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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
O95461

UPID:
LARG1_HUMAN

ALTERNATIVE NAMES:
Acetylglucosaminyltransferase-like 1A; Glycosyltransferase-like protein; LARGE xylosyl- and glucuronyltransferase 1

ALTERNATIVE UPACC:
O95461; B0QXZ7; O60348; Q17R80; Q9UGD1; Q9UGE7; Q9UGG3; Q9UGZ8; Q9UH22

BACKGROUND:
The protein Xylosyl- and glucuronyltransferase LARGE1, with its alternative names including Acetylglucosaminyltransferase-like 1A, is integral to the glycosylation process of alpha-dystroglycan. This enzymatic activity is essential for the proper functioning of alpha-dystroglycan, which connects the cytoskeleton of a muscle fiber to the surrounding extracellular matrix through the basement membrane.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Xylosyl- and glucuronyltransferase LARGE1 could open doors to potential therapeutic strategies. Its direct link to muscular dystrophy-dystroglycanopathy conditions, characterized by severe intellectual and physical disabilities, positions LARGE1 as a key target for drug discovery efforts aimed at mitigating these debilitating diseases.

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