*Result*: UniDock-Pro: A Unified GPU-Accelerated Platform for High-Throughput Structure-Based, Ligand-Based, and Synergistic Hybrid Virtual Screening.

Title:
UniDock-Pro: A Unified GPU-Accelerated Platform for High-Throughput Structure-Based, Ligand-Based, and Synergistic Hybrid Virtual Screening.
Authors:
Ni B; Institute for Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh EH9 3BF, U.K., Houston DR; Institute for Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh EH9 3BF, U.K.
Source:
Journal of chemical information and modeling [J Chem Inf Model] 2026 Mar 09; Vol. 66 (5), pp. 2735-2752. Date of Electronic Publication: 2026 Feb 23.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Imprint Name(s):
Original Publication: Washington, D.C. : American Chemical Society, c2005-
Substance Nomenclature:
0 (Ligands)
0 (Small Molecule Libraries)
Entry Date(s):
Date Created: 20260224 Date Completed: 20260309 Latest Revision: 20260309
Update Code:
20260309
DOI:
10.1021/acs.jcim.5c02587
PMID:
41731994
Database:
MEDLINE

*Further Information*

*The screening of ultralarge chemical libraries requires high-throughput computational tools that can efficiently exploit all available structural and chemical information. We present UniDock-Pro, a unified platform based on the GPU-accelerated Uni-Dock architecture that integrates structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS), and a novel hybrid virtual screening mode. By capitalizing on inter-ligand (batch) parallelism, UniDock-Pro achieves substantial throughput gains, enabling the processing of millions of compounds per day on a single GPU. We significantly enhanced the LBVS methodology by implementing a smooth, Lennard-Jones-like potential optimized for gradient-based search, which replaces the rugged recursive model employed in our previous work. This optimization yields a substantial 2.42-fold improvement in early enrichment (EF<subscript>1%</subscript>) over the legacy AutoDock-SS on the DUDE-Z benchmark. The Hybrid mode combines complementary information by integrating receptor- and ligand-derived grid maps on-the-fly during the conformational search, delivering strong early enrichment on DUDE-Z and competitive performance on the more stringent VSDS-vd TrueDecoy benchmark. To understand the mechanisms underlying this synergy, we introduce Force Field Complementarity Analysis (FFCA), a method for quantifying the spatial alignment between receptor and ligand force fields. UniDock-Pro offers a robust, versatile, and highly efficient solution for accelerating drug discovery campaigns across the expansive modern chemical space.*