Conformational Searching

Introduction
When modeling large molecules such as proteins and nucleic acids, one must recognize that the conformational space available to the molecules is so large that it is impossible to identify the structure corresponding to the global energy minimum. Thus, it is desirable to search conformational space to identify structures that correspond to local energy minima.

Conformational search methods can be classified as systematic (deterministic) or stochastic (probabilistic). In systematic search procedures, such as a grid scan search, specified torsion angles are varied over a grid of equally spaced values. When torsion angles are varied systematically over their entire range, a complete picture of the energy landscape can be generated, the quality of which is dependent on the spacing of the grid. However, this method is impractical for more than about four torsion angles, which limits its use to small molecules.

Stochastic search procedures involve random perturbations to a structure. Common implementations include Monte Carlo methods and molecular dynamics. In Monte Carlo methods, random changes in torsion angles are applied as a way to sample different regions of conformational space. In molecular dynamics, the search involves sampling structures at intervals of time during a simulation. Simulated annealing is an application of molecular dynamics designed for conformational searching. In this process, structures are heated to temperatures at which increased atomic motion will occur in an attempt to drive molecules out of their local energy wells. Structures are then cooled slowly to trap them in the new local energy minimum.

On-Line Text
An introduction to conformation searching is provided in The NIH Guide to Molecular Modeling.

Printed References
Elber, R. and Karplus, M. (1987) Multiple Conformational States of Proteins: A Molecular Dynamics Analysis of Myoglobin, Science 235: 318-321.

Leach, A.R. (1991) A Survey of Methods for Searching the Conformational Space of Small and Medium-Sized Molecules, in, Reviews in Computational Chemistry, Vol.2, Lipkowitz, K.B. and Boyd, D.B., eds. VCH Publishers, New York, pp. 1-55.