From target to lead decisions.
The right level of physics at the right stage — preparation, screening, rescoring, FEP, and covalent extensions.
Use one stage or the full workflow, depending on where your program needs more confidence.
Prepare the target and build credible binding hypotheses.
Target and pocket preparation, binding-mode hypotheses, and screening-ready structures that create a stronger foundation for downstream decisions.
- 01Protein preparation & protonation
- 02Pocket detection and characterization
- 03Co-crystal and homology assessment
- 04Reference ligand placement
Screen libraries and prioritize hits at scale.
High-throughput docking and virtual screening to identify promising candidates faster, while improving pose quality and early ranking.
- 01Ultra-large library docking
- 02Pose-quality filtering
- 03Pharmacophore constraints
- 04Cluster-aware hit triage
Re-rank the shortlist with higher-fidelity physics.
Rescore selected compounds to reduce false positives, improve hit triage, and focus synthesis and assay budgets on the molecules most worth advancing.
- 01MM/PBSA & MM/GBSA
- 02Quantum-mechanical rescoring
- 03Pose stability simulations
- 04Confidence-weighted ranking
Optimize lead series with scalable FEP.
For congeneric series and medicinal chemistry cycles, we plan, run, and analyze FEP campaigns that help teams compare analogs with more confidence.
- 01Perturbation network planning
- 02RBFE & ABFE campaigns
- 03GPU-scale execution
- 04Cycle closure and convergence analysis
Extend into covalent inhibitors and AI-ready data.
Covalent modeling and physics-grade datasets generated from the same computational backbone, ready for model training.
- 01Covalent docking & FEP
- 02Warhead reactivity analysis
- 03Physics-grade dataset generation
- 04Active learning loops