Molecular dynamics (MD) simulations are useful for a broad range of applications, including protein folding studies 1 , drug discovery 2 , and the determination of liquid structure and properties 3. Various approaches have been taken to improve the ability of simulations to explore the thermodynamically relevant parts of configuration space, including hardware advancements 4-9 and more effective sampling algorithms 10-14. While these efforts have dramatically improved our ability to generate well-converged results, errors persist in simulations, as highlighted for example, in the SAMPL series of blinded prediction exercises 15-21. Therefore, attention is now turning again to the potential functions, or force fields (FF), as sources of error, as recently reviewed 22 .