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UniDock-Pro: A Unified GPU-Accelerated Platform for High-Throughput Structure-Based, Ligand-Based, and Synergistic
Boyang Ni1, Douglas R Houston1
1Institute for Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh EH9 3BF, U.K.
Journal of Chemical Information and Modeling
|February 24, 2026
Summary
UniDock-Pro accelerates drug discovery by integrating structure-based, ligand-based, and hybrid screening. This GPU-accelerated platform processes millions of compounds daily, significantly improving early enrichment for efficient virtual screening.
Area of Science:
- Computational chemistry
- Drug discovery
- Bioinformatics
Background:
- High-throughput computational tools are essential for screening ultralarge chemical libraries.
- Existing methods require efficient exploitation of structural and chemical information.
Purpose of the Study:
- To present UniDock-Pro, a unified platform for accelerated virtual screening.
- To integrate structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS), and a novel hybrid mode.
- To enhance computational efficiency and accuracy in drug discovery.
Main Methods:
- Developed UniDock-Pro, a GPU-accelerated platform based on Uni-Dock architecture.
- Implemented enhanced LBVS with a smooth potential for gradient-based search.
- Introduced a hybrid screening mode integrating receptor- and ligand-derived grid maps.
- Developed Force Field Complementarity Analysis (FFCA) to quantify spatial alignment.
Main Results:
- UniDock-Pro processes millions of compounds per day on a single GPU.
- Achieved a 2.42-fold improvement in early enrichment (EF1%) over AutoDock-SS on the DUDE-Z benchmark.
- Demonstrated strong early enrichment on DUDE-Z and competitive performance on VSDS-vd TrueDecoy benchmark using Hybrid mode.
Conclusions:
- UniDock-Pro offers a robust, versatile, and highly efficient solution for drug discovery.
- The platform significantly accelerates campaigns across large chemical spaces.
- Enhanced LBVS and the novel hybrid mode improve virtual screening accuracy and speed.

