An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors
Q. Zhao, R. Capelli, P. Carloni, B. Luescher, J. Li, G. Rossetti
Abstract
A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- An enhanced-sampling MD-based protocol for molecular docking
A. Basciu, G. Malloci, … A. V. Vargiu·bioRxiv·Oct 3, 2018
- Accelerating the Calculation of Protein-Ligand Binding Free Energy and residence Times using Dynamically Optimized Collective Variables
Z. F. Brotzakis, V. Limongelli, M. Parrinello·bioRxiv·Sep 14, 2018
- Binding Affinity Estimation From Restrained Umbrella Sampling Simulations
V. Govind Kumar, S. Agrawal, … M. Moradi·bioRxiv·Oct 28, 2021
- Predicting Small Molecule Ligand/RNA Binding Pocket Binding Modes Using Metadynamics
- Induced fit with replica exchange improves protein complex structure prediction
Ameya Harmalkar, Sai Pooja Mahajan, Jeffrey J. Gray·PLoS Computational BiologyPeer-reviewed·Jun 3, 2022
- Predicting binding events in very flexible, allosteric, multi-domain proteins
Andrea Basciu, Mohd Athar, … Attilio Vittorio Vargiu·Journal of Chemical Information and ModelingPeer-reviewed·Feb 5, 2025