Protein folding stochastic optimization

Summary. We recently developed an all-atom free energy force field (PFFOl) for protein structure prediction with stochastic optimization methods. We demonstrated that PFFOl correctly predicts the native conformation of several proteins as the global optimum of the free energy surface. Here we review recent folding studies, which permitted the reproducible all-atom folding of the 20 amino-acid trp-cage protein, the 40-amino acid three-helix HIV accessory protein and the sixty amino acid bacterial ribosomal protein L20 with a variety of stochastic optimization methods. These results demonstrate that all-atom protein folding can be achieved with present day computational resources for proteins of moderate size. 

This review indicates that all-atom protein structure prediction with stochastic optimization methods becomes feasible with present-day computational resources. The fact that three proteins were reproducibly folded with different optimization methods to near-native conformation increases the confidence in the parameterization of our all-atom protein force field PFFOl. The... 

A. Schug, A. Verma, T. Herges, and W. Wenzel. Comparison of stochastic optimization methods for all-atom folding of the trp-cage protein, submitted to Proteins, 2005. 

In the literature, some computer models describing the evolution of copolymer sequences have been proposed [26,28]. Most of them are based on a stochastic Monte Carlo optimization principle (Metropolis scheme) and aimed at the problems of protein physics. Such optimization algorithms start with arbitrary sequences and proceed by making random substitutions biased to minimize relative potential energy of the initial sequence and/or to maximize the folding rate of the target structure. 

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