en
Scientific article
Open access
English

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

Published inJournal of chemical information and modeling, vol. 62, no. 23, p. 6209-6216
Publication date2022-11-19
First online date2022-11-19
Abstract

Predicting the correct pose of a ligand binding to a protein and its associated binding affinity is of great importance in computer-aided drug discovery. A number of approaches have been developed to these ends, ranging from the widely used fast molecular docking to the computationally expensive enhanced sampling molecular simulations. In this context, methods such as coarse-grained metadynamics and binding pose metadynamics (BPMD) use simulations with metadynamics biasing to probe the binding affinity without trying to fully converge the binding free energy landscape in order to decrease the computational cost. In BPMD, the metadynamics bias perturbs the ligand away from the initial pose. The resistance of the ligand to this bias is used to calculate a stability score. The method has been shown to be useful in reranking predicted binding poses from docking. Here, we present OpenBPMD, an open-source Python reimplementation and reinterpretation of BPMD. OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. We also investigated the role of accurate water positioning on the performance of the algorithm and showed how the combination with a grand-canonical Monte Carlo algorithm improves the accuracy of the predictions.

eng
Keywords
  • Drug development
  • Binding site
Citation (ISO format)
LUKAUSKIS, Dominykas et al. Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses. In: Journal of chemical information and modeling, 2022, vol. 62, n° 23, p. 6209–6216. doi: 10.1021/acs.jcim.2c01142
Main files (1)
Article (Published version)
Identifiers
ISSN of the journal1549-9596
18views
26downloads

Technical informations

Creation03/28/2023 8:34:49 AM
First validation04/27/2023 3:22:33 PM
Update time04/27/2023 3:22:33 PM
Status update04/27/2023 3:22:33 PM
Last indexation05/06/2024 3:47:05 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack