  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. Recently, a number of methods have been introduced to
automatize this approach. Here we review these methods, highlight their
relationship with machine learning methods, and discuss the open challenges in
the field.
