Submaps (p. 697) | html | pdf |
      - 25.2.1.4.2. Orthogonal and skewed maps (p. 697) | html | pdf |
      - 25.2.1.4.3. Graphics maps and skeletonization (p. 697) | html | pdf |
      - 25.2.1.4.4. Peak search (p. 697) | html | pdf |
    - 25.2.1.5. Structure-factor and phase calculations (pp. 697-698) | html | pdf |
      - 25.2.1.5.1. By heavy-atom or anomalous-scattering methods (pp. 697-698) | html | pdf |
      - 25.2.1.5.2. Directly from atomic coordinates (p. 698) | html | pdf |
      - 25.2.1.5.3. By map inversion (p. 698) | html | pdf |
    - 25.2.1.6. Parameter refinement (pp. 698-699) | html | pdf |
      - 25.2.1.6.1. Against amplitude differences (p. 698) | html | pdf |
      - 25.2.1.6.2. By minimizing lack of closure  (pp. 698-699) | html | pdf |
        25.2.1.6.2.1. `Classical' phase refinement  (p. 699) | html | pdf |
        25.2.1.6.2.2. Approximate-likelihood method  (p. 699) | html | pdf |
        25.2.1.6.2.3. Using external phase information  (p. 699) | html | pdf |
      - 25.2.1.6.3. Rigid-group refinement (p. 699) | html | pdf |
    - 25.2.1.7. Origin and hand correlation, and completing the heavy-atom substructure (pp. 699-700) | html | pdf |
      - 25.2.1.7.1. Difference and cross-difference Fourier syntheses (pp. 699-700) | html | pdf |
      - 25.2.1.7.2. Bijvoet difference and cross-Bijvoet difference Fourier syntheses (p. 700) | html | pdf |
    - 25.2.1.8. Solvent flattening and negative-density truncation (pp. 700-701) | html | pdf |
      - 25.2.1.8.1. Mask construction  (pp. 700-701) | html | pdf |
        25.2.1.8.1.1. Automated mask construction  (pp. 700-701) | html | pdf |
        25.2.1.8.1.2. Masks from atomic coordinates  (p. 701) | html | pdf |
        25.2.1.8.1.3. Mask verification and manual editing  (p. 701) | html | pdf |
      - 25.2.1.8.2. The flattening and truncation procedure (p. 701) | html | pdf |
    - 25.2.1.9. Phase combination and extension procedures (pp. 701-702) | html | pdf |
      - 25.2.1.9.1. Modified Sim weights (p. 701) | html | pdf |
      - 25.2.1.9.2. σ_A weights (p. 702) | html | pdf |
      - 25.2.1.9.3. Damping contributions (p. 702) | html | pdf |
      - 25.2.1.9.4. Phase extension (p. 702) | html | pdf |
    - 25.2.1.10. Noncrystallographic symmetry calculations (pp. 702-704) | html | pdf |
      - 25.2.1.10.1. Operator representation and definitions (p. 702) | html | pdf |
      - 25.2.1.10.2. Operator refinement  (pp. 702-703) | html | pdf |
        25.2.1.10.2.1. Simple rotational symmetry  (p. 703) | html | pdf |
        25.2.1.10.2.2. Complex rotational and/or translational symmetry  (p. 703) | html | pdf |
      - 25.2.1.10.3. Averaging mask construction (p. 703) | html | pdf |
      - 25.2.1.10.4. Map averaging  (p. 703) | html | pdf |
        25.2.1.10.4.1. Single-crystal averaging  (p. 703) | html | pdf |
        25.2.1.10.4.2. Multiple-crystal averaging  (p. 703) | html | pdf |
      - 25.2.1.10.5. Phase combination and extension (pp. 703-704) | html | pdf |
    - 25.2.1.11. Automated iterative processing (p. 704) | html | pdf |
      - 25.2.1.11.1. The DOALL procedure (p. 704) | html | pdf |
      - 25.2.1.11.2. The EXTNDAVG and EXTNDAVG_MC procedures (p. 704) | html | pdf |
    - 25.2.1.12. Graphical capabilities (pp. 704-705) | html | pdf |
      - 25.2.1.12.1. Pseudo-precession photographs (p. 704) | html | pdf |
      - 25.2.1.12.2. Interactive contouring or mask editing (p. 704) | html | pdf |
