Abstract
Understanding non-covalent biomolecular recognition, which includes drug–protein bound states and their binding/unbinding processes, is of fundamental importance in chemistry, biology, and medicine. Fully revealing the factors that govern the binding/unbinding processes can further assist in designing drugs with desired binding kinetics. HIV protease (HIVp) plays an integral role in the HIV life cycle, so it is a prime target for drug therapy. HIVp has flexible flaps, and the binding pocket can be accessible by a ligand via various pathways. Comparing ligand association and dissociation pathways can help elucidate the ligand–protein interactions such as key residues directly involved in the interaction or specific protein conformations that determine the binding of a ligand under certain pathway(s). Here, we investigated the ligand unbinding process for a slow binder, ritonavir, and a fast binder, xk263, by using unbiased all-atom accelerated molecular dynamics (aMD) simulation with a re-seeding approach and an explicit solvent model. Using ritonavir-HIVp and xk263-HIVp ligand–protein systems as cases, we sampled multiple unbinding pathways for each ligand and observed that the two ligands preferred the same unbinding route. However, ritonavir required a greater HIVp motion to dissociate as compared with xk263, which can leave the binding pocket with little conformational change of HIVp. We also observed that ritonavir unbinding pathways involved residues which are associated with drug resistance and are distal from catalytic site. Analyzing HIVp conformations sampled during both ligand–protein binding and unbinding processes revealed significantly more overlapping HIVp conformations for ritonavir-HIVp rather than xk263-HIVp. However, many HIVp conformations are unique in xk263-HIVp unbinding processes. The findings are consistent with previous findings that xk263 prefers an induced-fit model for binding and unbinding, whereas ritonavir favors a conformation selection model. This study deepens our understanding of the dynamic process of ligand unbinding and provides insights into ligand–protein recognition mechanisms and drug discovery.
Highlights
Introduction iationsHIV type 1 (HIV-1) garnered enormous attention in the 1970s because it can attackCD4 cells and weaken the immune system, eventually causing acquired immunodeficiency syndrome (AIDS) if not suppressed in vivo
Five 25-ns-long second re-seedings were applied with the last frame of the first re-seeding as an initial conformation if unbinding did not occur in the 400-ns accelerated molecular dynamics (aMD) simulation
If the selected initial frame contained a ligand–HIV protease (HIVp) conformation that presented a strong tendency to dissociate, up to twenty 25-ns-long aMD simulations would be generated from such frame
Summary
We selected Protein Data Bank entry 1HXW and 1HVR to study ritonavir and xk263 unbinding from HIVp, respectively (Figure 1b–d) [33,34]. 1HXW contains a ritonavir–HIVp crystal structure in the bound state, with a single protonation state applied for Asp25. 1HVR contains an xk263–HIVp crystal structure in the bound state, with a double protonation state for Asp25/124. Minimization of hydrogen atoms, the side chains and the entire xk263–HIVp, respectively. The SHAKE algorithm was used to constrain the covalent bonds involving hydrogen atoms [40]. We used the final frame from the cMD run as the initial conformation for aMD simulations with a different starting velocity for each seed. Where Ep and ED are the average total potential energy threshold and average dihedral energy threshold based on cMD simulation. By increasing the value of the tuning parameter α, we can reduce the energy boost, ∆V (r), allowing the conformational change of protein to evolve faster than in cMD yet maintain the protein’s secondary structure. Protein backbone dihedral angle change directly leads to protein conformational change We applied both dihedral and total potential energy boost to our model systems.
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