Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P0CG29

UPID:
GST2_HUMAN

ALTERNATIVE NAMES:
GST class-theta-2

ALTERNATIVE UPACC:
P0CG29; O60665; P30712; Q6IPV7; Q9HD76

BACKGROUND:
The enzyme Glutathione S-transferase theta-2, also known as GST class-theta-2, plays a pivotal role in the body's defense mechanism against toxic compounds. By facilitating the conjugation of glutathione to electrophiles, GSTT2 aids in neutralizing harmful substances and supports their excretion. Its sulfatase activity further underscores its importance in maintaining cellular health by processing sulfated compounds.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Glutathione S-transferase theta-2 opens up new horizons in therapeutic development. Given its central role in detoxification, targeting GSTT2 could lead to innovative treatments aimed at boosting the body's natural detoxification pathways, potentially mitigating the effects of exposure to environmental toxins and enhancing drug safety profiles.

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.