Harness the precision of quantum chemistry and AI-driven modeling to accelerate your drug discovery pipeline. From DFT calculations to ADMET predictions, we deliver actionable molecular insights.
Density Functional Theory and Quantum Electrodynamics calculations for precise electronic structure analysis.
High-fidelity molecular models using quantum chemistry methods for drug-target interactions.
Leverage machine learning for QSAR models, ADMET predictions, and virtual screening of compound libraries.
In silico ADMET profiling using validated computational models for early-stage compound assessment.
Molecular dynamics simulations to understand protein flexibility and binding thermodynamics.
Deliver comprehensive reports with prioritized compounds, optimization strategies, and clear recommendations.
A systematic approach combining quantum chemistry precision with AI acceleration to deliver reliable, actionable molecular insights.
Apply DFT and quantum mechanical methods to model electronic structures and molecular interactions with precision.
Leverage quantum mechanical calculations for accurate binding affinity predictions and lead optimization.
Leverage machine learning for QSAR models, ADMET predictions, and virtual screening of compound libraries.
Deliver comprehensive reports with prioritized compounds, optimization strategies, and clear recommendations.
From advanced materials discovery to sustainable energy solutions, our computational approaches drive innovation across multiple domains.
Discovered novel allosteric binding sites through MD ensemble analysis
Designed MOFs with tunable porosity and electronic structure using DFT and ML-guided screening for targeted applications
Identified low-cost, high-activity hydrogen evolution catalysts by modeling adsorption energetics and reaction pathways
Identified optimal linker conformations using quantum molecular modeling
Improved ion transport and electrochemical stability through computational screening of MOF-derived electrode materials
Elucidated catalytic mechanism using QM/MM calculations and published in Nature Chemistry
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