Conformational Search of Peptides and Proteins:Monte Carlo Minimization with an Adaptive Bias Method Applied to the Heptapeptide Deltorphin

摘要

The energy function of a protein consists of a tremendous number of minima.Locating the global energy minimum(GEM)structure,which corresponds approximately to the native structure,is a severe problem in global optimization.Recently we have proposed a conformational search technique based on the Monte Carlo minimization(MCM)method of Li and Scheraga,where trial dihedral angles are not selected at random within the range [-180 deg,180deg](as with MCM)but with biased probabilites depending on the increased structure-energy correlations as the GEM is approached during the search.This method,called the Monte Carlo minimization with an adaptive bias (MCMAB),was applied initially to the pentapeptide Leu-enkephalin.Here we study its properties further by applying it to the larger peptide with bulky side chains,deltophin(H-Tyr-D-Met-Phe-His-Leu-Met-Asp-NH_2).We find that on average the number of energy minimizations required by MCMAB to locate the GEM for the first time is smaller by a factor of approximately three than the number required by MCM-in accord with results obtained for Leu-enkephalin.