title: A segment-based approach to protein secondary structure prediction.
abstract: Amino acid sequence patterns have been used to identify the location of turns in globular proteins [Cohen et al. (1986) Biochemistry 25, 266-275]. We have developed sequence patterns that facilitate the prediction of helices in all helical proteins. Regular expression patterns recognize the component parts of a helix: the amino terminus (N-cap), the core of the helix (core), and the carboxy terminus (C-cap). These patterns recognize the core features of helices with a 95% success rate and the N- and C-capping features with success rates of 56% and 48%, respectively. A metapattern language, ALPPS, coordinates the recognition of turns and helical components in a scheme that predicts the location and extent of alpha-helices. On the basis of raw residue scoring, a 71% success rate is observed. By focusing on the recognition of core helical features, we achieve a 78% success rate. Amended scoring procedures are presented and discussed, and comparisons are made to other predictive schemes.
authors.affiliation: Department of Pharmaceutical Chemistry, University of California, San Francisco 94143.
authors.forename: S R
authors.initials: SR
authors.lastname: Presnell
authors.forename: B I
authors.initials: BI
authors.lastname: Cohen
authors.forename: F E
authors.initials: FE
authors.lastname: Cohen
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D006801:Humans; D008969:Molecular Sequence Data; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins