Accelerate new therapeutic indications for existing drugs with our integrated computational repurposing platform. We combine large-scale Structure-Based Virtual Screening, Protein-Small Molecule Docking, and Molecular Dynamics Simulation to identify hidden polypharmacology, off-target liabilities, and novel mechanisms. Our pipeline is backed by focused wet-lab validation for hit confirmation.
We dock approved drugs, natural products, or custom libraries against one or multiple targets to reveal repurposing candidates.
Identify unexpected protein targets for a drug of interest using inverse docking or proteome-wide virtual screening.
Prioritize hits with stable binding modes, then confirm with biochemical assays (SPR, ITC, thermal shift) or cell-based assays.
Dock compounds into multiple conformational states from MD or NMR to capture induced-fit effects and cryptic pockets.
When no structure is available, we use pharmacophore modeling, shape similarity, and QSAR to screen drug libraries.
Refine top hits with MMGBSA and MD simulation to assess binding stability and residence time.
Dock compounds into multiple conformational states from MD or NMR to capture induced-fit effects and cryptic pockets.
When no structure is available, we use pharmacophore modeling, shape similarity, and QSAR to screen drug libraries.
Refine top hits with MMGBSA and MD simulation to assess binding stability and residence time.
Define target(s) of interest, select drug library (approved, natural, custom), and prepare structures (PDB, AlphaFold, homology models).
Generate multiple receptor conformations via MD, normal mode analysis, or co-crystal structures to account for flexibility.
Dock library into each ensemble, apply consensus scoring, and filter by ADMET/PAINS properties.
Cluster poses, analyze interactions, and rescore top hits with MM-GBSA/MM-PBSA to estimate relative binding affinity.
Select top candidates for biochemical validation (SPR, ITC) or cell-based assays through our experimental partners.
Deliver ranked candidate list, binding modes, mechanistic hypotheses, and suggested experimental validation plans.
| Research Goal | Recommended Approach | Key Readouts | Decision Supported |
|---|---|---|---|
| Find new targets for a known drug | Inverse docking / target fishing | Target list, binding scores, off-target profile | Mechanism repurposing, safety assessment |
| Screen drug library against a specific protein | Ensemble docking + MM-GBSA | Ranked hits, binding modes, interaction fingerprints | Hit prioritization for experimental testing |
| Discover allosteric modulators from existing drugs | Cryptic pocket detection + docking | Allosteric site identification, binding stability | Novel mechanism repurposing |
| Repurpose drugs for a new indication | Multi-target panel screening | Selectivity matrix, polypharmacology profile | Indication expansion, combination therapy |
| Validate virtual hits with wet-lab | SPR/ITC or cell-based assay (partner) | Kd, IC50, cellular activity | Confirmation of computational predictions |
A client wanted to test existing antiviral drugs against a novel coronavirus protease. We performed ensemble docking of 1,200 approved drugs, identified 8 promising hits, and validated 3 with SPR (Kd < 10 µM).
A repurposing screen of 800 kinase inhibitors against a mutant kinase revealed 5 off-target hits. MD simulations confirmed stable binding, and two compounds showed cellular activity in a target-specific assay.
We screened a drug library against a cryptic allosteric site of a GPCR. Two drugs were predicted to bind with high affinity; subsequent functional assays confirmed one as a negative allosteric modulator.
We combine large-scale virtual screening, conformational flexibility, and focused wet-lab validation to deliver repurposing candidates with high translational potential. Our CADD-first approach reduces cost and time while increasing confidence in hits.
Goal: Screen 2,000 approved drugs against a GPCR target to find new agonists.
Goal: Identify off-target kinases for a failed oncology drug to explain toxicity.
Goal: Find drugs that bind to a cryptic allosteric site of an enzyme.
We routinely screen approved drug libraries (DrugBank), natural product libraries, and custom compound sets. We can also build a custom library from your in-house collection.
Yes. We use homology modeling (via Protein Homology Modeling) or AlphaFold models to enable structure-based screening.
We collaborate with experimental partners to perform SPR, ITC, thermal shift, or cell-based assays. We can also provide detailed protocols for your lab.
Yes, we perform inverse docking against a panel of relevant proteins (e.g., kinases, GPCRs, proteases) to predict polypharmacology and safety liabilities.
A standard repurposing screen (1 target, 1,000–2,000 compounds) with MM-GBSA rescoring takes 3–4 weeks. Wet-lab validation adds 2–4 weeks depending on assay.
Submit your target and drug library. Our team will deliver a ranked repurposing candidate list, binding mode analysis, and a wet-lab validation roadmap.
Start Your Repurposing ScreenSubmit your project details below, and our team will respond within 24 hours.
Talk to our technical team about your project!
I Want To Talk
