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

S. Banu Ozkan, Hagai Meirovitch

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

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°, 180°] (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-NH2). 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.

Original languageEnglish (US)
Pages (from-to)565-572
Number of pages8
JournalJournal of Computational Chemistry
Volume25
Issue number4
DOIs
StatePublished - Mar 2004
Externally publishedYes

Keywords

  • Conformational search
  • Energy minimization
  • Global energy minimum
  • Monte Carlo
  • Protein folding

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Mathematics

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