      - 25.2.1.12.3. Off-line contouring (p. 704) | html | pdf |
      - 25.2.1.12.4. Generic plot files and drivers  (p. 705) | html | pdf |
        25.2.1.12.4.1. GL displays  (p. 705) | html | pdf |
        25.2.1.12.4.2. X-Window displays  (p. 705) | html | pdf |
        25.2.1.12.4.3. PostScript files  (p. 705) | html | pdf |
        25.2.1.12.4.4. Tektronix output  (p. 705) | html | pdf |
    - 25.2.1.13. Auxiliary programs (p. 705) | html | pdf |
      - 25.2.1.13.1. Coordinate conversions (p. 705) | html | pdf |
      - 25.2.1.13.2. NC symmetry operator conversions (p. 705) | html | pdf |
      - 25.2.1.13.3. Binary or formatted file conversions (p. 705) | html | pdf |
      - 25.2.1.13.4. Importing phase information (p. 705) | html | pdf |
      - 25.2.1.13.5. Phase set comparisons (p. 705) | html | pdf |
  - 25.2.2. DM/DMMULTI software for phase improvement by density modification (pp. 705-710) | html | pdf |
    K. D. Cowtan, K. Y. J. Zhang and P. Main
    - 25.2.2.1. Introduction (pp. 705-706) | html | pdf |
    - 25.2.2.2. Program operation (p. 706) | html | pdf |
    - 25.2.2.3. Preparation of input data (p. 706) | html | pdf |
    - 25.2.2.4. Choice of modes (pp. 706-709) | html | pdf |
      - 25.2.2.4.1. Density-modification modes (p. 707) | html | pdf |
      - 25.2.2.4.2. Phase-combination modes (pp. 707-708) | html | pdf |
      - 25.2.2.4.3. Phase-extension schemes (pp. 708-709) | html | pdf |
    - 25.2.2.5. Code description (pp. 709-710) | html | pdf |
      - 25.2.2.5.1. Scaling (p. 709) | html | pdf |
      - 25.2.2.5.2. Solvent-mask determination (pp. 709-710) | html | pdf |
      - 25.2.2.5.3. Averaging-mask determination (p. 710) | html | pdf |
      - 25.2.2.5.4. Fourier transforms (p. 710) | html | pdf |
      - 25.2.2.5.5. Histogram matching (p. 710) | html | pdf |
      - 25.2.2.5.6. Averaging (p. 710) | html | pdf |
      - 25.2.2.5.7. Multi-crystal averaging (p. 710) | html | pdf |
  - 25.2.3. The structure-determination language of the Crystallography & NMR System (pp. 710-716) | html | pdf |
    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
    - 25.2.3.1. Introduction (p. 710) | html | pdf |
    - 25.2.3.2. The CNS language (pp. 711-712) | html | pdf |
    - 25.2.3.3. Symbols and parameters (p. 712) | html | pdf |
    - 25.2.3.4. Statistical functions (p. 712) | html | pdf |
    - 25.2.3.5. Symbolic target function (pp. 712-713) | html | pdf |
    - 25.2.3.6. Modules and procedures (p. 714) | html | pdf |
    - 25.2.3.7. Task files (p. 715) | html | pdf |
    - 25.2.3.8. HTML interface (p. 715) | html | pdf |
    - 25.2.3.9. Example: combined maximum-likelihood and simulated-annealing refinement (pp. 715-716) | html | pdf |
    - 25.2.3.10. Conclusions (p. 716) | html | pdf |
  - 25.2.4. The TNT refinement package (pp. 716-720) | html | pdf |
    D. E. Tronrud and L. F. Ten Eyck
    - 25.2.4.1. Scope and function of the package (pp. 716-717) | html | pdf |
    - 25.2.4.2. Historical context (p. 717) | html | pdf |
    - 25.2.4.3. Design principles (pp. 717-718) | html | pdf |
      - 25.2.4.3.1. Refinement should be simple to run (p. 717) | html | pdf |
      - 25.2.4.3.2. Refinement should run quickly and use as little memory as possible (pp. 717-718) | html | pdf |
      - 25.2.4.3.3. The source code should not require customization for each project (p. 718) | html | pdf |
