Molecular mechanics Poisson−Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are two widely developed end-point methods to predict the free energy of protein-ligand binding, due to their ability to achieve a good compromise between computational cost and accuracy. A single-trajectory protocol which assumes there is no significant conformational change occurs upon protein-ligand binding, is usually adopted. In addition to the excellent error cancellation, the overall prediction accuracy also depends on the accurate prediction of each individual energy terms, especially the polar and nonpolar terms of solvation free energy predicted by either PBSA or GBSA. The prediction accuracy of PB/GBSA method can be affected by several factors, including charge model, dielectric constant, radius parameters which define the solute-solvent boundary, as well as the overlap or screening parameters. It is challenging to develop highly-accurate PB/GBSA models without causing overfitting, and can improve both the relative and absolute binding free energies for most protein-ligand binding systems. In this work, we applied a genetic algorithm to optimize the PB radii parameters and screening parameters for three GB methods (GB1, GB2, GB5) for three charge models (RESP, BCC and ABCG2). The PB radius parameters were optimized to reproduce the free energy of decharging using thermodynamic integration method in conjunction with ABCG2. Note that the optimized PB radius parameters were directly used to define solute-solvent boundary for GB models. We found that the new PB/GB models outperformed most of the reported ones in terms of solvation free energy calculations for a collection of more than 700 solutes. More encouragingly, we found that those PB/GBSA models can also significantly increase the prediction accuracy of protein-ligand binding free energy prediction for eight gold-standard protein systems as previously reported.

Development and testing of end-point solvation free energy models for binding free energy prediction

Where thousands of chemistry professionals meet to share ideas and advance scientific and technical knowledge. Spring 2023 abstracts, posters, and presentations will launch at the end of March.

ACS Spring 2023

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.