ParaMol: A Package for Parametrization of Molecular Mechanics Force Fields

The ensemble of structures generated by molecular mechanics (MM) simulations is determined by the functional form of the force field employed and its parametrization. For a given functional form, the quality of the parametrization is crucial and will determine how accurately we can compute observable properties from simulations. Whilst accurate force field parametrizations are available for biomolecules, such as proteins or DNA, the parametrization of new molecules, such as drug candidates, is particularly challenging as these may involve functional groups and interactions for which accurate parameters may not be available. Here, in an effort to address this problem, we present ParaMol, a Python package that has a special focus on the parametrization of bonded and non-bonded terms of drug-like molecules by fitting to ab initio data. We demonstrate the software by deriving bonded terms’ parameters of three widelyknown drug molecules: aspirin, caffeine, and a norfloxacin analog, for which we show