title: Statistical theory for protein ensembles with designed energy landscapes.
abstract: Combinatorial protein libraries provide a promising route to investigate the determinants and features of protein folding and to identify novel folding amino acid sequences. A library of sequences based on a pool of different monomer types are screened for folding molecules, consistent with a particular foldability criterion. The number of sequences grows exponentially with the length of the polymer, making both experimental and computational tabulations of sequences infeasible. Herein a statistical theory is extended to specify the properties of sequences having particular values of global energetic quantities that specify their energy landscape. The theory yields the site-specific monomer probabilities. A foldability criterion is derived that characterizes the properties of sequences by quantifying the energetic separation of the target state from low-energy states in the unfolded ensemble and the fluctuations of the energies in the unfolded state ensemble. For a simple lattice model of proteins, excellent agreement is observed between the theory and the results of exact enumeration. The theory may be used to provide a quantitative framework for the design and interpretation of combinatorial experiments.
authors.affiliation: Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA. pbiswas@chemistry.du.ca.in
authors.forename: Parbati
authors.initials: P
authors.lastname: Biswas
authors.forename: Jinming
authors.initials: J
authors.lastname: Zou
authors.forename: Jeffery G
authors.initials: JG
authors.lastname: Saven
mesh_terms: D015233:Models, Statistical; D008962:Models, Theoretical; D019151:Peptide Library; D017510:Protein Folding; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D019151:Peptide Library