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Protein inherent structures by different minimization strategies
Author(s) -
Rao Francesco
Publication year - 2010
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.21691
Subject(s) - maxima and minima , discretization , computer science , minification , energy minimization , snapshot (computer storage) , cluster analysis , potential energy , molecular dynamics , algorithm , energy landscape , statistical physics , mathematical optimization , population , computational chemistry , mathematics , chemistry , physics , artificial intelligence , classical mechanics , mathematical analysis , biochemistry , operating system , demography , sociology
Network‐based methods provide an accurate description of the free‐energy landscape of peptides and proteins sampled by molecular dynamics simulations. To that end, it is necessary to group the individual snapshots in a meaningful way. The inherent structures (ISs) provide an appropriate discretization of the trajectory into microstates, avoiding problems that can arise in clustering algorithms that have been used previously. In this work, different minimization protocols to obtain the IS of a peptide are investigated on the basis of cut‐based free‐energy profiles. It is found that a computationally more efficient quasi‐Newtonian algorithm provides quantitative agreement to the classical conjugate gradient method in terms of the population of the peptide substates and the energy barriers separating them. That is, despite the fact that the two algorithms can occasionally quench a given peptide snapshot in different potential energy minima, the overall properties of the system are not affected. As reported by others, atom permutations affect the calculation of the IS, requiring an improved implementation of current potential energy functions. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011