Harness the power of Generative AI
and Physics-based methods
Chemistry42 is a comprehensive small molecules drug discovery platform. It combines both the flexibility of generative AI and accuracy of physics-based methods to create optimal molecules.
Create novel small molecules with optimized properties using generative AI: de novo design, hit optimization, scaffold hopping and R-groups search.
Predict and optimize physicochemical and ADMET molecular properties.
Predict kinome activity to find off-targets and build selectivity profiles.
Accurately estimate the relative binding free energy to prioritize molecules with efficient physics-based methods.
Launch a Ligand-Based or Structure-Based Drug Discovery workflow.
Generative models ensemble will Create optimal molecules based on your criteria.
Prioritize results using Alchemistry, ADMET profiling, and Golden Cubes.
Customize the platform with your external tools such as QSAR models, MD simulators, and in-house databases.
Generative Chemistry
Physics-based core — an algorithm built on fundamental principles of physics for unprecedented accuracy and speed
Compute the relative binding free energy between your protein and ligands to prioritize your lead compounds. Augment your analysis with experimental data to determine the absolute binding free energy.
ADMET Profiling
Predict and optimize the ADMET profile of your lead molecules. Use our ADMET models as stand-alone tools or with Generative Chemistry to guide the design towards better molecules.
Golden Cubes
Predict kinome activity and selectivity.
Golden Cubes works with 2D and 3D structures, using models trained on carefully curated activity datasets.
Golden Cubes is a proprietary engine that achieves high accuracy thanks to multi-dimensional Self-Organizing Maps.
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