ArticleJournal of chemical information and modeling2025
BIOPTIC B1 Ultra-High-Throughput Virtual Screening System Discovers LRRK2 Ligands in Vast Chemical Space.
Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Chemical modulation of Miro1 alleviates cell-type-specific vulnerabilities in Friedreich's ataxia.Cell chemical biology · 2026Article
- Artificial Intelligence Across the Drug Development Lifecycle.Medical sciences (Basel, Switzerland) · 2026Review
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Authors and funding
5 authors.
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Abstract
The rapid expansion of chemical space presents significant challenges in identifying novel ligands for drug targets. Here, we introduce BIOPTIC B1, an ultra-high-throughput ligand-based virtual screening system capable of rapidly evaluating multi-billion-molecule libraries in minutes. In retrospective analyses across seven diverse drug targets, BIOPTIC B1 demonstrated performance comparable to state-of-the-art machine learning models, including Chemprop and Gradient Boosting. Prospectively, we applied BIOPTIC B1 to leucine-rich repeat kinase 2 (LRRK2), a high-priority drug target for Parkinson's disease. BIOPTIC B1 successfully identified multiple novel ligands binding both wild-type and G2019S-mutant LRRK2 with dissociation constants (K
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