We’re excited to introduce a powerful enhancement to your compound discovery workflow. A curated subset of OTAVA’s CHEMRIYA™ Virtual Chemical Space — comprising 1.4 billion synthetically feasible small molecules (just 2.5% of our total 55+ billion compound collection) — is now fully searchable through the AI-powered CHEESE Search platform.
This seamless integration enables researchers to explore the richness and diversity of CHEMRIYA™ using three orthogonal and precision-guided similarity search modes — each tailored to different stages of the drug discovery pipeline.
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Phenotypic drug discovery is successful strategy that allows to identify substances (small molecules, peptides etc.) which alter the phenotype of cells, tissues or whole organisms in a desired manner.
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 Fragment-based lead design (FBLD) could be used to identify new metal-binding groups for metalloenzyme inhibitors. Several small-molecule chelators have been shown to effectively inhibit metalloproteins, therefore the design,
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The OTAVA GPCR Antagonist Library is a computationally designed collection created to explore GPCR-privileged chemical space with a focus on antagonist and inverse-agonist pharmacology.
The library integrates ligand-based machine learning, Bayesian modeling, and AI-driven scaffold optimization to enable efficient discovery of structurally diverse GPCR antagonists.
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 Natural Product-Like Library has been designed as a special screening library containing synthetic compounds similar to natural products.
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