Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 utilise our cutting-edge, exclusive workflow to develop 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
A6NGU5

UPID:
GGT3_HUMAN

ALTERNATIVE NAMES:
Gamma-glutamyltransferase 3; Putative gamma-glutamyltranspeptidase 3

ALTERNATIVE UPACC:
A6NGU5

BACKGROUND:
The enzyme known as Putative glutathione hydrolase 3 proenzyme, with alternative names Gamma-glutamyltransferase 3 and Putative gamma-glutamyltranspeptidase 3, is essential for the metabolism of glutathione, facilitating the transfer of gamma-glutamyl functional groups. This process is critical for amino acid transport, antioxidative defense, and cellular detoxification.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Putative glutathione hydrolase 3 proenzyme offers a promising pathway to novel therapeutic approaches. Given its central role in antioxidative defense and detoxification, targeting this enzyme could lead to innovative treatments for diseases characterized by impaired detoxification and oxidative damage.

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