Established Techniques
AI capabilities are integrated with a broad collection of academically established computational approaches rather than relying on a single predictive method.
02 · EVALUATE
Scientific
Evidence
Building quantum-chemical understanding across broad chemical space by combining advanced AI with complementary ligand- and receptor-based analysis, engineered for scalable large-scale computation.
← Back to Our ApproachQM
AI
LIGAND
RECEPTOR
PHYSICS + AI AT SCALE
Deeper molecular understanding, designed to scale.
UDD integrates advanced artificial intelligence with more than 10 academically established computational techniques to investigate molecular behavior from complementary ligand- and receptor-based perspectives. The platform brings together physics-based molecular information, structural analysis, and AI while emphasizing automation and computational scalability for large-scale calculations.
Ligand Intelligence
QM-derived molecular information and advanced pharmacophore models support deeper characterization and comparison of candidate compounds across chemical space.
Receptor Intelligence
Receptor-site environments are examined alongside ligand properties to build a more complete representation of molecular recognition and interaction.
Physics-Based Analysis
Quantum chemistry, xTB, and QM/MM provide complementary levels of physical description for molecular systems and local interaction environments.
Dynamic Systems
Molecular dynamics extends analysis beyond static structures by examining molecular behavior and interaction environments over time.
Automated Computation
Highly automated and scalable computational systems are designed to distribute large numbers of calculations efficiently, allowing advanced methods and AI to be applied across substantially larger molecular collections.