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Capturing Protein-Ligand Recognition Pathways in Coarse-Grained Simulation.

Protein-ligand recognition is dynamic and complex. A key approach in deciphering the mechanism underlying recognition process is to capture the kinetic process of ligand in its act of binding to its designated protein cavity. Towards this end, ultra-long all-atom molecular dynamics simulation has recently emerged as popular method of choice, due to its ability to record these events at high spatial and temporal resolution. However, success via this route comes at an exorbitant computational cost. Here we demonstrate that coarse-grained models of protein, when systematically optimised to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to cavity at crystallographic precision and within orders of magnitude shorter wall clock time than of all-atom simulations. The exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation, leads to elucidation of new ligand recognition pathways and discovery of non-native binding poses.