ArticleBiochemistry2017
Mechanism of the Association Pathways for a Pair of Fast and Slow Binding Ligands of HIV-1 Protease.
Article in Biochemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 40 citations in OpenAlex.
- Ligand Versatility and Resistance Mechanism of Monotherapy-Grade HIV-1 Protease Inhibitor GRL-142 Binding the Multidrug Resistant Variant p51: Insights from 1 μs MD Simulations.Journal of chemical information and modeling · 2026Article
- Factors Influencing the Binding of HIV-1 Protease Inhibitors: Insights from Machine Learning Models.ChemMedChem · 2025Article
- Uncovering water effects in protein-ligand recognition: importance in the second hydration shell and binding kinetics.Physical chemistry chemical physics : PCCP · 2023Article
- Ritonavir and xk263 Binding-Unbinding with HIV-1 Protease: Pathways, Energy and Comparison.Life (Basel, Switzerland) · 2022Article
- The structural, dynamic, and thermodynamic basis of darunavir resistance of a heavily mutated HIV-1 protease using molecular dynamics simulation.Frontiers in molecular biosciences · 2022Article
- Multiscale computational study of ligand binding pathways: Case of p38 MAP kinase and its inhibitors.Biophysical journal · 2021Article
- Molecular Dynamics of Cobalt Protoporphyrin Antagonism of the Cancer Suppressor REV-ERBβ.Molecules (Basel, Switzerland) · 2021Article
- Molecular Mechanics Study of Flow and Surface Influence in Ligand-Protein Association.Frontiers in molecular biosciences · 2021Article
- Transient States and Barriers from Molecular Simulations and the Milestoning Theory: Kinetics in Ligand-Protein Recognition and Compound Design.Journal of chemical theory and computation · 2020Article
- Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems.Journal of chemical theory and computation · 2019Article
- Prediction of Drug-Target Binding Kinetics by Comparative Binding Energy Analysis.ACS medicinal chemistry letters · 2018Article
- Gaussian accelerated molecular dynamics for elucidation of drug pathways.Expert opinion on drug discovery · 2018Review
- Role of Molecular Interactions and Protein Rearrangement in the Dissociation Kinetics of p38α MAP Kinase Type-I/II/III Inhibitors.Journal of chemical information and modeling · 2018Article
- Escape of a Small Molecule from Inside T4 Lysozyme by Multiple Pathways.Biophysical journal · 2018Article
- Ligand Binding Pathways and Conformational Transitions of the HIV Protease.Biochemistry · 2018Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
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.
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