BespokeFit is an automated solution for creating bespoke force field parameters for small molecules of interest in the SMIRNOFF-format that can be used seamlessly with more general force fields (such as Parsley and Sage) that are based on SMIRNOFF.
It is a Python library in the Open Force Field ecosystem that emphasises:
accuracy: by training highly specific force field parameters to data that is bespoke to molecules that are of most interest, such as candidate drug molecules, a much higher level of accuracy can be achieved than a general force field will achieve
efficiency: built-in advanced techniques such as automated chemical fragmentation enable the framework to rapidly generate bespoke quantum chemical training data at a fraction of the cost while retaining accuracy without any additional user intervention
ease of use: bespoke fitting using well tested, opinionated default settings can be easily performed directly from the command line without touching a line of Python
Please note that BespokeFit is under continuous development. It does not promise to have a stable API and may in cases produce inaccurate results. We are always looking to improve this framwork so if you do find any undesirable or irritating behaviour, please file an issue!
BespokeFit: Creating bespoke parameters for individual molecules.