Focused On-demand Library for Interleukin-31 receptor subunit alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

This process includes extensive molecular simulations of the receptor in its native membrane environment, along with ensemble virtual screening that accounts for its conformational mobility. In the case of dimeric or oligomeric receptors, the entire functional complex is modelled, identifying potential binding pockets on and between the subunits to encompass all possible mechanisms of action.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Cytokine receptor-like 3; GLM-R; Gp130-like monocyte receptor; ZcytoR17

Alternative UPACC:

Q8NI17; A6NIF8; Q2TBA1; Q6EBC3; Q6EBC4; Q6EBC5; Q6EBC6; Q6UWL8; Q8WYJ0


The Interleukin-31 receptor subunit alpha, also known as Cytokine receptor-like 3, GLM-R, Gp130-like monocyte receptor, and ZcytoR17, plays a pivotal role in the immune system. It forms a receptor with OSMR that activates STAT3, STAT1, and STAT5, influencing skin immunity and mediating IL31-induced itch. This receptor is crucial for the survival and proliferation of myeloid progenitor cells in bone marrow.

Therapeutic significance:

Given its involvement in primary localized cutaneous amyloidosis, understanding the role of Interleukin-31 receptor subunit alpha could open doors to potential therapeutic strategies. Targeting this receptor may offer new avenues for treating skin-related amyloidosis, emphasizing the importance of further research in this area.

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