Abstract
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.
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Saunders, J. A., & Scheraga, H. A. (2003). Challenges in structure prediction of oligomeric proteins at the united-residue level: Searching the multiple-chain energy landscape with CSA and CFMC. In Biopolymers (Vol. 68, pp. 318–332). https://doi.org/10.1002/bip.10227
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