Accelerate your drug discovery pipeline with molecular modeling, virtual screening, and in-silico design — delivering actionable insights before a single experiment is run.
Structure-based virtual screening using AutoDock Vina, Glide, and GOLD platforms. Predict binding affinities and rank compound libraries against validated drug targets.
Build predictive models linking molecular descriptors to biological activity. Identify pharmacophores and guide synthetic optimization of lead compounds.
High-throughput in-silico screening of compound libraries — millions of molecules ranked by predicted potency, selectivity, and ADME compatibility.
All-atom MD simulations (GROMACS, AMBER) to characterize binding stability, residence time, protein flexibility, and ligand-induced conformational changes.
FEP, TI, and MM-GBSA/PBSA methods to provide accurate binding free energy rankings for lead optimization campaigns.
Fragment-based and generative AI-assisted design of novel scaffolds with optimized drug-likeness, synthetic accessibility, and target affinity.
Describe your target, compound library, and objectives — we'll design a customized workflow.