Algorithms for the Discovery and Geometric-Matching of Hierarchical 3-D Templates of Functional Sites in Protein Structures

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The long-term aims of this research are to develop automated algorithms to identify functional sites in protein structures and to characterize protein function on a proteomic scale. The approach is predicated on the Evolutionary Trace method (ET), which uses evolutionary data to identify key functional residues in proteins. These residues form spatial clusters that predict the location of active sites, or of binding sites, and they can be taken as three-dimensional (3-D) templates that may directly suggest functions when recognized in novel structures. This motivates our specific goals to automate and optimize functional site identification and the extraction of 3-D templates by ET (Aim 1); and then to refine algorithms that search for these templates in other structures, and score the quality of matches and the likelihood that they indicate functional similarity based on molecular mimicry (Aim 2). The broader impact of this proposal is manifold. It will strengthen biological research infrastructure, first, by revealing which regions of proteins are most biologically relevant, and hence logical targets for protein engineering and drug design. Second, it will develop a novel method for functional characterization of gene products by extending to three dimensions a functional annotation strategy traditionally bases on one-dimensional pattern matching on protein sequences. In so doing, this work addresses the fundamental problem in "post-genomic biology": that of linking massive and exponentially growing amounts of raw sequence and structure data to the molecular basis of biological function. The proposal will also lead to software that is robust, standardized, and easy to use, and technology transfer will benefit from the channels opened by the collaboration with the PDB. Another activity with broad impact will be the training of undergraduates and graduate students, and participation in programs that support female and minority applications at both Rice and Baylor College of Medicine.