Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9Y644

UPID:
RFNG_HUMAN

ALTERNATIVE NAMES:
O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase

ALTERNATIVE UPACC:
Q9Y644; O00588

BACKGROUND:
The enzyme Beta-1,3-N-acetylglucosaminyltransferase radical fringe, alternatively known as O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase, is instrumental in modifying O-fucose residues on EGF-like repeats within Notch molecules' extracellular domains. This modification is key to modulating NOTCH1's interaction with ligands DLL1 and JAG1, thereby influencing NOTCH1 activation. Its activities are essential for developmental processes, including limb formation and neurogenesis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Beta-1,3-N-acetylglucosaminyltransferase radical fringe presents a promising avenue for developing novel therapeutic approaches.

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