Conformational search of peptides and proteins: Monte Carlo minimization with an adaptive bias method applied to the heptapeptide deltorphin.
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 degrees,180 degrees ] (as with MCM) but with biased probabilities 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, deltorphin (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.
Ozkan
S Banu
SB
Center for Computational Biology and Bioinformatics & Department of Molecular Genetics and Biochemistry, University of Pittsburgh School of Medicine, BST W1058, Pittsburgh, Pennsylvania 15261, USA.
Meirovitch
Hagai
H
D000465:Algorithms; D004743:Enkephalin, Leucine / Q000737:chemistry; D008958:Models, Molecular; D009010:Monte Carlo Method; D009842:Oligopeptides / Q000737:chemistry*; D010455:Peptides / Q000737:chemistry; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry; D013816:Thermodynamics
D009842:Oligopeptides; D010455:Peptides; D011506:Proteins; C059567:deltorphin; D004743:Enkephalin, Leucine