A comprehensive analysis of structure-function relationships in membrane protein families

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In spite of their crucial importance membrane-bound proteins encoded in complete genomes are relatively poorly annotated compared to globular proteins. The main goal of the present proposal is to build a general bioinformatics workbench for investigating membrane protein families at large scale. Based on our previous work in systematic genome analysis we intend to develop a comprehensive and hierarchical membrane protein family classification and provide appropriate bioinformatics instruments ¿ multiple sequence alignments, Hidden Markov Models ¿ for investigating aspects of their structure and function. In particular, alignment algorithms specifically taking into account predicted structural features ¿ such as hydrophobic transmembrane segments ¿ will be designed. Furthermore we plan to develop advanced approaches for predicting the precise functional specificity of membrane proteins. Correlated mutation analysis will be applied to explore the networks of inter-correlated residues, determine the residues that confer functional specificity, and to identify functional subtypes within each sequence family. In parallel, specificity-determining residues will be delineated from multiply aligned sequences using a novel automatic approach based on the genetic algorithm that does not require a priori knowledge on functional sub-groups in a given family. Accurate function prediction is an important pre-requisite for constructing drugs capable of blocking specific channels and transport systems of the cell. Another potential application for the methods and data generated in this work will be target selection for structural genomics of membrane proteins. In addition, the results of this project will be useful for constructing molecular models for numerous families of membrane proteins, investigating helix packing, and oligomerization interfaces.