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.


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.


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 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.


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
Q8NBL1

UPID:
PGLT1_HUMAN

ALTERNATIVE NAMES:
CAP10-like 46 kDa protein; KTEL motif-containing protein 1; Myelodysplastic syndromes relative protein; O-glucosyltransferase Rumi homolog; Protein O-xylosyltransferase POGLUT1

ALTERNATIVE UPACC:
Q8NBL1; B2RD13; Q53GJ4; Q8N2T1

BACKGROUND:
The enzyme Protein O-glucosyltransferase 1, with alternative names such as CAP10-like 46 kDa protein and O-glucosyltransferase Rumi homolog, is a dual specificity glycosyltransferase. It is instrumental in the O-glucosylation of Notch, a process vital for regulating muscle development and promoting gastrulation during early development by mediating the localization of CRB2 to the cell membrane.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases like Dowling-Degos disease 4 and limb-girdle muscular dystrophy autosomal recessive 21, POGLUT1 represents a significant target for drug discovery. The exploration of POGLUT1's functions and mechanisms offers promising avenues for developing novel therapeutic interventions for these debilitating conditions.

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