Enhancing Drug Discovery Research by Free Energy Modeling

Brooklyn College, New York NY

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY/ABSTRACT Accurate computational binding free energy models that estimate the dissociation constants of protein- ligand complexes by representing the motion of compounds and their cellular targets at atomic resolution are increasingly contributing to the discovery of drugs. However, due to their limited range of applicability, perceived barriers to entry, and scarcity of computational modelers with sufficient expertise to make good use of them, free energy models of protein-drug binding are still not widely adopted, especially in academic settings. The project addresses the need to widen access, build expertise, and extend binding free energy computational models for a broader pool of drug discovery applications in academic and industrial settings. It does so while expanding the research capacity at Brooklyn College by providing molecular modeling support to experimental projects in the health sciences and offering meaningful educational and research opportunities to our students. The PI’s lab has developed the Alchemical Transfer Method (ATM) for binding free energy estimation that incorporates the best science and simplifications afforded by the next generation of algorithms and circumvents many of the shortcomings of traditional approaches. ATM supports diverse ligand libraries and will be extended to treat bridging water molecules, metal ions, and conformational changes induced by ligand binding, all critical and outstanding problem areas for binding free energy models. Through partnerships with local academic labs, the project will investigate viral, cancer, and drug addiction targets enabled by these novel technologies. Molecular modeling tools are only as good as their ability to give insights into the molecular basis of disease. Building on solid partnerships with experimental laboratories, the project will promote the complementary use of molecular modeling in biochemical and drug discovery research through interdisciplinary student research experiences. It will build upon the successful ICompute Interdisciplinary Undergraduate Research initiative at Brooklyn College to bring computational and experimental laboratories together and nurture the next generation of researchers.