    - 25.2.4.4. Current structure of the package (p. 718) | html | pdf |
    - 25.2.4.5. Innovations first introduced in TNT (pp. 718-719) | html | pdf |
      - 25.2.4.5.1. Identifying and restraining symmetry-related contacts (1982) (p. 719) | html | pdf |
      - 25.2.4.5.2. The ability of a single package to perform both individual atom and rigid-body refinement (1982) (p. 719) | html | pdf |
      - 25.2.4.5.3. Space-group optimized FFTs for all space groups (1989) (p. 719) | html | pdf |
      - 25.2.4.5.4. Modelling bulk solvent scattering via local scaling (∼1989) (p. 719) | html | pdf |
      - 25.2.4.5.5. Preconditioned conjugate-gradient minimization (1990) (p. 719) | html | pdf |
      - 25.2.4.5.6. Restraining stereochemistry of chemical links to symmetry-related molecules (∼1992) (p. 719) | html | pdf |
      - 25.2.4.5.7. Knowledge-based B-factor restraints (∼1994) (p. 719) | html | pdf |
      - 25.2.4.5.8. Block-diagonal preconditioned conjugate-gradient minimization with pseudoinverses (1998) (p. 719) | html | pdf |
      - 25.2.4.5.9. Generalization of noncrystallographic symmetry operators to include shifts in the average B factor (1998) (p. 719) | html | pdf |
    - 25.2.4.6. TNT as a research tool (pp. 719-720) | html | pdf |
      - 25.2.4.6.1. Michael Chapman's real-space refinement package (p. 719) | html | pdf |
      - 25.2.4.6.2. Gerard Bricogne's Buster refinement package (p. 719) | html | pdf |
      - 25.2.4.6.3. Randy Read's maximum-likelihood function (p. 720) | html | pdf |
      - 25.2.4.6.4. J. P. Abrahams' likelihood-weighted noncrystallographic symmetry restraints (p. 720) | html | pdf |
  - 25.2.5. The ARP/wARP suite for automated construction and refinement of protein models (pp. 720-722) | html | pdf |
    V. S. Lamzin, A. Perrakis and K. S. Wilson
    - 25.2.5.1. Refinement and model building are two sides of modelling a structure (pp. 720-721) | html | pdf |
      - 25.2.5.1.1. Model update (p. 720) | html | pdf |
      - 25.2.5.1.2. Model reconstruction (pp. 720-721) | html | pdf |
      - 25.2.5.1.3. Representation of a map by free-atom models (p. 721) | html | pdf |
      - 25.2.5.1.4. Hybrid models (p. 721) | html | pdf |
      - 25.2.5.1.5. Real-space manipulation coupled with reciprocal-space refinement (p. 721) | html | pdf |
    - 25.2.5.2. ARP/wARP applications (pp. 721-722) | html | pdf |
      - 25.2.5.2.1. Model building from initial phases (p. 721) | html | pdf |
      - 25.2.5.2.2. Refinement of molecular-replacement solutions (p. 721) | html | pdf |
      - 25.2.5.2.3. Density modification via averaging of multiple refinements (pp. 721-722) | html | pdf |
      - 25.2.5.2.4. Ab initio solution of metalloproteins (p. 722) | html | pdf |
      - 25.2.5.2.5. Solvent building (p. 722) | html | pdf |
    - 25.2.5.3. Applicability and requirements (p. 722) | html | pdf |
    - 25.2.5.4. An example (p. 722) | html | pdf |
  - 25.2.6. PROCHECK: validation of protein-structure coordinates (pp. 722-725) | html | pdf |
    R. A. Laskowski, M. W. MacArthur and J. M. Thornton
    - 25.2.6.1. Introduction (pp. 722-723) | html | pdf |
    - 25.2.6.2. The program (p. 723) | html | pdf |
    - 25.2.6.3. The parameters (p. 723) | html | pdf |
    - 25.2.6.4. Which parameters are best? (pp. 723-724) | html | pdf |
    - 25.2.6.5. Input (pp. 724-725) | html | pdf |
    - 25.2.6.6. Output produced (p. 725) | html | pdf |
    - 25.2.6.7. Other validation tools (p. 725) | html | pdf |
