Secondary structure of proteins and three-dimensional pattern recognition.
We describe a new, parameter-free, method to predict the secondary structure of a protein. It is based on the recognition of well-defined pentapeptides, which allows the discrimination of alpha helices, beta sheets and random coils in proteins. Presently, a success rate of about 65% is achieved for a three-state model.
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Université Claude Bernard, Villeurbanne, 69622, France.
Angélica Soto
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Tohá
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D000465:Algorithms; D000818:Animals; D008956:Models, Chemical; D017433:Protein Structure, Secondary