Mechanism of the Association Pathways for a Pair of Fast and Slow Binding Ligands of HIV-1 Protease

Abstract

Equilibrium constants, together with kinetic rate constants of binding, are key factors in the efficacy and safety of drug compounds, informing drug design. However, the association pathways of protein–ligand binding, which contribute to their kinetic behaviors, are little understood. In this work, we used unbiased all-atom molecular dynamics (MD) simulations with an explicit solvent model to study the association processes of protein–ligand binding. Using the HIV protease (HIVp)–xk263 and HIVp–ritonavir protein–ligand systems as cases, we observed that ligand association is a multistep process involving diffusion, localization, and conformational rearrangements of the protein, ligand, and water molecules. Moreover, these two ligands preferred different routes of binding, which reflect two well-known binding mechanisms: induced-fit and conformation selection models. Our study shows that xk263 has a stronger capacity for desolvating surrounding water molecules, thereby inducing a semiopen conformation of the HIVp flaps (induced-fit model). In contrast, the slow dehydration characteristic of ritonavir allows for gradual association with the binding pocket of HIVp when the protein’s flap conformation is fully open (conformation selection model). By studying the mechanism of ligand association and understanding the role of solvent molecules during the binding event, we can obtain a different perspective on the mechanism of macromolecule recognition, providing insights into drug discovery.

Ligand Binding Pathways and Conformational Transitions of the HIV Protease

“…The conformational transition between the unbound and intermediate states exhibited the highest free energy barrier (Figure 2A and Figure S4) and thus appeared to be the rate-limiting step during association of the XK263 ligand, although the anisotropic diffusion of the flexible flaps and other factors could affect the ligand binding rate, as well. 48 The binding mechanism of the XK263 obtained from the GaMD simulations is consistent with those from previous cMD studies; 16,27 i.e., an induced-fit model is more suitable for describing binding of XK263 to the HIV protease than a conformational-selection mechanism is. 16,49 …”

“…48 The binding mechanism of the XK263 obtained from the GaMD simulations is consistent with those from previous cMD studies; 16,27 i.e., an induced-fit model is more suitable for describing binding of XK263 to the HIV protease than a conformational-selection mechanism is. 16,49 …”

“…GaMD provided significantly enhanced sampling compared with that of cMD simulations. Figure S6 plots the RMSDs of the XK263 ligand relative to the 1HVR X-ray crystal conformation obtained from a previous ~14000 ns Anton cMD simulation 16 and two 2500 ns GaMD simulations (“Sim1” and “Sim2” listed in Table 1). Relative to the X-ray crystal structure, the XK263 ligand reached a minimum RMSD of 2.26 Å during 2500 ns GaMD simulations.…”

Role of Molecular Interactions and Protein Rearrangement in the Dissociation Kinetics of p38α MAP Kinase Type-I/II/III Inhibitors

“…However, the number of pocket-waters fluctuated considerably. Unlike ligands binding to HIV protease, in which a few transient water molecules stay for a long time between the ligand and protein, 74 with SB2 unbinding from p38 α , all the water molecules were replaced by each other frequently. However, a water molecule can still weaken interactions between functional groups of SB2 and the protein, which assists the unbinding process.…”

Transient states and barriers from molecular simulations and milestoning theory: kinetics in ligand-protein recognition and compound design

“…Molecular simulations, which are able to provide atomistic descriptions of temporal and spatial details of ligand-protein association and dissociation processes, become an important tool to characterize mechanistic features of binding kinetics and further assist drug development 6 . Features that govern binding kinetics are system-dependent and include ligand properties, conformational fluctuations, intermolecular interactions, and solvent effects [7][8][9][10][11][12] . However, the determinants to adjust for optimizing kinetic properties for a drug discovery project are not well understood.…”