Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.


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
Q8TDU9

UPID:
RL3R2_HUMAN

ALTERNATIVE NAMES:
G-protein coupled receptor 100; G-protein coupled receptor GPCR142; Insulin-like peptide INSL5 receptor; Relaxin family peptide receptor 4

ALTERNATIVE UPACC:
Q8TDU9; B0M0L4; Q3MJB1; Q8NGZ8

BACKGROUND:
The protein Relaxin-3 receptor 2, alternatively named Insulin-like peptide INSL5 receptor, serves as a crucial component in the regulation of various physiological processes through its interaction with ligands like INSL5 and relaxin-3. This interaction significantly impacts cAMP levels within cells, indicating its central role in cellular signaling mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Relaxin-3 receptor 2 holds promise for the development of novel therapeutic approaches. Given its central role in modulating intracellular signaling pathways, targeting this receptor could lead to innovative treatments for diseases where these pathways are dysregulated.

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