Computational Drug Discovery
Rank ten thousand molecules. Synthesize ten.
DrugSynq simulates protein-ligand binding at atomic resolution — scoring candidates by predicted binding affinity and ADMET risk before your chemists touch a flask.
The Problem
The synthesis bottleneck isn't chemistry. It's prioritization.
Most discovery teams synthesize the top 50–100 molecules from a virtual screen — and 90% of them fail for reasons a physics-based simulation would have flagged. DrugSynq narrows that list before the first reaction.
The Platform
Three simulation layers, one ranked list.
Binding Affinity Ranking
Free-energy perturbation (FEP) calculations rank candidates by predicted ΔG binding, not just docking score. Physics-grounded prioritization for the full lead series.
ADMET Risk Scoring
12 ADMET properties per candidate — permeability, metabolic stability, hERG liability, aqueous solubility — scored and ranked alongside binding affinity.
Molecule Prioritization
Multi-parameter optimization surface combining affinity, ADMET, and synthetic accessibility into one ranked synthesis queue ready for the bench.
The Science
Physics-based, not just pattern-matched.
DrugSynq uses alchemical free energy methods grounded in statistical mechanics — not just ML regression on existing activity data. That means better extrapolation into novel chemical space.
Our FEP calculations use the OPLS4 force field with enhanced sampling techniques, achieving r² = 0.82 correlation against experimental IC50 measurements in retrospective validation across diverse target classes.
Read the MethodologyValidation
Benchmark performance on retrospective datasets.
We validate against publicly available crystal structure sets and published activity series to demonstrate predictive accuracy before you run your own campaign.
Retrospective benchmarks across diverse target classes show r² = 0.82 Pearson correlation between predicted and experimental ΔG values, with median absolute error of 0.78 kcal/mol.
View Validation DataWorkflow
From SMILES to synthesis shortlist in 48 hours.
Submit up to 100K SMILES strings or an SDF file via our API or web UI.
Provide an apo/holo crystal structure (PDB) or use our curated target library.
Our simulation pipeline runs alchemical perturbation cycles and ADMET property prediction in parallel.
Receive a CSV/JSON ranked list with ΔG predictions, ADMET flags, and synthetic accessibility scores.
From the Field
What computational chemists say.
"DrugSynq cut our lead optimization synthesis cycle from 14 compounds per round to 6. The ADMET ranking alone removes the obvious failures before they hit the bench."
"We were spending two weeks running our own FEP calculations per series. Now we upload the library on Monday and have the ranked list by Wednesday. That time goes back into chemistry."
Ready to shorten your synthesis shortlist?
Request platform access or schedule a live demo with Dr. Patel.