Navjeet Ahalawat, Satyabrata Bandyopadhyay, and Jagannath Mondal (2020).
The Journal of chemical physics, 152, 074104.   (PubMed)

A solvent often manifests itself as the key determinant of the kinetic aspect of the molecular recognition process. While the solvent is often depicted as a source of barrier in the ligand recognition process by the polar cavity, the nature of solvent's role in the recognition process involving hydrophobic cavity and hydrophobic ligand remains to be addressed. In this work, we quantitatively assess the role of solvent in dictating the kinetic process of recognition in a popular system involving the hydrophobic cavity and ligand. In this prototypical system, the hydrophobic cavity undergoes dewetting transition as the ligand approaches the cavity, which influences the cavity-ligand recognition kinetics. Here, we build a Markov state model (MSM) using adaptively sampled unrestrained molecular dynamics simulation trajectories to map the kinetic recognition process. The MSM-reconstructed free energy surface recovers a broad water distribution at an intermediate cavity-ligand separation, consistent with a previous report of dewetting transition in this system. Time-structured independent component analysis of the simulated trajectories quantitatively shows that cavity-solvent density contributes considerably in an optimized reaction coordinate involving cavity-ligand separation and water occupancy. Our approach quantifies two solvent-mediated macrostates at an intermediate separation of the cavity-ligand recognition pathways, apart from the fully ligand-bound and fully ligand-unbound macrostates. Interestingly, we find that these water-mediated intermediates, while transient in populations, can undergo slow mutual interconversion and create possibilities of multiple pathways of cavity recognition by the ligand. Overall, the work provides a quantitative assessment of the role that the solvent plays in facilitating the recognition process involving the hydrophobic cavity.

This work describes an example of using Markov State Modeling in kinetic calculations.