UniDock-Pro achieves significant throughput in drug discovery, utilizing high-throughput structure-based and ligand-based virtual screening methods.
The imperative to screen ultra-large chemical libraries necessitates high-throughput computational tools capable of efficiently leveraging all available structural and chemical information. We introduce UniDock-Pro, a unified platform built upon the GPU-accelerated Uni-Dock architecture, which integrates structure-based (SBVS), ligand-based (LBVS), and a novel Hybrid virtual screening mode. By capitalizing on inter-ligand (batch) parallelism, UniDock-Pro achieves massive throughput gains, processing 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, replacing the rugged recursive model used in prior tools. This optimization yields a substantial 2.45-fold improvement in early enrichment (EF1%) over the legacy AutoDock-SS on the DUDE-Z benchmark. The Hybrid mode synergizes orthogonal information by integrating receptor- and ligand-derived grid maps on-the-fly during the conformational search, consistently achieving the highest overall enrichment across diverse benchmarks. To elucidate 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 provides a robust, versatile, and highly efficient solution for accelerating drug discovery campaigns across the vast modern chemical space.
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Ni et al. (2025) studied this question.
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