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A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70%
Author(s) -
Mehta Perdeep K.,
Heringa Jaap,
Argos Patrick
Publication year - 1995
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.5560041208
Subject(s) - protein secondary structure , protein structure prediction , correctness , protein structure , protein design , robustness (evolution) , loop modeling , algorithm , biological system , mathematics , computer science , crystallography , biology , chemistry , genetics , biochemistry , gene
To improve secondary structure predictions in protein sequences, the information residing in multiple sequence alignments of substituted but structurally related proteins is exploited. A database comprised of 70 protein families and a total of 2, 500 sequences, some of which were aligned by tertiary structural superpositions, was used to calculate residue exchange weight matrices within α ‐helical, β ‐strand, and coil substructures, respectively. Secondary structure predictions were made based on the observed residue substitutions in local regions of the multiple alignments and the largest possible associated exchange weights in each of the three matrix types. Comparison of the observed and predicted secondary structure on a per‐residue basis yielded a mean accuracy of 72.2%. Individual α ‐helix, β ‐strand, and coil states were respectively predicted at 66.4, 66.7, and 75.8°7o correctness, representing a well‐balanced three‐state prediction. The accuracy level, verified by cross‐validation through jack‐knife tests on all protein families, dropped, on average, to only 70.9%, indicating the rigor of the prediction procedure. On the basis of robustness, conceptual clarity, accuracy, and executable efficiency, the method has considerable advantage, especially with its sole reliance on amino acid substitutions within structurally related proteins.

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