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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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 high-tech, dedicated method is applied to construct targeted 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
Q16772

UPID:
GSTA3_HUMAN

ALTERNATIVE NAMES:
GST class-alpha member 3; Glutathione S-transferase A3-3

ALTERNATIVE UPACC:
Q16772; O43468; Q068V6; Q8WWA8; Q9H415

BACKGROUND:
The protein Glutathione S-transferase A3, also known as GST class-alpha member 3, is pivotal in the conjugation of reduced glutathione with a variety of hydrophobic electrophiles. It facilitates crucial isomerization reactions essential for the production of key steroid hormones. Additionally, GSTA3 has significant activity in detoxifying aflatoxin B1-8,9-epoxide, showcasing its protective role against toxins.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Glutathione S-transferase A3 offers a promising avenue for developing novel therapeutic approaches. Its critical role in detoxification and hormone biosynthesis underscores its potential as a target for interventions aimed at restoring homeostasis and enhancing the body's defense mechanisms.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.