  - 25.2.7. MolScript (pp. 725-727) | html | pdf |
    P. J. Kraulis
    - 25.2.7.1. Introduction (p. 725) | html | pdf |
    - 25.2.7.2. Input (p. 725) | html | pdf |
    - 25.2.7.3. Graphics (pp. 725-726) | html | pdf |
      - 25.2.7.3.1. The coordinate system (p. 725) | html | pdf |
      - 25.2.7.3.2. The graphics state (pp. 725-726) | html | pdf |
      - 25.2.7.3.3. Graphics commands (p. 726) | html | pdf |
      - 25.2.7.3.4. Atom and residue selection (p. 726) | html | pdf |
      - 25.2.7.3.5. External objects (p. 726) | html | pdf |
    - 25.2.7.4. Output (p. 726) | html | pdf |
      - 25.2.7.4.1. PostScript (p. 726) | html | pdf |
      - 25.2.7.4.2. Raster3D (p. 726) | html | pdf |
      - 25.2.7.4.3. VRML97 (p. 726) | html | pdf |
      - 25.2.7.4.4. OpenGL (p. 726) | html | pdf |
      - 25.2.7.4.5. Image files (p. 726) | html | pdf |
    - 25.2.7.5. Utilities (pp. 726-727) | html | pdf |
  - 25.2.8. MAGE, PROBE and kinemages (pp. 727-730) | html | pdf |
    D. C. Richardson and J. S. Richardson
    - 25.2.8.1. Introduction to aims and concepts (p. 727) | html | pdf |
    - 25.2.8.2. Use as a reader of existing kinemages (p. 727) | html | pdf |
    - 25.2.8.3. Use for teaching (pp. 727-728) | html | pdf |
    - 25.2.8.4. Use for research (pp. 728-729) | html | pdf |
    - 25.2.8.5. Contact dots in crystallographic rebuilding (p. 729) | html | pdf |
    - 25.2.8.6. Making kinemages (pp. 729-730) | html | pdf |
    - 25.2.8.7. Software notes (p. 730) | html | pdf |
  - 25.2.9. XDS (pp. 730-734) | html | pdf |
    W. Kabsch
    - 25.2.9.1. Functional specification (p. 730) | html | pdf |
    - 25.2.9.2. Components of the package (pp. 730-734) | html | pdf |
      - 25.2.9.2.1. XDS (pp. 730-733) | html | pdf |
      - 25.2.9.2.2. XPLAN (p. 733) | html | pdf |
      - 25.2.9.2.3. XSCALE (pp. 733-734) | html | pdf |
      - 25.2.9.2.4. VIEW (p. 734) | html | pdf |
      - 25.2.9.2.5. XDSCONV (p. 734) | html | pdf |
    - 25.2.9.3. Remarks (p. 734) | html | pdf |
  - 25.2.10. Macromolecular applications of SHELX (pp. 734-738) | html | pdf |
    G. M. Sheldrick
    - 25.2.10.1. Historical introduction to SHELX (p. 734) | html | pdf |
    - 25.2.10.2. Program organization and philosophy (p. 735) | html | pdf |
    - 25.2.10.3. Heavy-atom location using SHELXS and SHELXD (pp. 735-736) | html | pdf |
      - 25.2.10.3.1. The Patterson map interpretation algorithm in SHELXS (p. 735) | html | pdf |
      - 25.2.10.3.2. Integrated Patterson and direct methods: SHELXD (p. 735) | html | pdf |
      - 25.2.10.3.3. Practical considerations (p. 736) | html | pdf |
    - 25.2.10.4. Macromolecular refinement using SHELXL (pp. 736-737) | html | pdf |
      - 25.2.10.4.1. Constraints and restraints (p. 736) | html | pdf |
      - 25.2.10.4.2. Least-squares refinement algebra (p. 736) | html | pdf |
      - 25.2.10.4.3. Full-matrix estimates of standard uncertainties (p. 736) | html | pdf |
      - 25.2.10.4.4. Refinement of anisotropic displacement parameters (pp. 736-737) | html | pdf |
      - 25.2.10.4.5. Similar geometry and NCS restraints (p. 737) | html | pdf |
      - 25.2.10.4.6. Modelling disorder and solvent (p. 737) | html | pdf |
      - 25.2.10.4.7. Twinned crystals (p. 737) | html | pdf |
      - 25.2.10.4.8. The radius of convergence (p. 737) | html | pdf |
    - 25.2.10.5. SHELXPRO – protein interface to SHELX (pp. 737-738) | html | pdf |
