While the goal of protein descriptors is to capture the full complexity of the protein, they largely fail to depict protein dynamism. At physiological temperatures, proteins exist in an equilibrium of structural conformations, which can be studied experimentally or simulated with Molecular Dynamics (MD) . Changes in metabolite or ligand concentrations, as well as mutations and other structural alterations can impact protein dynamics . These, in turn, directly influence protein function and interactions . The inclusion of dynamic information in protein descriptors could therefore increase performance in some of the machine learning applications listed above. Positive effects have already been reported in target and functional sites identification , but this potential is yet to be explored in PCM bioactivity modelling.