Focused On-demand Library for Ras-related and estrogen-regulated growth inhibitor

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We employ our advanced, specialised process to create 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.


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
Q96A58

UPID:
RERG_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q96A58; B2R9R0; B4DI02

BACKGROUND:
The Ras-related and estrogen-regulated growth inhibitor is crucial for regulating cell growth and signaling pathways. It binds to GDP/GTP and has a significant GTPase activity, with a preference for GDP. This protein's overexpression is associated with reduced cell proliferation, colony formation, and tumorigenic potential, underscoring its potential as a tumor suppressor.

THERAPEUTIC SIGNIFICANCE:
Exploring the Ras-related and estrogen-regulated growth inhibitor's function offers a pathway to novel therapeutic approaches. Its impact on cell proliferation and tumorigenic potential positions it as a key target for drug discovery in oncology and growth-related diseases.

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