International
Tables for
Crystallography
Volume F
Crystallography of biological macromolecules
Edited by M. G. Rossmann and E. Arnold

International Tables for Crystallography (2006). Vol. F. ch. 22.1, pp. 537-538   | 1 | 2 |

Section 22.1.1.5.1. Using volume to measure packing efficiency

M. Gersteina* and F. M. Richardsa

22.1.1.5.1. Using volume to measure packing efficiency

| top | pdf |

Volume calculations are principally applied in measuring packing. This is because the packing efficiency of a given atom is simply the ratio of the space it could minimally occupy to the space that it actually does occupy. As shown in Fig. 22.1.1.8[link], this ratio can be expressed as the VDW volume of an atom divided by its Voronoi volume (Richards, 1974[link], 1985[link]; Richards & Lim, 1994[link]). (Packing efficiency also sometimes goes by the equivalent terms `packing density' or `packing coefficient'.) This simple definition masks considerable complexities – in particular, how does one determine the volume of the VDW envelope (Petitjean, 1994[link])? This requires knowledge of what the VDW radii of atoms are, a subject on which there is not universal agreement (see above), especially for water molecules and polar atoms (Gerstein et al., 1995[link]; Madan & Lee, 1994[link]).

[Figure 22.1.1.8]

Figure 22.1.1.8 | top | pdf |

Packing efficiency. (a) The relationship between Voronoi polyhedra and packing efficiency. Packing efficiency is defined as the volume of an object as a fraction of the space that it occupies. (It is also known as the `packing coefficient' or `packing density'.) In the context of molecular structure, it is measured by the ratio of the VDW volume ([V_{\rm VDW}], shown by a light grey line) and Voronoi volume ([V_{\rm Vor}], shown by a dotted line). This calculation gives absolute packing efficiencies. In practice, one usually measures a relative efficiency, relative to the atom in a reference state: [(V_{\rm VDW}/V_{\rm Vor})/[V_{\rm VDW}/V_{\rm Vor}\hbox{(ref)}]]. Note that in this ratio the unchanging VDW volume of an atom cancels out, leaving one with just a ratio of two Voronoi volumes. Perhaps more usefully, when one is trying to evaluate the packing efficiency P at an interface, one computes [P = p \textstyle\sum\displaystyle V_{i}/\textstyle\sum\displaystyle v_{i}], where p is packing efficiency of the reference data set (usually 0.74), [V_{i}] is the actual measured volume of each atom i at the interface and [v_{i}] is the reference volume corresponding to the type of atom i. (b) A graphical illustration of the difference between tight packing and loose packing. Frames from a simulation are shown for liquid water (left) and for liquid argon, a simple liquid (right). Owing to its hydrogen bonds, water is much less tightly packed than argon (packing efficiency of 0.35 versus ∼0.7). Each water molecule has only four to five nearest neighbours while each argon atom has about ten.

Knowing that the absolute packing efficiency of an atom is a certain value is most useful in a comparative sense, i.e. when comparing equivalent atoms in different parts of a protein structure. In taking a ratio of two packing efficiencies, the VDW envelope volume remains the same and cancels. One is left with just the ratio of space that an atom occupies in one environment to what it occupies in another. Thus, for the measurement of packing, standard reference volumes are particularly useful. Recently calculated values of these standard volumes are shown in Tables 22.1.1.3[link] and 22.1.1.4[link] for atoms and residues (Tsai et al., 1999[link]).

Table 22.1.1.3 | top | pdf |
Standard residue volumes

The mean standard volume, the standard deviation about the mean and the frequency of occurrence of each residue in the protein core are given. Considering cysteine (Cyh, reduced) to be chemically different from cystine (Cys, involved in a disulfide and hence oxidized) gives 21 different residues. These residue volumes are adapted from the ProtOr parameter set (also known as the BL+ set) in Tsai et al. (1999)[link] and Tsai et al. (2001)[link]. For this set, the averaging is done over 87 representative high-resolution crystal structures, only buried atoms not in contact with ligands are selected, the radii set shown in the last column of Table 22.1.1.1[link] is used and the volumes are computed in the presence of the crystal water. The frequencies for buried residues are from Harpaz et al. (1994[link]).

Residue Volume (Å3) Standard deviation (Å3) Frequency (%)
Ala 89.3 3.5 13
Val 138.2 4.8 13
Leu 163.1 5.8 12
Gly 63.8 2.7 11
Ile 163.0 5.3 9
Phe 190.8 4.8 6
Ser 93.5 3.9 6
Thr 119.6 4.2 5
Tyr 194.6 4.9 3
Asp 114.4 3.9 3
Cys 102.5 3.5 3
Pro 121.3 3.7 3
Met 165.8 5.4 2
Trp 226.4 5.3 2
Gln 146.9 4.3 2
His 157.5 4.3 2
Asn 122.4 4.6 1
Glu 138.8 4.3 1
Cyh 112.8 5.5 1
Arg 190.3 4.7 1
Lys 165.1 6.9 1

