AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-related protein R-Ras2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, 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.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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

Reaxense

upacc

P62070

UPID:

RRAS2_HUMAN

Alternative names:

Ras-like protein TC21; Teratocarcinoma oncogene

Alternative UPACC:

P62070; B2R9Z3; B7Z5Z2; B7Z6C4; B7Z7H6; P17082

Background:

Ras-related protein R-Ras2, also known as Ras-like protein TC21 or Teratocarcinoma oncogene, plays a pivotal role in cellular processes through its involvement in the MAPK signaling pathway. This protein's GTPase activity is crucial for regulating various cellular functions, including craniofacial development, as evidenced by research findings (PubMed:31130282, PubMed:31130285).

Therapeutic significance:

R-Ras2 is implicated in significant health conditions such as Ovarian cancer and Noonan syndrome 12. The protein's association with these diseases highlights its potential as a target for therapeutic intervention. Understanding the role of Ras-related protein R-Ras2 could open doors to potential therapeutic strategies, especially considering the variability in disease severity and the broad spectrum of symptoms.

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