Protein structure prediction using mutually orthogonal Latin squares and a genetic algorithm.

J Arunachalam; V Kanagasabai; N Gautham

doi:10.1016/j.bbrc.2006.01.162

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Protein structure prediction using mutually orthogonal Latin squares and a genetic algorithm.

J Arunachalam·V Kanagasabai·N Gautham

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Abstract

We combine a new, extremely fast technique to generate a library of low energy structures of an oligopeptide (by using mutually orthogonal Latin squares to sample its conformational space) with a genetic algorithm to predict protein structures. The protein sequence is divided into oligopeptides, and a structure library is generated for each. These libraries are used in a newly defined mutation operator that, together with variation, crossover, and diversity operators, is used in a modified genetic algorithm to make the prediction. Application to five small proteins has yielded near native structures.

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Algorithms Animals Chickens Computational Biology Melitten Microfilament Proteins Oligopeptides Pancreatic Polypeptide Peptide Library Predictive Value of Tests Protein Conformation Protein Structure, Tertiary Proto-Oncogene Proteins c-myb Tryptophan Comparative Study Journal Article Research Support, Non-U.S. Gov't

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J Arunachalam, V Kanagasabai, N Gautham. 2006-02-08. Protein structure prediction using mutually orthogonal Latin squares and a genetic algorithm.. https://doi.org/10.1016/j.bbrc.2006.01.162

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