EasyDock 1.3: An Automated Pipeline for Molecular Docking

J Chem Inf Model. 2026 Jun 10. doi: 10.1021/acs.jcim.6c01221. Online ahead of print.

Abstract

Molecular docking is widely used in drug design, particularly for large compound libraries. We previously developed EasyDock, an automated docking pipeline with multiserver task distribution to support such large-scale campaigns, and present here its extended version. Supported docking engines now include Vina-family CPU- and GPU-based variants (QVina2, Vina-GPU, etc.) and deep-learning-based engines (CarsiDock, SurfDock) via a built-in client-server architecture. Ligand preparation was enriched with salt stripping, stereoisomer enumeration, and conformational sampling of saturated ring systems. Integration of open-source protonation tools (pkasolver, MolGpKa, Uni-pKa) replaces previously required commercial software, making the pipeline fully open source. Postdocking analysis now includes protein-ligand interaction fingerprint (PLIF) computation and pose quality assessment via PoseBusters. We provide Apptainer/Docker containers for the docking engines and protonation tools, simplifying installation and HPC deployment. The source code is available at https://github.com/ci-lab-cz/easydock.