    - 25.2.10.6. Distribution and support of SHELX (p. 738) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 25.2.1.1. Flow chart for the major phasing path (p. 696) | html | pdf |
    - Fig. 25.2.1.2. Relationships between noncrystallographic symmetry rotation axis direction, orthogonal reference system axes X, Y, Z and crystallographic axes (p. 702) | html | pdf |
    - Fig. 25.2.2.1. (a) Input and output data for a DM calculation with no averaging (p. 707) | html | pdf |
    - Fig. 25.2.2.2. (a) Flow chart for a simple DM calculation with free-Sim phase combination (p. 708) | html | pdf |
    - Fig. 25.2.2.3. (a) Conceptual flowchart for a DMMULTI multi-crystal calculation (p. 709) | html | pdf |
    - Fig. 25.2.3.1. CNS consists of five layers which are under user control (p. 711) | html | pdf |
    - Fig. 25.2.3.2. Examples of compound symbols and compound parameters (p. 712) | html | pdf |
    - Fig. 25.2.3.3. Example for statistical operations provided by the CNS language (p. 712) | html | pdf |
    - Fig. 25.2.3.4. Examples of symbolic definition of a refinement target function and its derivatives with respect to the calculated structure-factor arrays (p. 713) | html | pdf |
    - Fig. 25.2.3.5. Use of compound parameters within a module (p. 713) | html | pdf |
    - Fig. 25.2.3.6. Example of (a) a CNS module and (b) the corresponding module invocation (p. 714) | html | pdf |
    - Fig. 25.2.3.7. Procedures and features available in CNS for structure determination by X-ray crystallography (p. 714) | html | pdf |
    - Fig. 25.2.3.8. Example of a typical CNS task file (p. 715) | html | pdf |
    - Fig. 25.2.3.9. Example of a CNS HTML form page (p. 715) | html | pdf |
    - Fig. 25.2.3.10. 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. 716) | html | pdf |
    - Fig. 25.2.5.1. A flow chart of the Automated Refinement Procedure (p. 720) | html | pdf |
    - Fig. 25.2.6.1. PROCHECK Ramachandran plots (p. 723) | html | pdf |
    - Fig. 25.2.6.2. Two of the residue-property plots generated by PROCHECK (p. 724) | html | pdf |
    - Fig. 25.2.6.3. Schematic plots of various residue-by-residue properties (p. 724) | html | pdf |
    - Fig. 25.2.8.1. A typical macromolecular kinemage (p. 728) | html | pdf |
    - Fig. 25.2.8.2. A ribbon-schematic kinemage of ribonuclease A (p. 728) | html | pdf |
    - Fig. 25.2.8.3. A thin slice through an all-atom contact kinemage showing the van der Waals interactions of Pro203 and neighbouring atoms in Zn elastase (p. 728) | html | pdf |
    - Fig. 25.2.8.4. All-atom contact dots being used in O for model rebuilding during refinement of a Trp tRNA synthetase (p. 729) | html | pdf |
  - Tables
    - Table 25.2.6.1. Summary of expected values for stereochemical parameters in well resolved structures (p. 723) | html | pdf |
    - Table 25.2.9.1. Information exchange between program steps of XDS (p. 731) | html | pdf |

A historical perspective
- 26.1. How the structure of lysozyme was actually determined (pp. 745-772) | 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
  - 26.1.1. Introduction (p. 745) | html | pdf |
  - 26.1.2. Structure analysis at 6 Å resolution (pp. 745-753) | html | pdf |
    - 26.1.2.1. Technical facilities (p. 745) | html | pdf |
    - 26.1.2.2. Lysozyme crystallization (pp. 745-746) | html | pdf |
    - 26.1.2.3. Preparation of heavy-atom derivatives (p. 746) | html | pdf |
