AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Beta-chimaerin

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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

P52757

UPID:

CHIO_HUMAN

Alternative names:

Beta-chimerin; Rho GTPase-activating protein 3

Alternative UPACC:

P52757; A4D1A2; B3VCF1; B3VCF2; B3VCF3; B3VCF7; B3VCG1; C9J7B0; E9PGE0; F8QPL9; Q2M203; Q75MM2

Background:

Beta-chimaerin, also known as Beta-chimerin or Rho GTPase-activating protein 3, plays a crucial role in the regulation of the p21-rac pathway. Its primary function is as a GTPase-activating protein, which is essential for controlling the activity of Rac proteins. These proteins are pivotal in various cellular processes, including cell morphology, migration, and division.

Therapeutic significance:

Understanding the role of Beta-chimaerin could open doors to potential therapeutic strategies. Its involvement in the progression from low-grade to high-grade tumors highlights its significance in cancer biology. Targeting the pathways regulated by Beta-chimaerin may offer new avenues for the development of cancer treatments.

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