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

TL;DR

This study benchmarks the impact of protonation and electronic polarization modeling on the accuracy of absolute binding free energy predictions, emphasizing their importance for charged molecules in drug design.

Contribution

It introduces an approach to incorporate electronic polarization and protonation states into alchemical binding affinity simulations, improving predictive accuracy.

Findings

Electronic polarization significantly improves binding affinity predictions.

Proper protonation states are crucial for charged ligand systems.

Proposed alternative binding mode for experimental validation.

Abstract

Accurate prediction of binding free energies is critical to streamlining the drug development and protein design process. With the advent of GPU acceleration, absolute alchemical methods, which simulate the removal of ligand electrostatics and van der Waals interactions with the protein, have become routinely accessible and provide a physically rigorous approach that enables full consideration of flexibility and solvent interaction. However, standard explicit solvent simulations are unable to model protonation or electronic polarization 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 the impact of modeling conditions on predictive accuracy for absolute alchemical simulations. Binding to urokinase plasminogen activator (UPA), a protein frequently overexpressed in metastatic tumors, is evaluated for a set of ten inhibitors with extended flexibility, highly charged character, and titratable properties. We demonstrate that the alchemical simulations can be adapted to utilize the MBAR/PBSA method to improve the accuracy upon incorporating electronic polarization, highlighting the importance of polarization in alchemical simulations of binding affinities. Comparison of binding energy prediction at various protonation states indicates that proper electrostatic setup is also crucial in binding affinity prediction of charged systems, prompting us to propose an alternative binding mode with protonated ligand phenol and Hid-46 at the binding site, a testable hypothesis for future experimental validation.