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 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 high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
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:
The protein Beta-chimaerin, known alternatively as Beta-chimerin or Rho GTPase-activating protein 3, is instrumental in modulating the activity of Rac proteins through its GTPase-activating function. This regulation is vital for maintaining cellular functions such as migration, morphology, and proliferation.

THERAPEUTIC SIGNIFICANCE:
The exploration of Beta-chimaerin's function presents a promising frontier in the quest for novel cancer therapies. Given its role in the transition of tumors from low-grade to high-grade, targeting Beta-chimaerin or its pathways could be key in developing innovative treatments for cancer.

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