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Опубликовано 2006-05-21 Опубликовано на SciPeople2009-11-21 05:27:08 ЖурналOMICS: A Journal of Integrative Biology

New approach to predict enzyme function without the alignment
Fomenko A.E., Filimonov D.A., Sobolev B.N., Poroikov V.V. / Vladimir Poroikov
OMICS: A Journal of Integrative Biology, 2006, 10 (1), 56-65.
Аннотация We propose a new approach to predict functional specificity of proteins from their amino acid sequences. Our approach is based on two things: structural Multilevel Neighborhoods of Atom (MNA) descriptors and an original Bayesian algorithm. Usually, a protein sequence is presented as a string of amino acid symbols. Here we introduce a new description of an amino acid sequence: a set of structural MNA descriptors. The MNA descriptor is a string describing an atom and its neighbor atoms according to the selected level. In this work, we also use description of a protein sequence as a set of peptides (strings of amino acid symbols). We performed a case study on two subsubclasses of enzyme nomenclature (EC). It is shown that B-statistics give a sufficient predictive power of enzyme specificity prediction for both MNA descriptors and peptides. We also showed that MNA descriptors give higher accuracy values in comparison with peptides and also provide a choice of MNA descriptor levels for best accuracy prediction. The highest average accuracy prediction that was achieved was 0.98.
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