title: Challenges in structure prediction of oligomeric proteins at the united-residue level: searching the multiple-chain energy landscape with CSA and CFMC.
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.
authors.affiliation: Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853-1301.
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Saunders
authors.forename: Harold A
authors.initials: HA
authors.lastname: Scheraga
mesh_terms: D000465:Algorithms; D019281:Dimerization; D016350:Leucine Zippers; D008958:Models, Molecular; D009010:Monte Carlo Method; D017434:Protein Structure, Tertiary; D021122:Protein Subunits / Q000737:chemistry; D011506:Proteins / Q000737:chemistry*
chemical_list: D021122:Protein Subunits; D011506:Proteins