ABI Innovation: Synergistic application of cheminformatics and computational geometry approaches for predicting protein-protein interactions

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An award is made to the University of North Carolina at Chapel Hill to develop and deliver, ultimately in the form of user-friendly software, novel approaches to analyzing protein-protein interactions (PPIs) that employ a unique combination of concepts at the interface of structural bioinformatics, computational geometry, and cheminformatics. Protein-protein interactions play a central role in all major signaling events that occur in living cells. A new family of cheminformatics descriptors of PPIs derived from Delaunay tessellation of PPI interface termed SNAP3 (Simplicial Neighborhood Analysis of Protein-Protein Packing), based on the previously-developed SNAPP approach, will be developed. These descriptors will be employed as part of novel approaches to (1) identify hot spot regions on protein surfaces and (2) predict the structure of protein-protein (or protein-peptide) complexes using novel GridDock docking method to be developed in this project. In the post-genomic era, analysis and prediction of PPIs is considered critical for elucidating of many if not most protein functions to better our understanding of cell biology, cellular networks and human diseases. This project will provide both the experimental and computational communities with novel and powerful methodologies and software for analyzing and predicting PPIs and enable several important applications including: (1) unique description and comparison of PPIs using chemometric approaches; (2) the identification of unknown PPI hot spots on protein surfaces; and (3) rational design of novel peptides with desired binding specificity against target proteins. It will have a broad impact by making all PPI datasets, computational tools, and models developed accessible via a new module within the publicly available framework, the ChemBench web portal.