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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
P09210

UPID:
GSTA2_HUMAN

ALTERNATIVE NAMES:
GST HA subunit 2; GST class-alpha member 2; GST-gamma; GSTA2-2; GTH2

ALTERNATIVE UPACC:
P09210; Q12759; Q16491; Q9NTY6

BACKGROUND:
The enzyme Glutathione S-transferase A2, also known as GSTA2, GST-gamma, or GTH2, is integral to the body's defense mechanism against toxic and carcinogenic compounds. By facilitating the conjugation of glutathione with electrophilic substances, GSTA2 plays a key role in the metabolism and elimination of toxins, contributing to cellular health and resilience.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Glutathione S-transferase A2 holds significant promise for drug discovery and development. Its critical role in detoxification processes positions it as a potential target for creating innovative treatments aimed at boosting the body's natural defense mechanisms against a range of diseases, thereby enhancing patient outcomes.

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