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Prediction of peptide conformation by multicanonical algorithm: New approach to the multiple‐minima problem
Author(s) -
Hansmann Ulrich H. E.,
Okamoto Yuko
Publication year - 1993
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.540141110
Subject(s) - maxima and minima , simulated annealing , ergodicity , statistical physics , algorithm , simple (philosophy) , monte carlo method , canonical ensemble , potential energy , chemistry , computer science , mathematics , physics , classical mechanics , quantum mechanics , mathematical analysis , philosophy , statistics , epistemology
We apply a recently developed method, the multicanonical algorithm, to the problem of tertiary structure prediction of peptides and proteins. As a simple example to test the effectiveness of the algorithm, metenkephalin is studied and the ergodicity problem, or multiple‐minima problem, is shown to be overcome by this algorithm. The lowest‐energy conformation obtained agrees with that determined by other efficient methods such as Monte Carlo simulated annealing. The superiority of the present method to simulated annealing lies in the fact that the relationship to the canonical ensemble remains exactly controlled. Once the multicanonical parameters are determined, only one simulation run is necessary to obtain the lowest‐energy conformation and further the results of this one run can be used to calculate various thermodynamic quantities at any temperature. The latter point is demonstrated by the calculation of the average potential energy and specific heat as functions of temperature. © John Wiley & Sons, Inc.