TargetForge · computational drug discovery
AI-Powered Drug Discovery & Target Identification
TargetForge is a computational workbench that supports researchers with target identification, drug repurposing screens, molecular docking, ADME analysis, and scientific hypothesis testing. Outputs help prioritize candidates for follow-up — they are triage aids, not evidence of clinical efficacy.
Drug discovery
Stage a protein target, shortlist molecules from PubChem, compare drug-likeness and PAINS flags, and generate a transparent AI recommendation before running native molecular docking and ADME prediction. Open the discovery staging bench.
Drug repurposing
Screen approved drugs against a protein target to surface repurposing candidates with target-aware scoring across a curated library of marketed small molecules. Run a drug repurposing screen.
Target identification
Find genetically validated but underexplored protein targets for a disease using Open Targets evidence. Helps researchers prioritize candidates for follow-up screening. Explore target identification.
Molecular docking
Compute binding free energy estimates, inhibition constants, and inspect 3D poses in crystallographic binding pockets — simulated in-browser for structure-based prioritization. Run molecular docking.
ADME analysis
Calculate physicochemical properties, rule-based druglikeness filters (Lipinski, Veber, Ghose), and BOILED-Egg absorption models locally with RDKit for lead optimization triage. Analyze ADME properties.
Scientific hypothesis testing
Critically interrogate drug discovery and biology hypotheses with evidence mapping, falsification checks, and structured scientific critique. Test a scientific hypothesis.
Automated scientific research
Run TargetForge workflows in sequence — target discovery, PDB selection, approved-drug ranking, and adversarial critique — for automated research triage. Launch the research agent.