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A model of local‐minima distribution on conformational space and its application to protein structure prediction
Author(s) -
Li Hongzhi
Publication year - 2006
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.21084
Subject(s) - decoy , maxima and minima , protein structure prediction , conformational ensembles , statistical physics , distribution (mathematics) , energy landscape , algorithm , biological system , protein structure , molecular dynamics , mathematics , chemistry , computational chemistry , physics , thermodynamics , mathematical analysis , biochemistry , receptor , biology
A quantitative two‐parameter model is developed to describe local energy minima distribution. On a conformational space measured by least‐square‐fitting root‐mean‐squared distance (RMSD), the number of local minima in a r RMSD region is proposed to be proportional to exp (− 1 / r ). As part of the model derivations, the minimum RMSD of decoys from the largest cluster, the number of decoys in the largest cluster, and the RMSD distribution of the decoys have inner connections with each other. The model is successfully verified on a 49 helix‐packing decoy set and a 30 loop‐prediction decoy set, as well as both knowledge‐based potential (DFIRE) and physical force‐fields (OPLS and CHARMM). One of the model's applications is predicting behaviors of a large amount of decoys (e.g., minimum RMSD of 40,000 decoys) by generating only a small number of decoys (e.g., 500). It may be applied to structure predictions guided by any Lennard‐Jones‐like potential functions and can be extended to other sampling methods guided by simple energy terms. Proteins 2006. © 2006 Wiley‐Liss, Inc.