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

International Tables for Crystallography (2006). Vol. F. ch. 21.1, pp. 503-504   | 1 | 2 |

Section Miscellaneous

G. J. Kleywegta*

aDepartment of Cell and Molecular Biology, Uppsala University, Biomedical Centre, Box 596, SE-751 24 Uppsala, Sweden
Correspondence e-mail: Miscellaneous

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Many other coordinate-based methods for assessing the validity or correctness of protein models have been developed. These include the profile method of Eisenberg and co-workers (Bowie et al., 1991[link]; Lüthy et al., 1992[link]), the inspection of atomic volumes (Pontius et al., 1996[link]), and the use of threading and other potentials (Sippl, 1993[link]; Melo & Feytmans, 1998[link]; Maiorov & Abagyan, 1998[link]). Some of these methods are described in more detail elsewhere in this volume. The program WHAT IF (Vriend, 1990[link]) contains a large array of quality checks, many of which are not available in other programs, that span the spectrum from administrative checks to global quality indicators (Hooft et al., 1996[link]). During the refinement process, coordinate shifts can be used as a rough indication of `quality' or, rather, convergence (Carson et al., 1994[link]; Kleywegt & Jones, 1996a[link]). Crude models tend to undergo much larger changes during refinement than models that are essentially correct and complete. Also at the residue level, large coordinate shifts indicate residues that are worth a closer look.

Laskowski et al. (1994[link]) have formulated single-number geometrical quality criteria, which they dubbed `G factors' in analogy to crystallographic R values. These G factors combine the results of a number of quality checks (covalent geometry, main-chain and side-chain torsion angles etc.) in a single number.


First citation Bowie, J. U., Lüthy, R. & Eisenberg, D. (1991). A method to identify protein sequences that fold into a known three-dimensional structure. Science, 253, 164–170.Google Scholar
First citation Carson, M., Buckner, T. W., Yang, Z., Narayana, S. V. L. & Bugg, C. E. (1994). Error detection in crystallographic models. Acta Cryst. D50, 900–909.Google Scholar
First citation Hooft, R. W. W., Vriend, G., Sander, C. & Abola, E. E. (1996). Errors in protein structures. Nature (London), 381, 272.Google Scholar
First citation Kleywegt, G. J. & Jones, T. A. (1996a). Efficient rebuilding of protein structures. Acta Cryst. D52, 829–832.Google Scholar
First citation Laskowski, R. A., MacArthur, M. W. & Thornton, J. M. (1994). Evaluation of protein coordinate data sets. In Proceedings of the CCP4 study weekend. From first map to final model, edited by S. Bailey, R. Hubbard & D. A. Waller, pp. 149–159. Warrington: Daresbury Laboratory.Google Scholar
First citation Lüthy, R., Bowie, J. U. & Eisenberg, D. (1992). Assessment of protein models with three-dimensional profiles. Nature (London), 356, 83–85.Google Scholar
First citation Maiorov, V. & Abagyan, R. (1998). Energy strain in three-dimensional protein structures. Fold. Des. 3, 259–269.Google Scholar
First citation Melo, F. & Feytmans, E. (1998). Assessing protein structures with a non-local atomic interaction energy. J. Mol. Biol. 277, 1141–1152.Google Scholar
First citation Pontius, J., Richelle, J. & Wodak, S. J. (1996). Deviations from standard atomic volumes as a quality measure for protein crystal structures. J. Mol. Biol. 264, 121–136.Google Scholar
First citation Sippl, M. J. (1993). Recognition of errors in three-dimensional structures of proteins. Proteins Struct. Funct. Genet. 17, 355–362.Google Scholar
First citation Vriend, G. (1990). WHAT IF: a molecular modeling and drug design program. J. Mol. Graphics, 8, 52–56.Google Scholar

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