Automated Annotation of Function in Protein Structures from Evolutionary-based 3D-Templates

PI Olivier Lichtarge, Baylor College of MedicineCo-PI Lydia Kavraki, Rice UniveristyThe goals of this project are to develop automated algorithms to identify functional sites in protein structures and to characterize protein function on a genome scale. The approach is predicated on the Evolutionary Trace method (ET) to locate functional sites in structures. Past NSF support enabled to automate functional site analysis with ET; the extraction of 3D-templates of residues; the search in other structures for geometric matches to these templates; and the statistical likelihood that matched structures perform the function associated with the template. Taken together these steps create a complete, automated functional annotation pipeline that motivates the new goals: to optimize the extraction of 3-D templates that capture the necessary and sufficient determinants of function (Aim 1); to add new template information into our matching algorithms to better evaluate whether molecular mimicry underlies functional similarity (Aim 2); and the development of novel strategies that use multiple templates to identify function (Aim 3). The broader impact of this proposal is manifold. It will strengthen biological research infrastructure 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 based on one-dimensional pattern matching in protein sequences. The proposal will also lead to software that is robust, standardized, and easy to use. High-school, undergraduates and graduate students will participate in the development of the system. The project will broaden participation using campus programs that attract female and minority applications and are being offered at both institutions.

PI Olivier Lichtarge, Baylor College of MedicineCo-PI Lydia Kavraki, Rice UniveristyThe goals of this project are to develop automated algorithms to identify functional sites in protein structures and to characterize protein function on a genome scale. The approach is predicated on the Evolutionary Trace method (ET) to locate functional sites in structures. Past NSF support enabled to automate functional site analysis with ET; the extraction of 3D-templates of residues; the search in other structures for geometric matches to these templates; and the statistical likelihood that matched structures perform the function associated with the template. Taken together these steps create a complete, automated functional annotation pipeline that motivates the new goals: to optimize the extraction of 3-D templates that capture the necessary and sufficient determinants of function (Aim 1); to add new template information into our matching algorithms to better evaluate whether molecular mimicry underlies functional similarity (Aim 2); and the development of novel strategies that use multiple templates to identify function (Aim 3). The broader impact of this proposal is manifold. It will strengthen biological research infrastructure 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 based on one-dimensional pattern matching in protein sequences. The proposal will also lead to software that is robust, standardized, and easy to use. High-school, undergraduates and graduate students will participate in the development of the system. The project will broaden participation using campus programs that attract female and minority applications and are being offered at both institutions.