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.


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


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q86SR1

UPID:
GLT10_HUMAN

ALTERNATIVE NAMES:
Polypeptide GalNAc transferase 10; Protein-UDP acetylgalactosaminyltransferase 10; UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase 10

ALTERNATIVE UPACC:
Q86SR1; B3KXC9; Q6IN56; Q86VP8; Q8IXJ2; Q8TEJ2; Q96IV2; Q9H8E1; Q9Y4M4

BACKGROUND:
The enzyme Polypeptide N-acetylgalactosaminyltransferase 10, known for its alternative names such as Polypeptide GalNAc transferase 10, is pivotal in initiating O-linked oligosaccharide biosynthesis. This process involves the enzymatic transfer of N-acetyl-D-galactosamine to serine or threonine on the target protein, a key step in mucin production evidenced by its activity on substrates like Muc5Ac.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Polypeptide N-acetylgalactosaminyltransferase 10 offers a promising avenue for the development of novel therapeutic interventions.

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