Table 22.1.1.4 | top | pdf |
Standard atomic volumes

Tsai et al. (1999)[link] and Tsai et al. (2001)[link] clustered all the atoms in proteins into the 18 basic types shown below. Most of these have a simple chemical definition, e.g. `=O' are carbonyl carbons. However, some of the basic chemical types, such as the aromatic CH group (`[\geq\!\hbox{CH}]'), need to be split into two subclusters (bigger and smaller), as is indicated by the column labelled `Cluster'. Volume statistics were accumulated for each of the 18 types based on averaging over 87 high-resolution crystal structures (in the same fashion as described for the residue volumes in Table 22.1.1.3)[link]. No. is the number of atoms averaged over. The final column (`Symbol') gives the standardized symbol used to describe the atom in Tsai et al. (1999)[link]. The atom volumes shown here are part of the ProtOr parameter set (also known as the BL+ set) in Tsai et al. (1999)[link].

Atom type Cluster Description Average volume (Å3) Standard deviation (Å3) No. Symbol
>C= Bigger Trigonal (unbranched), aromatics 9.7 0.7 4184 C3H0b
>C= Smaller Trigonal (branched) 8.7 0.6 11876 C3H0s
[\geq \!\hbox{CH}] Bigger Aromatic, CH (facing away from main chain) 21.3 1.9 2063 C3H1b
[\geq\!\hbox{CH}] Smaller Aromatic, CH (facing towards main chain) 20.4 1.7 1742 C3H1s
>CH— Bigger Aliphatic, CH (unbranched) 14.4 1.3 3642 C4H1b
>CH— Smaller Aliphatic, CH (branched) 13.2 1.0 7028 C4H1s
—CH2 Bigger Aliphatic, methyl 24.3 2.1 1065 C4H2b
—CH2 Smaller Aliphatic, methyl 23.2 2.3 4228 C4H2s
—CH3   Aliphatic, methyl 36.7 3.2 3497 C4H3u
>N—   Pro N 8.7 0.6 581 N3H0u
>NH Bigger Side chain NH 15.7 1.5 446 N3H1b
>NH Smaller Peptide 13.6 1.0 10016 N3H1s
—NH2   Amino or amide 22.7 2.1 250 N3H2u
[\hbox{--NH}_{3}^{+}]   Amino, protonated 21.4 1.2 8 N4H3u
=O   Carbonyl oxygen 15.9 1.3 7872 O1H0u
—OH   Alcoholic hydroxyl 18.0 1.7 559 O2H1u
—S—   Thioether or –S–S– 29.2 2.6 263 S2H0u
—SH   Sulfhydryl 36.7 4.2 48 S2H1u

In analysing molecular systems, one usually finds that close packing is the default (Chandler et al., 1983[link]), i.e. atoms pack like billiard balls. Unless there are highly directional interactions (such as hydrogen bonds) that have to be satisfied, one usually achieves close packing to optimize the attractive tail of the VDW interaction. Close-packed spheres of the same size have a packing efficiency of ∼0.74. Close-packed spheres of different size are expected to have a somewhat higher packing efficiency. In contrast, water is not close-packed because it has to satisfy the additional constraints of hydrogen bonding. It has an open, tetrahedral structure with a packing efficiency of ∼0.35. (This difference in packing efficiency is illustrated in Fig. 22.1.1.8b[link])

References

First citation Chandler, D., Weeks, J. D. & Andersen, H. C. (1983). van der Waals picture of liquids, solids, and phase transformations. Science, 220, 787–794.Google Scholar
First citation Gerstein, M., Tsai, J. & Levitt, M. (1995). The volume of atoms on the protein surface: calculated from simulation, using Voronoi polyhedra. J. Mol. Biol. 249, 955–966.Google Scholar
First citation Madan, B. & Lee, B. (1994). Role of hydrogen bonds in hydrophobicity: the free energy of cavity formation in water models with and without the hydrogen bonds. Biophys. Chem. 51, 279–289.Google Scholar
First citation Petitjean, M. (1994). On the analytical calculation of van der Waals surfaces and volumes: some numerical aspects. J. Comput. Chem. 15, 1–10.Google Scholar
First citation Richards, F. M. (1974). The interpretation of protein structures: total volume, group volume distributions and packing density. J. Mol. Biol. 82, 1–14.Google Scholar
First citation Richards, F. M. (1985). Calculation of molecular volumes and areas for structures of known geometry. Methods Enzymol. 115, 440–464.Google Scholar
First citation Richards, F. M. & Lim, W. A. (1994). An analysis of packing in the protein folding problem. Q. Rev. Biophys. 26, 423–498.Google Scholar
First citation Tsai, J., Taylor, R., Chothia, C. & Gerstein, M. (1999). The packing density in proteins: standard radii and volumes. J. Mol. Biol. 290, 253–266.Google Scholar








































to end of page
to top of page