Abstract
Accurate prediction of protein-ligand binding affinity is essential to computational drug discovery. Although virtual screening has been widely utilized, current approaches are seriously limited by the accuracy of the underlying potential energy model (i.e. force field) that describes atomic interactions. A more rigorous physical model combined with effective sampling of molecular configurations is critical for binding affinity prediction to chemical accuracy, which is defined as within one order of magnitude of the true equilibrium dissociation constant. We have demonstrated that electrostatic interactions, especially electronic polarization, are critical for protein-ligand recognition due to the significant change in electrostatic environments between bulk water and protein pockets and have achieved encouraging success in treating charged species using the polarizable Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field. To maintain accuracy while also achieving efficiency, AMOEBA has been combined with the Orthogonal Space Random Walk enhanced alchemical free energy algorithm. Here we present applications of this strategy for the computation of protein-ligand binding affinities and, for the first time, drug solubility from alchemical simulations using the Force Field X software.View Large Image | View Hi-Res Image | Download PowerPoint Slide
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