CHARMM-GUI <i>Ligand Docker</i> for Molecular Docking with Various Docking Programs

Molecular docking aims to identify a biologically relevant binding pose of a ligand in the active site of a receptor. Reliable preparation of docking systems remains a key bottleneck in structure-based drug discovery, as it requires extensive preprocessing of receptor and ligand structures and careful configuration of docking parameters. To simplify this process and promote reproducibility through online docking experiments, we have developed CHARMM-GUI <i>Ligand Docker</i>, integrating four popular docking engines (AutoDock Vina, Smina, RxDock, and DiffDock) into a unified and intuitive framework for both experts and nonexperts. Users can upload and modify receptor and ligand structures, define binding sites and flexible residues, select docking programs, and execute docking calculations. The resulting docking poses can be optionally filtered using PoseBuster to remove physically implausible or geometrically strained ligand poses. Selected poses can then be seamlessly transferred to the CHARMM-GUI <i>High-Throughput Simulator</i> to generate molecular dynamics simulation systems and inputs for further refinement or free-energy evaluation. <i>Ligand Docker</i> thus provides a robust and automated platform that bridges the gap between ligand docking and simulation, ensuring that reproducible and simulation-ready systems can be prepared rapidly and conveniently for a wide range of applications in drug discovery. <i>Ligand Docker</i> is expected to serve as a valuable web-based resource that simplifies and accelerates the multistate docking setup.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-03-27
DOI
https://doi.org/10.1021/acs.jcim.6c00111
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CHARMM-GUI Ligand Docker for Molecular Docking with Various Docking Programs

Donghyuk Suh, Gyusik Kim, Wonpil Im
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
article

CHARMM-GUI Ligand Docker for Molecular Docking with Various Docking Programs

Donghyuk Suh, Gyusik Kim, Wonpil Im
article en

Abstract

Molecular docking aims to identify a biologically relevant binding pose of a ligand in the active site of a receptor. Reliable preparation of docking systems remains a key bottleneck in structure-based drug discovery, as it requires extensive preprocessing of receptor and ligand structures and careful configuration of docking parameters. To simplify this process and promote reproducibility through online docking experiments, we have developed CHARMM-GUI <i>Ligand Docker</i>, integrating four popular docking engines (AutoDock Vina, Smina, RxDock, and DiffDock) into a unified and intuitive framework for both experts and nonexperts. Users can upload and modify receptor and ligand structures, define binding sites and flexible residues, select docking programs, and execute docking calculations. The resulting docking poses can be optionally filtered using PoseBuster to remove physically implausible or geometrically strained ligand poses. Selected poses can then be seamlessly transferred to the CHARMM-GUI <i>High-Throughput Simulator</i> to generate molecular dynamics simulation systems and inputs for further refinement or free-energy evaluation. <i>Ligand Docker</i> thus provides a robust and automated platform that bridges the gap between ligand docking and simulation, ensuring that reproducible and simulation-ready systems can be prepared rapidly and conveniently for a wide range of applications in drug discovery. <i>Ligand Docker</i> is expected to serve as a valuable web-based resource that simplifies and accelerates the multistate docking setup.

Journal of Chemical Information and Modeling
Lehigh University (US), Dongguk University (KR)
Affordable and clean energy
Openalex Percentile: Top 4%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.