    - 26.1.2.4. Determination of heavy-atom positions (pp. 746-747) | html | pdf |
      - 26.1.2.4.1. The mercuri-iodide (K₂HgI₄) derivative (p. 747) | html | pdf |
      - 26.1.2.4.2. The palladium chloride (K₂PdCl₄) derivative (p. 747) | html | pdf |
      - 26.1.2.4.3. The o-mercurihydroxytoluene p-sulfonate (MHTS) derivative (p. 747) | html | pdf |
      - 26.1.2.4.4. Other potential derivatives (p. 747) | html | pdf |
    - 26.1.2.5. Refinement of heavy-atom parameters (p. 747) | html | pdf |
    - 26.1.2.6. Analysis in three dimensions (pp. 747-751) | html | pdf |
      - 26.1.2.6.1. X-ray intensity measurements (pp. 747-750) | html | pdf |
      - 26.1.2.6.2. Data processing (pp. 750-751) | html | pdf |
      - 26.1.2.6.3. The absolute scale of the intensities (p. 751) | html | pdf |
      - 26.1.2.6.4. Re-assessment of heavy-atom derivatives (p. 751) | html | pdf |
    - 26.1.2.7. Phase determination at 6 Å resolution (pp. 751-752) | html | pdf |
    - 26.1.2.8. The electron-density map of lysozyme at 6 Å resolution (pp. 752-753) | html | pdf |
  - 26.1.3. Analysis of the structure at 2 Å resolution (pp. 753-765) | html | pdf |
    - 26.1.3.1. Heavy-atom derivatives at 2 Å resolution (pp. 754-756) | html | pdf |
    - 26.1.3.2. Intensity measurements (pp. 756-757) | html | pdf |
    - 26.1.3.3. The second low-resolution map at 6 Å (p. 757) | html | pdf |
    - 26.1.3.4. Intensity measurements at high resolution (pp. 757-759) | html | pdf |
      - 26.1.3.4.1. Experimental methods (pp. 757-758) | html | pdf |
      - 26.1.3.4.2. Diffractometer output (pp. 758-759) | html | pdf |
    - 26.1.3.5. Data processing (p. 759) | html | pdf |
      - 26.1.3.5.1. Absorption corrections (p. 759) | html | pdf |
    - 26.1.3.6. Further stages of data processing (pp. 759-760) | html | pdf |
    - 26.1.3.7. The crystal-type problem (pp. 760-761) | html | pdf |
    - 26.1.3.8. Final refinement of heavy-atom parameters (pp. 761-762) | html | pdf |
    - 26.1.3.9. Calculation of phase values (p. 762) | html | pdf |
    - 26.1.3.10. The electron-density map at 2 Å resolution (p. 763) | html | pdf |
    - 26.1.3.11. Map interpretation and model building (pp. 763-765) | html | pdf |
  - 26.1.4. Structural studies on the biological function of lysozyme (pp. 765-769) | html | pdf |
    - 26.1.4.1. Lysozyme substrates (pp. 765-766) | html | pdf |
    - 26.1.4.2. The crystal structure of GlcNAc (p. 766) | html | pdf |
    - 26.1.4.3. Low-resolution binding studies of lysozyme with GlcNAc and other sugars (p. 766) | html | pdf |
    - 26.1.4.4. Binding studies of lysozyme with tri-N-acetyl-chitotriose, (GlcNAc)₃, at 2 Å resolution (pp. 766-768) | html | pdf |
    - 26.1.4.5. Proposals for the catalytic mechanism of lysozyme (pp. 768-769) | html | pdf |
  - References | html | pdf |
  - Figures
    - Fig. 26.1.2.1. Tetragonal lysozyme crystals with well developed {110} faces (left-hand crystal) and small {110} faces (right-hand crystal) (p. 746) | html | pdf |
    - Fig. 26.1.2.2. Difference-Patterson h0l projection map for the derivative obtained with K₂PdCl₄ (p. 747) | html | pdf |
    - Fig. 26.1.2.3. Difference-Patterson hk0 projection for the derivative obtained with MHTS (p. 747) | html | pdf |
    - Fig. 26.1.2.4. 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. 748) | html | pdf |
    - Fig. 26.1.2.5. Crystal mounting (p. 749) | html | pdf |
    - Fig. 26.1.2.6. Absorption curve (p. 749) | html | pdf |
