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
- Donghyuk Suh (ORCID: https://orcid.org/0000-0002-7478-4579)
- Gyusik Kim
- Wonpil Im
Institutions
- Lehigh University (US)
- Dongguk University (KR)
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