Enter a disease gene: disease-network scoring, direction-aware triage, and a diversity-clustered screening plate.
Enter a disease gene to generate a mechanistically diverse screening plate from our library of tool compounds and FDA-approved drugs. The pipeline builds a disease network, scores candidate relevance, and filters out compounds predicted to worsen the phenotype.
These computational results are strictly for laboratory research purposes. They do not constitute medical advice, clinical guidance, or therapeutic recommendations.
Enter a disease gene. The pipeline builds the disease model, triages the library, and returns a screening plate with a direction-aware rationale for every pick.
Free live demo, limited to 3 new genes per visitor per day. A new gene takes ~60-90s; previously run genes return instantly.
The full library in interactive chemical space. Choose any physicochemical or ADMET property for each axis, switch to 3D, filter by target class, and click a point for detail.
Filters
Compound detail
Click any point to see the compound, its mechanism, and properties.
24 wells
Score landscape
Every triaged compound: disease-network graph score vs. assay visibility, sized by final score, colored by direction (green helps, red harms, grey neutral).
Plate (diversity-clustered, direction-passing)
The direction gate is the core of repurposing: it keeps mechanisms expected to counteract the disease and rejects those that would worsen it. This is what separates a screening plate from a list of compounds that merely touch the gene.
Partner with us
We build custom, mechanism-focused screening libraries for specific genes, pathways, and disease programs to prioritize the most promising candidates. We are always happy to discuss research projects and collaborations with physicians, patients, advocates, and patient advocacy groups.
References
Szklarczyk D, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res 2023;51(D1):D638-D646.
Ochoa D, et al. The next-generation Open Targets Platform: reimagined, redesigned, rebuilt. Nucleic Acids Res 2023;51(D1):D1353-D1359.
Swanson K, et al. ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries. Bioinformatics 2024;40(7):btae416.
Harding SD, et al. The IUPHAR/BPS Guide to PHARMACOLOGY in 2024. Nucleic Acids Res 2024;52(D1):D1438-D1449.