CONFORMATIONAL SEARCHES FOR THE GLOBAL MINIMUM OF PROTEIN MODELS

The conformational space of two protein structures has been examined using a stochastic search method in an effort to locate the global minimum conformation. In order to reduce this optimization problem to a tractable level, we have implemented a simplified force field representation of the protein structure that drastically reduces the degrees of freedom. The model replaces each amino acid (containing many atoms) with a single sphere centered on the C(alpha) position. These spheres are connected by virtual bonds, producing a ''string of beads'' model of the peptide chain. This model has been coupled with our stochastic search method to globally optimize the conformation of two common structural motifs found in proteins, a 22-residue alpha-helical hairpin and a 46-residue beta-barrel. The search method described further reduces the optimization problem by taking advantage of the rotational isomerisms associated with molecular conformations and stochastically explores the energy surface using internal, torsional degrees of freedom. The approach proved to be highly efficient for globally optimizing the conformation of the alpha-helical hairpin and beta-barrel structure on a moderately powered workstation. The results were further verified by applying variations in the search strategy that probed the low energy regions of conformational space near the suspected global minimum. Since this method also provides information regarding the low energy conformers, we have presented an analysis of the structures populated, and brief comparisons with other work. Finally, we applied the method to globally optimize the conformation of a 9-residue peptide fragment using a popular all-atom representation and successfully located the global minimum consistent with results from previous work.