AutoParams: An Automated Web-Based Tool To Generate Force Field Parameters for Molecular Dynamics Simulations

The growth of machine learning as a predictive tool in biochemical research has led to an increased need for large-scale datasets. Certain research questions benefit from molecular dynamics simulations to observe the motions and conformations of molecules over time, however contemporary methods rely on forcefields which describe sets of common biomolecules. Unusual molecules, such as nucleotide analogues, functionalized carbohydrates, and modified amino acids are often ill-described in standard forcefields, requiring the development of custom parameters for each unique molecule. While these parameters may be created by individual users, the process is time-consuming and can introduce errors that may not be immediately apparent. We present an open-source automated parameter generation service, AutoParams, which requires minimal input from the user and creates useful forcefield parameter sets for most molecules, particularly those that combine molecular types (ex: a carbohydrate functionalized with a benzene). It can be straightforwardly linked to any charge generation program, and currently has interfaces to PsiRESP and TeraChem, and is available via GitHub and as a Docker container. It includes error checking and testing protocols to ensure the parameters will be sufficient for subsequent molecular dynamics simulations, and streamlines the creation of force field databases.