title: Fast protein fold recognition via sequence to structure alignment and contact capacity potentials.
abstract: We propose new empirical scoring potentials and associated alignment procedures for optimally aligning protein sequences to protein structures. The method has two main applications: first, the recognition of a plausible fold for a protein sequence of unknown structure out of a database of representative protein structures and, second, the improvement of sequence alignments by using structural information in order to find a better starting point for homology based modelling. The empirical scoring function is derived from an analysis of a nonredundant database of known structures by converting relative frequencies into pseudoenergies using a normalization according to the inverse Bolzmann law. These-so called contact capacity-potentials turn out to be discriminative enough to detect structural folds in the absence of significant sequence similarity and at the same time simple enough to allow for a very fast optimization in an alignment procedure.
authors.affiliation: Laboratory of Mathematical Biology, NCI-FCRF, Frederick, MD 21702-1201, USA. nicka@ncifcrf.gov
authors.forename: N N
authors.initials: NN
authors.lastname: Alexandrov
authors.forename: R
authors.initials: R
authors.lastname: Nussinov
authors.forename: R M
authors.initials: RM
authors.lastname: Zimmer
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D016208:Databases, Factual; D008969:Molecular Sequence Data; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software; D013816:Thermodynamics
chemical_list: D011506:Proteins