The duration of drug efficacy in vivo is a key aspect primarily addressed during the lead optimization phase of drug discovery. Hence, the availability of robust computational approaches that can predict the residence time of a compound at its target would accelerate candidate selection. Nowadays the theoretical prediction of this parameter is still very challenging. Starting from methods reported in the literature, we set up and validated a new metadynamics (META-D)-based protocol that was used to rank the experimental residence times of 10 arylpyrazole cyclin-dependent kinase 8 (CDK8) inhibitors for which target-bound X-ray structures are available. The application of reported methods based on the detection of the escape from the first free energy well gave a poor correlation with the experimental values. Our protocol evaluates the energetics of the whole unbinding process, accounting for multiple intermediates and transition states. Using seven collective variables (CVs) encoding both roto-translational and conformational motions of the ligand, a history-dependent biasing potential is deposited as a sum of constant-height Gaussian functions until the ligand reaches an unbound state. The time required to achieve this state is proportional to the integral of the deposited potential over the CV hyperspace. Average values of this time, for replicated META-D simulations, provided an accurate classification of CDK8 inhibitors spanning short, medium, and long residence times.
This work describes an example of using Metadynamics in kinetic calculations.