A segment-based approach to protein secondary structure prediction.
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.
Presnell
S R
SR
Department of Pharmaceutical Chemistry, University of California, San Francisco 94143.
Cohen
B I
BI
Cohen
F E
FE
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
D011506:Proteins