A segment-based approach to protein secondary structure prediction.

S R Presnell; B I Cohen; F E Cohen

doi:10.1021/bi00119a006

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A segment-based approach to protein secondary structure prediction.

S R Presnell·B I Cohen·F E Cohen

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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.

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Algorithms Amino Acid Sequence Humans Molecular Sequence Data Protein Conformation Proteins Software Structure-Activity Relationship Journal Article Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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S R Presnell, B I Cohen, F E Cohen. 1992-02-04. A segment-based approach to protein secondary structure prediction.. https://doi.org/10.1021/bi00119a006

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