Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q92820

UPID:
GGH_HUMAN

ALTERNATIVE NAMES:
Conjugase; GH; Gamma-Glu-X carboxypeptidase

ALTERNATIVE UPACC:
Q92820

BACKGROUND:
The enzyme Gamma-glutamyl hydrolase, also referred to as Conjugase or GH, is instrumental in breaking down pteroylpolyglutamates into folic acid and glutamate. This process is vital for making dietary folates bioavailable and for the effective metabolism of antifolate drugs, underscoring the enzyme's significance in both nutrition and medicine.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Gamma-glutamyl hydrolase offers promising pathways for developing new therapeutic approaches. Given its central role in folate and antifolate metabolism, targeting this enzyme could lead to innovative treatments for conditions related to folate deficiency or for enhancing the efficacy of antifolate therapies.

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