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Accurate prediction of binding free energies is critical to streamlining thedrug development and protein design process. With the advent of GPUacceleration, absolute alchemical methods, which simulate the removal of ligandelectrostatics and van der Waals interactions with the protein, have becomeroutinely accessible and provide a physically rigorous approach that enablesfull consideration of flexibility and solvent interaction. However, standardexplicit solvent simulations are unable to model protonation or electronicpolarization changes upon ligand transfer from water to the protein interior,leading to inaccurate prediction of binding affinities for charged molecules.Here, we perform extensive simulation totaling ~540 $\mu$s to benchmark theimpact of modeling conditions on predictive accuracy for absolute alchemicalsimulations. Binding to urokinase plasminogen activator (UPA), a proteinfrequently overexpressed in metastatic tumors, is evaluated for a set of teninhibitors with extended flexibility, highly charged character, and titratableproperties. We demonstrate that the alchemical simulations can be adapted toutilize the MBAR/PBSA method to improve the accuracy upon incorporatingelectronic polarization, highlighting the importance of polarization inalchemical simulations of binding affinities. Comparison of binding energyprediction at various protonation states indicates that proper electrostaticsetup is also crucial in binding affinity prediction of charged systems,prompting us to propose an alternative binding mode with protonated ligandphenol and Hid-46 at the binding site, a testable hypothesis for futureexperimental validation.

Estimating the Roles of Protonation and Electronic Polarization in Absolute Binding Affinity Simulations