    - Fig. 26.1.2.7. Typical output from the linear diffractometer (p. 750) | html | pdf |
    - Fig. 26.1.2.8. Format of monitor output in which the computer lists reflections that fail the tests for format or significance (p. 750) | html | pdf |
    - Fig. 26.1.2.9. Three-dimensional $[|\Delta F|^{2}]$ syntheses for the PdCl₄ and MHTS derivatives (p. 751) | html | pdf |
    - Fig. 26.1.2.10. Phase determination for reflection 424 (p. 752) | html | pdf |
    - Fig. 26.1.2.11. 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. 753) | html | pdf |
    - Fig. 26.1.2.12. Electron-density distribution in lysozyme at 6 Å resolution viewed parallel to the c axis (p. 753) | html | pdf |
    - Fig. 26.1.2.13. Views of a 6 Å resolution model of the regions in which the electron density exceeds about 0.53 e Å⁻³ (p. 754) | html | pdf |
    - Fig. 26.1.3.1. 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. 756) | html | pdf |
    - Fig. 26.1.3.2. The $[a^{*}b^{*}]$ plane of the reciprocal lattice oriented to rotate about the $[[\bar{1}10]]$ axis (p. 757) | html | pdf |
    - Fig. 26.1.3.3. 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. 758) | html | pdf |
    - Fig. 26.1.3.4. 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. 759) | html | pdf |
    - Fig. 26.1.3.5. Asymmetric mounting of a protein crystal with its mother liquor in a capillary tube (p. 760) | html | pdf |
    - Fig. 26.1.3.6. Plot of the ratio $[\textstyle\sum_{h}\displaystyle I(h)/ \textstyle\sum_{h}\displaystyle I(-h)]$ against h (p. 760) | html | pdf |
    - Fig. 26.1.3.7. (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. 762) | html | pdf |
    - Fig. 26.1.3.8. Variation of the mean figure of $[\langle m\rangle]$ with $[\sin^{2}\theta / \lambda^{2}]$ (p. 763) | html | pdf |
    - Fig. 26.1.3.9. 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. 763) | html | pdf |
    - Fig. 26.1.3.10. The amino-acid sequence of hen egg-white lysozyme (Canfield & Liu, 1965) (p. 764) | html | pdf |
    - Fig. 26.1.3.11. Schematic drawing of the main-chain conformation of lysozyme (p. 764) | html | pdf |
    - Fig. 26.1.3.12. Stereo-photographs of a model of the lysozyme molecule to a scale of 2 cm to 1 Å (p. 765) | html | pdf |
    - Fig. 26.1.4.1. The cell-wall tetrasaccharide with the $[\beta (1\!\rightarrow \!4)]$ glycosidic bond that is hydrolysed by lysozyme indicated (Blake et al (p. 765) | html | pdf |
    - Fig. 26.1.4.2. Inhibitor molecules of lysozyme (Blake et al (p. 767) | html | pdf |
    - Fig. 26.1.4.3. Contemporary drawings of the binding to lysozyme of: (a) β-N-acetylglucosamine and (b) α-N-acetylglucosamine (Blake et al (p. 768) | html | pdf |
    - Fig. 26.1.4.4. Stereo-photographs of a model of the lysozyme molecule showing how a hexasaccharide substrate may bind to the enzyme (p. 769) | html | pdf |
    - Fig. 26.1.4.5. 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. 770) | html | pdf |
  - Tables
    - Table 26.1.2.1. Heavy-atom parameters used in the final phase calculation for the lysozyme structure (p. 752) | html | pdf |
    - Table 26.1.3.1. Structure amplitudes of the $[11_{'}11_{'}L]$ reflections from crystal types I and II (p. 761) | html | pdf |
    - Table 26.1.3.2. Heavy-atom parameters for the 2 Å structure (p. 761) | html | pdf |
    - Table 26.1.3.3. Discrepancies in amino-acid sequences (excluding Asp/Asn) (p. 764) | html | pdf |