Stuart M. Rothstein: Research.

TOWARDS THE COMPLETE CLASSIFICATION OF PROTEIN NATIVE STATE CONFORMATIONAL DIVERSITY

The traditional objective in the computational investigation of protein structure is to locate a single conformation at the global minimum in the potential energy. It was commonly believed that the native state of a protein lies at that position on the energy surface. In recent developments it is now believed to be necessary to characterize the distribution of conformations of a protein active site, not just the single conformation at the global minimum. 

A further difficulty is the inefficiency of the widely used simulated annealing method when employed to optimize the structures of proteins, especially those which exhibit a frustrated energy landscape. An exhaustive search of parameter space in such systems is unfeasible, so it is typical for only a handful of runs to be performed on a reasonably sized protein. Even allowing for advances in high performance computer technology and for the development of more efficient Monte Carlo optimization algorithms, it is likely that the problem of incomplete energy distributions and qualitative characterization of low-energy conformations will persist for the foreseeable future. 

Recently we published a pattern recognition technique, “histogram filtering” [Ref. 56] with which to optimize parameters in wave functions for use in quantum Monte Carlo simulations. We are exploiting histogram filtering in conjunction with cluster analysis to a) characterize the low-energy local minimum energy structures, and b) to arrive at a complete description of the distribution of conformations for proteins, without having to take recourse to a very large number of simulated annealing runs.
 

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