Enhanced macromolecular refinement by simulated annealing

Abstract

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. This chapter is also available as HTML from the International Tables Online site hosted by the IUCr.