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Prediction of homology and divergence in the secondary structure of polypeptides.
Author(s) -
S. Pongor,
Aladar A. Szalay
Publication year - 1985
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.82.2.366
Subject(s) - protein secondary structure , alpha helix , matthews correlation coefficient , divergence (linguistics) , amino acid , homology (biology) , peptide sequence , computational biology , protein structure , protein superfamily , protein structure prediction , biology , genetics , gene , biochemistry , artificial intelligence , computer science , support vector machine , linguistics , philosophy
A quantitative procedure is described for the comparison of secondary structure of homologous proteins. Standard predictive methods are used to generate probability profiles from pairs of homologous amino acid sequences; correlation coefficients (R) are then computed between each pair of amino acids for alpha-helix (R alpha), extended structure (R beta), turn (R(t)), and coil (R(c)). R values are >0.2 for correctly aligned homologous sequences. Unrelated or incorrectly aligned sequences give R values near zero. Lack of correlation for a segment of otherwise well-correlated sequences is used to identify structural divergence, which is then evaluated graphically by using difference profiles. A combination of these techniques correctly predicts secondary structural differences between melittin or beta-endorphin and their respective synthetic analogs. The method is potentially useful to describe evolutionary changes in protein secondary structure as well as in the design of peptide analogs.

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