The residence time of a ligand-protein complex is a crucial aspect in determining biological effect in vivo. Despite its importance, the prediction of ligand koff still remains challenging for modern computational chemistry. We have developed aMetaD, a fast and generally applicable computational protocol to predict ligand-protein unbinding events using a molecular dynamics (MD) method based on adiabatic-bias MD and metadynamics. This physics-based, fully flexible, and pose-dependent ligand scoring function evaluates the maximum energy (RTscore) required to move the ligand from the bound-state energy basin to the next. Unbinding trajectories are automatically analyzed and translated into atomic solvation factor (SF) values representing the water dynamics during the unbinding event. This novel computational protocol was initially tested on two M3 muscarinic receptor and two adenosine A2A receptor antagonists and then evaluated on a test set of 12 CRF1R ligands. The resulting RTscores were used successfully to classify ligands with different residence times. Additionally, the SF analysis was used to detect key differences in the degree of accessibility to water molecules during the predicted ligand unbinding events. The protocol provides actionable working hypotheses that are applicable in a drug discovery program for the rational optimization of ligand binding kinetics.
This work describes an example of using Metadynamics in kinetic calculations.
The following methods are also used: