Addressing biomedical challenges with computational mechanics and big data

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PROJECT SUMMARY The objective of this project is to develop better algorithms for molecular mechanics and flexible docking, incorporate new data, and use the methods to expand the set of three-dimensional atomic models of bio-macromolecules and their ligand complexes with predicted parts and homology models. These models will be used to identify new therapeutic candidates and predict mechanism of action of drugs. Since 2007 we collaborated and published with over sixty research laboratories and used structural models to understand biological function and therapeutic action. We will work in close collaboration with several laboratories at Skaggs School of Pharmacy and Pharmaceutical Sciences, UCSD, UCSD Medical School, Bioinformatics and Systems Biology Program at UCSD and several US Institutions. The SSPPS collaborators include Tracy Handel (chemokine receptors), James McKerrow (head of CDIPD center), Larissa Podust (crystallography, CDIPD), Conor Caffrey (schistosomiasis, hookworms), Jair L. Siqueira-Neto (HTS core, trypanosomiasis, leishmaniasis, antivirals), Anjan Debnath (amebiasis), Carlo Ballatore and Dionicio Siegel (medicinal chemistry) . Nuno Bandeira and Pieter Dorrestein (NIH/NCRR Center for Computational Mass Spectrometry), will help with incorporating or generating mass spectrometry data. We will also work on new treatments for several diseases, molecular mechanisms of action, and probes for new disease related pathways with the laboratories from UCSD Health Sciences Departments (Silvio Gutkind, Joseph Califano, Don Durden, Nunzio Bottini, Olivier Harismendy - oncogenomics, Pavel Pevzner, Lev Tsimring) and several US laboratories (Mark Yeager, UVa, Irina Artsimovich, OHSU, Andrei Osterman, SBP- Med.Res.Institute, Eric Debler, Jefferson Uni.). Better methods, better models, better data will help with new probes for disease-related pathways, drug repurposing and designing new drug combinations, understanding drug- resistance mutations, and understanding multi-target drug pharmacology. We will make all the data and programs produced during the project publicly available.