Chapter 18.2 Enhanced macromolecular refinement by simulated annealing

Crystallography of biological macromolecules

First Online Edition (2006)

Part 18. Refinement

  1. A. T. Brunger1,
  2. P. D. Adams2,
  3. L. M. Rice3

Published Online: 1 JAN 2006

DOI: 10.1107/97809553602060000694

International Tables for Crystallography

International Tables for Crystallography

How to Cite

Brunger, A. T., Adams, P. D. and Rice, L. M. 2006. Enhanced macromolecular refinement by simulated annealing. International Tables for Crystallography. F:18:18.2:375–381.

Author Information

  1. 1

    The 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

  2. 2

    The Howard Hughes Medical Institute and Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA

  3. 3

    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA

Publication History

  1. Published Online: 1 JAN 2006


The analysis of X-diffraction data generally requires sophisticated computational procedures that culminate in refinement and structure validation. The refinement procedure can be formulated as the chemically constrained or restrained nonlinear optimization of a target function, which usually measures the agreement between observed diffraction data and data computed from an atomic model. The ultimate goal of refinement is to simultaneously optimize the agreement of an atomic model with observed diffraction data and with a priori chemical information. Simulated annealing is an optimization technique particularly well suited to overcoming the multiple minima problem. Unlike gradient-descent methods, simulated annealing can cross barriers between minima and thus can explore a greater volume of the parameter space to find better models (deeper minima). Following its introduction to crystallographic refinement, there have been major improvements of the original method in four principal areas: the measure of model quality, the search of the parameter space, the target function and the modelling of conformational variability. These developments are discussed in this chapter.


  • cross validation;
  • molecular dynamics;
  • multistart refinement;
  • refinement;
  • simulated annealing;
  • structure-factor averaging;
  • target functions;
  • temperature