title: Statistical mechanics of protein folding with separable energy functions.
abstract: We have initiated an entirely new approach to statistical mechanical models of strongly interacting systems where the configurational parameters and the potential energy function are both constructed so that the canonical partition function can be evaluated analytically. For a simplified model of proteins consisting of a single, fairly short polypeptide chain without cross-links, we can adjust the energy parameters to favor the experimentally determined native state of seven proteins having diverse types of folds. Then 497 test proteins are predicted to have stable native folds, even though they are also structurally diverse, and 480 of them have no significant sequence similarity to any of the training proteins.
authors.affiliation: College of Pharmacy, University of Michigan, Ann Arbor, MI 48109-1065, USA.
authors.forename: Jianyong
authors.initials: J
authors.lastname: Wang
authors.forename: Gordon M
authors.initials: GM
authors.lastname: Crippen
mesh_terms: D008962:Models, Theoretical; D010455:Peptides / Q000235:genetics / Q000378:metabolism; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D013816:Thermodynamics
chemical_list: D010455:Peptides; D011506:Proteins