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Challenges in structure prediction of oligomeric proteins at the united‐residue level: Searching the multiple‐chain energy landscape with CSA and CFMC
Author(s) -
Saunders Jeffrey A.,
Scheraga Harold A.
Publication year - 2003
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.10227
Subject(s) - chemistry , monte carlo method , simulated annealing , dimer , energy landscape , population , energy minimization , cluster analysis , statistical physics , computational biology , computational chemistry , algorithm , computer science , biochemistry , artificial intelligence , physics , mathematics , biology , statistics , demography , organic chemistry , sociology
A revised version of the Conformational Space Annealing (CSA) global optimization method is developed, with three separate measures of structural similarity, in order to overcome the inability of a single distance measure to evaluate multiple‐chain protein structures adequately. A second search method, Conformational Family Monte Carlo (CFMC), involving genetic‐type moves, Monte Carlo‐with‐minimization perturbations, and explicit clustering of the population into conformational families, is adapted to treat multiple‐chain proteins. These two methods are applied to two oligomeric proteins, the retro‐GCN4 leucine zipper and the synthetic domain‐swapped dimer. CFMC proves superior to CSA in its search for low‐energy representatives of its conformational families, but both methods encounter difficulty in finding the native packing arrangements in the absence of native‐like symmetry constraints, even when native monomers are present in the population. © 2003 Wiley Periodicals, Inc. Biopolymers: 318–332, 2003