Focused On-demand Library for Polypeptide N-acetylgalactosaminyltransferase 12

Details

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.


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 top-notch dedicated system is used to design specialised 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
Q8IXK2

UPID:
GLT12_HUMAN

ALTERNATIVE NAMES:
Polypeptide GalNAc transferase 12; Protein-UDP acetylgalactosaminyltransferase 12; UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase 12

ALTERNATIVE UPACC:
Q8IXK2; Q5TCF7; Q8NG54; Q96CT9; Q9H771

BACKGROUND:
The enzyme Polypeptide N-acetylgalactosaminyltransferase 12, known for its alternative names such as Protein-UDP acetylgalactosaminyltransferase 12, is integral to the mucin-type oligosaccharide biosynthesis in digestive organs. It specifically transfers N-acetyl-D-galactosamine to serine or threonine residues, a critical step in the biosynthesis pathway. Its activity towards specific peptides like Muc5AC and Muc1a, but not Muc2 or Muc7, suggests a targeted function in cellular mechanisms.

THERAPEUTIC SIGNIFICANCE:
Despite the ongoing debate regarding GALNT12's direct contribution to colorectal cancer susceptibility, its association with the disease highlights the enzyme's potential in therapeutic applications. Understanding the role of GALNT12 could open doors to potential therapeutic strategies, especially in the context of colorectal cancer, where genetic alterations play a significant role.

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