Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating ΔAlow→high, remains the most challenging step within an (S)QM/MM indirect FES protocol. To improve calculations of ΔAlow→high, we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of ΔAlow→high calculated for a wide variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards this end, we have carried out several benchmark studies, based on a recently introduced "HiPen" dataset, which seeks to optimize the convergence of ΔAlow→high. These studies focus on (1) optimizing protocols for carrying out non-equilibrium work simulations in combination with Jarzynski’s equation to ensure both robustness and efficiency, and (2) evaluating our recently developed machine learning-based force matching technique to assist in bridging the gap in, often, disparate levels of theory. Progress in both of these directions will be reported in this presentation.

Optimizing the calculation of free energy differences between low and high levels of theory using force matching and non-equilibrium work simulations

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.