Efforts to build better computational models for more accurate protein-ligand binding predictions are a major area of research towards designing effective and safe drugs. In this work, we will review the development and implementation of an improved computational method based on a binding free energy model which includes the effects of water displaced by the ligand during binding. The method is built based on an advanced implicit solvent model (AGBNP2) constructed purposely for binding free energy estimation of protein-ligand complexes and customized to reproduce the thermodynamics of water expulsion as derived from Hydration Site Analysis. The binding free energy protocol is based on the alchemical Single-Decoupling Method (SDM) and multidimensional Asynchronous Replica Exchange sampling framework (AsyncRE). In this work, we applied this novel computational approach to study binding affinities of Dopamine receptor antagonists to treat drug addiction, as well as other targets. We tested our model on experimentally validated ligands and as well as ligand libraries which are not synthesized yet. To achieve high-throughput in calculations of large ligand libraries, we developed interfaces to run replica-exchange Molecular Dynamics calculations on computational grids, including the XSEDE Open Science Grid.

Computational methodologies for studying the binding affinities of protein-ligand complexes by combining hydration and dynamical effects

256th National Meeting (2018)

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