Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
O00507

UPID:
USP9Y_HUMAN

ALTERNATIVE NAMES:
Deubiquitinating enzyme FAF-Y; Fat facets protein-related, Y-linked; Ubiquitin thioesterase FAF-Y; Ubiquitin-specific protease 9, Y chromosome; Ubiquitin-specific-processing protease FAF-Y

ALTERNATIVE UPACC:
O00507; O14601

BACKGROUND:
USP9Y, known for its roles in ubiquitin processing and TGF-beta/BMP signaling, is vital for protein stability and cell signaling. By deubiquitinating SMAD4, it ensures the proper functioning of the TGF-beta pathway, critical for cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given USP9Y's link to spermatogenic failure Y-linked 2, exploring its function further could lead to novel treatments for male infertility. The protein's complex role in cellular mechanisms makes it a promising candidate for drug discovery.

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