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Statistical mechanics of protein folding by cluster distance geometry
Author(s) -
Crippen Gordon M.
Publication year - 2004
Publication title -
biopolymers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 125
eISSN - 1097-0282
pISSN - 0006-3525
DOI - 10.1002/bip.20118
Subject(s) - chemistry , partition function (quantum field theory) , protein folding , statistical potential , pairwise comparison , folding funnel , lattice protein , folding (dsp implementation) , native state , cluster (spacecraft) , partition (number theory) , statistical mechanics , similarity (geometry) , function (biology) , statistical physics , energy (signal processing) , downhill folding , crystallography , protein structure , combinatorics , protein structure prediction , physics , quantum mechanics , phi value analysis , mathematics , artificial intelligence , image (mathematics) , computer science , engineering , biology , biochemistry , evolutionary biology , programming language , statistics , electrical engineering
This is our second type of model for protein folding where the configurational parameters and the effective potential energy function are chosen in such a way that all conformations are described and the canonical partition function can be evaluated analytically. Structure is described in terms of distances between pairs of sequentially contiguous blocks of eight residues, and all possible conformations are grouped into 71 subsets in terms of bounds on these distances. The energy is taken to be a sum of pairwise interactions between such blocks. The 210 energy parameters were adjusted so that the native folds of 32 small proteins are favored in free energy over the denatured state. We then found 146 proteins having negligible sequence similarity to any of the training proteins, yet the free energy of the respective correct native states were favored over the denatured state. © 2004 Wiley Periodicals, Inc. Biopolymers, 2004