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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P32929

UPID:
CGL_HUMAN

ALTERNATIVE NAMES:
Cysteine desulfhydrase; Cysteine-protein sulfhydrase; Gamma-cystathionase; Homocysteine desulfhydrase

ALTERNATIVE UPACC:
P32929; B4E1R2; E9PDV0; Q53FB3; Q53Y79; Q9H4W7; Q9H4W8

BACKGROUND:
Cystathionine gamma-lyase, known for its roles in the metabolism of sulfur-containing amino acids, catalyzes the formation of L-cysteine, ammonia, and 2-oxobutanoate from L,L-cystathionine. It is crucial for glutathione synthesis and the production of hydrogen sulfide (H2S), which has significant implications in physiological functions such as bone protection and myogenesis.

THERAPEUTIC SIGNIFICANCE:
The enzyme's ability to modulate hydrogen sulfide levels and its involvement in glutathione biosynthesis positions Cystathionine gamma-lyase as a key target in researching treatments for diseases like Cystathioninuria. Exploring the enzyme's function further could lead to breakthroughs in managing diseases associated with sulfur amino acid metabolism.

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