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.


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 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P30711

UPID:
GSTT1_HUMAN

ALTERNATIVE NAMES:
GST class-theta-1; Glutathione transferase T1-1

ALTERNATIVE UPACC:
P30711; O00226; Q5TZY2; Q6IC69; Q969K8; Q96IY3

BACKGROUND:
The enzyme Glutathione S-transferase theta-1, known alternatively as GST class-theta-1 or Glutathione transferase T1-1, is pivotal in the body's defense mechanism against toxicants. It achieves this by facilitating the conjugation of glutathione to a wide array of exogenous and endogenous compounds, including harmful electrophiles like 4-nitrobenzyl chloride. This action not only neutralizes toxins but also plays a part in glutathione peroxidase activity, reducing peroxides such as cumene hydroperoxide, thereby safeguarding cells from oxidative stress.

THERAPEUTIC SIGNIFICANCE:
The exploration of Glutathione S-transferase theta-1's function offers promising avenues for therapeutic intervention. Given its critical role in detoxifying harmful substances and mitigating oxidative stress, strategies aimed at enhancing GSTT1 activity could be beneficial in treating diseases where these processes are compromised. This underscores the potential of GSTT1 as a target in developing treatments that bolster the body's natural defense mechanisms.

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