UC Riverside

Investigation of protein-drug recognition is key to understanding drug selectivity and binding affinity. In combination, the binding/unbinding free energy landscape and intermolecular interactions can be used to understand drug binding/unbinding mechanisms. This information is vital for the development of drugs with improved efficacy and explanation of mutation effects. This study investigated the dissociation processes of ritonavir unbinding from HIV protease (HIVp). Analyzing unbinding trajectories modeled by accelerated molecular dynamics (MD) simulations, three distinct pathways, pathways A-C, were characterized. Using a reduced dimensionality strategy with the principal component analysis, we carried out short classical MD runs with explicit water to sample local fluctuation during ritonavir dissociation and applied the milestoning theory to construct an unbinding free energy landscape. We found that each pathway showed similar values of binding free energy, albeit pathway A accounts for over 50% of dissociation trajectories. Interestingly, residue-residue correlation network analysis showed that in pathway A, a broad correlation network outside the flap region governs protein motions during ritonavir unbinding, which includes residues with reported mutation effects. However, the other two pathways showed limited correlation networks where no reported mutated residues were involved, explaining the favorability of pathway A. Guided by the free energy profile, we investigated each energy barrier and minimum, demonstrating that hydrogen bonding governed movement of the flap regions, directly impacting the calculated energy. Our study provided a new strategy to estimate ligand binding free energy and demonstrated the importance of the transient interactions during ligand-protein dissociation pathways in understanding drug unbinding.