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

International Tables for Crystallography (2006). Vol. F, ch. 18.2, p. 381   | 1 | 2 |

Section 18.2.8. Conclusions

A. T. Brunger,a* P. D. Adamsb and L. M. Ricec

aThe Howard Hughes Medical Institute, and Departments of Molecular and Cellular Physiology, Neurology and Neurological Sciences, and Stanford Synchrotron Radiation Laboratory, Stanford Universty, 1201 Welch Road, MSLS P210, Stanford, CA 94305-5489, USA,bThe Howard Hughes Medical Institute and Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA, and cDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA
Correspondence e-mail:

18.2.8. Conclusions

| top | pdf |

Simulated annealing has dramatically improved the efficiency of crystallographic refinement. A case in point is the combination of torsion-angle molecular dynamics with cross-validated maximum-likelihood targets. These two independent developments interact synergistically to produce less model bias than any other method to date. The combined method dramatically increases the radius of convergence, allowing the productive refinement of poor initial models, e.g. those obtained by weak molecular-replacement solutions (Rice & Brünger, 1994[link]; Adams et al., 1997[link], 1999[link]).

Simulated annealing can also be used to provide new physical insights into molecular function which may depend on conformational variability. The sampling characteristics of simulated annealing allow the generation of multi-conformer models that can represent molecular motion and discrete disorder, especially when combined with the acquisition of high-quality data (Burling et al., 1996[link]). Thus, simulated annealing is also a stepping stone towards development of improved models of macromolecules in solution and in the crystalline state.

The computational developments discussed in this review are implemented in the software suite Crystallography & NMR System (Brunger et al., 1998[link]). A pre-release of the software suite is available upon request.


Adams, P. D., Pannu, N. S., Read, R. J. & Brünger, A. T. (1997). Cross-validated maximum likelihood enhances crystallographic simulated annealing refinement. Proc. Natl Acad. Sci. USA, 94, 5018–5023.Google Scholar
Adams, P. D., Pannu, N. S., Read, R. J. & Brunger, A. T. (1999). Extending the limits of molecular replacement through combined simulated annealing and maximum-likelihood refinement. Acta Cryst. D55, 181–190.Google Scholar
Brunger, A. T., Adams, P. D., Clore, G. M., DeLano, W. L., Gros, P., Grosse-Kunstleve, R. W., Jiang, J.-S., Kuszewski, J., Nilges, M., Pannu, N. S., Read, R. J., Rice, L. M., Simonson, T. & Warren, G. L. (1998). Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Cryst. D54, 905–921.Google Scholar
Burling, F. T., Weis, W. I., Flaherty, K. M. & Brunger, A. T. (1996). Direct observation of protein solvation and discrete disorder with experimental crystallographic phases. Science, 271, 72–77.Google Scholar
Hsu, I. N., Delbaere, L. T. J., James, M. N. G. & Hoffman, T. (1977). Penicillopepsin from Penicillium janthinellum crystal structure at 2.8 Å and sequence homology with porcine pepsin. Nature (London), 266, 140–145.Google Scholar
Kleywegt, G. J. & Brunger, A. T. (1996). Cross-validation in crystallography: practice and applications. Structure, 4, 897–904.Google Scholar
Luzzati, V. (1952). Traitement statistique des erreurs dans la determination des structures cristallines. Acta Cryst. 5, 802–810.Google Scholar
Read, R. J. (1986). Improved Fourier coefficients for maps using phases from partial structures with errors. Acta Cryst. A42, 140–149.Google Scholar
Rice, L. M. & Brunger, A. T. (1994). Torsion angle dynamics: reduced variable conformational sampling enhances crystallographic structure refinement. Proteins Struct. Funct. Genet. 19, 277–290.Google Scholar
Suguna, K., Bott, R. R., Padlan, E. A., Subramanian, E., Sheriff, S., Cohen, G. H. & Davies, D. R. (1987). Structure and refinement at 1.8 Å resolution of the aspartic proteinase from Rhizopus chinensis. J. Mol. Biol. 196, 877–900.Google Scholar

to end of page
to top of page