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Peer-reviewedCC BYJournal of Cheminformatics

DockM8: an all-in-one open-source platform for consensus virtual screening in drug design

  • Antoine Lacour1,2,3,4
  • Hamza Agha1,3
  • Anna K. H. Hirsch2,3,4
  • Andrea Volkamer5,6,7
7 affiliations
  1. 1Data Driven Drug Design, Faculty of Mathematics and Computer Sciences, Saarland University, Campus E2.1, 66123, Saarbrücken, Saarland, Germany
  2. 2Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Campus E8.1, 66123, Saarbrücken, Saarland, Germany
  3. 3PharmaScienceHub, Saarland University, Campus E2.1, Saarland, 66123, Saarbrücken, Germany
  4. 4Saarland University, Department of Pharmacy, Campus E8.1, 66123, Saarbrücken, Saarland, Germany
  5. 5Data Driven Drug Design, Faculty of Mathematics and Computer Sciences, Saarland University, Campus E2.1, 66123, Saarbrücken, Saarland, Germany. [email protected]
  6. 6Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Campus E8.1, 66123, Saarbrücken, Saarland, Germany. [email protected]
  7. 7PharmaScienceHub, Saarland University, Campus E2.1, Saarland, 66123, Saarbrücken, Germany. [email protected]
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Abstract

Virtual screening remains a critical step in structure-based drug design, yet variability in docking algorithms and scoring functions often limits its reliability. To address this challenge, we introduce DockM8, an open-source platform for consensus virtual screening that integrates pocket detection, ligand preparation, docking, rescoring, and consensus ranking within a single modular workflow. DockM8 supports five docking engines, 17 pose-selection methods, 17 scoring functions (SFs), and five consensus methods, all accessible through both a graphical user interface (GUI) and a Python application programming interface (API). Systematic evaluation on the DEKOIS 2.0, DUD-E, and Lit-PCBA datasets yielded median relative enrichments of 100%, 82.59%, and 8.85%, respectively, frequently matching or outperforming state-of-the-art approaches. Our findings further reveal that no pose-selection or consensus strategy universally excels, emphasizing the need for tailored, target-specific workflows. DockM8 is freely available under the GNU General Public License at https://github.com/DrugBud-Suite/DockM8 . Scientific contributionDockM8 is, to our knowledge, the most comprehensive open-source platform to integrate the complete consensus structure-based virtual screening (SBVS) pipeline within a single, graphical-interface-driven tool, yielding over 55 million configurable protocols, a breadth unmatched by previously published consensus docking software. Through systematic multi-benchmark evaluation, we demonstrate that no single pose-selection or consensus strategy generalizes across targets, motivating a target-specific workflow-selection paradigm in place of prevailing one-size-fits-all heuristics. By delivering this tunability through a graphical interface rather than scripts, DockM8 brings rigorous, reproducible consensus virtual screening within reach of non-specialist medicinal chemists.

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Cite

BibTeXRIS
BibTeX
@article{lacour2026dockm8,
  title = {{DockM8: an all-in-one open-source platform for consensus virtual screening in drug design}},
  author = {Antoine Lacour and Hamza Agha and Anna K. H. Hirsch and Andrea Volkamer},
  journal = {Journal of Cheminformatics},
  year = {2026},
  month = sep,
  doi = {10.1186/s13321-026-01287-2},
  url = {https://doi.org/10.1186/s13321-026-01287-2},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - DockM8: an all-in-one open-source platform for consensus virtual screening in drug design
AU  - Antoine Lacour
AU  - Hamza Agha
AU  - Anna K. H. Hirsch
AU  - Andrea Volkamer
PY  - 2026
DA  - 2026/09/18
JO  - Journal of Cheminformatics
DO  - 10.1186/s13321-026-01287-2
UR  - https://doi.org/10.1186/s13321-026-01287-2
AB  - Virtual screening remains a critical step in structure-based drug design, yet variability in docking algorithms and scoring functions often limits its reliability. To address this challenge, we introduce DockM8, an open-source platform for consensus virtual screening that integrates pocket detection, ligand preparation, docking, rescoring, and consensus ranking within a single modular workflow. DockM8 supports five docking engines, 17 pose-selection methods, 17 scoring functions (SFs), and five consensus methods, all accessible through both a graphical user interface (GUI) and a Python application programming interface (API). Systematic evaluation on the DEKOIS 2.0, DUD-E, and Lit-PCBA datasets yielded median relative enrichments of 100%, 82.59%, and 8.85%, respectively, frequently matching or outperforming state-of-the-art approaches. Our findings further reveal that no pose-selection or consensus strategy universally excels, emphasizing the need for tailored, target-specific workflows. DockM8 is freely available under the GNU General Public License at https://github.com/DrugBud-Suite/DockM8 . Scientific contributionDockM8 is, to our knowledge, the most comprehensive open-source platform to integrate the complete consensus structure-based virtual screening (SBVS) pipeline within a single, graphical-interface-driven tool, yielding over 55 million configurable protocols, a breadth unmatched by previously published consensus docking software. Through systematic multi-benchmark evaluation, we demonstrate that no single pose-selection or consensus strategy generalizes across targets, motivating a target-specific workflow-selection paradigm in place of prevailing one-size-fits-all heuristics. By delivering this tunability through a graphical interface rather than scripts, DockM8 brings rigorous, reproducible consensus virtual screening within reach of non-specialist medicinal chemists.
SN  - 1758-2946
ER  -