Improving Force Fields by Identifying and Characterizing Small Molecules with Parameter Inconsistencies

Computer-aided drug design utilizes force fields to simulate chemical structures. Force fields are sets of functions and parameters which return the potential energy of a chemical system. Force fields are widely used, but their inadequacies are often thought to contribute to systematic errors in molecular simulations. Furthermore, different force fields tend to give varying results on the same systems with the same simulation settings. Here, we present a pipeline for comparing molecules minimized with a variety of force fields. We apply this pipeline to the eMolecules database, and highlight molecules that appear to be parameterized inconsistently across different force fields. We aim to identify molecules that are informative for future force field development, and therefore display these inconsistencies between force fields. We then characterize these sets by identifying overrepresented functional groups. This project is a subset of the Open Force Field Initiative, which is working to automate force field parameterization. Molecules identified by our pipeline will be used to parameterize future force fields