Towards empirical force fields that reproduce experimental observables.

Biomolecular force fields have been traditionally derived based on a mixture of reference quantum chemistry data and experimental information obtained on small fragments. However, the possibility to run extensive molecular dynamics simulations on larger systems achieving ergodic sampling is paving the way to directly using such simulations along with solution experiments obtained on macromolecular systems. During recent years, a number of methods have been introduced to automatize this approach. We here review these methods, highlight their relationship with machine learning methods, and discuss the open challenges in the field.