Abstract
Currently there exist several computational methods for predicting the functional sites in a set of homologous proteins based on their sequences. Due to difficulties in defining the functional site in a protein, it is not trivial to compare the performance of these methods, evaluate their limitations and quantify improvements by new approaches. Here, we use extensive mutation data from two proteins, Lac repressor and subtilisin, to perform such an analysis. Along with the evaluation of existing approaches, we describe a site class model of evolution as a tool to predict functional sites in proteins. The results indicate that this model, which simulates the evolution process at the amino acid level using site-specific substitution matrices, provides the most accurate information on functional sites in a given protein family. Secondly, we present an application of this model to neurotransmitter transporters, a superfamily of proteins of which we have limited experimental knowledge. Based on this application we present testable hypotheses regarding the mechanism of action of these proteins.
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