Focused On-demand Library for Interleukin-17 receptor C

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

It features thorough molecular simulations of the receptor within its native membrane environment, complemented by ensemble virtual screening that considers its conformational mobility. For dimeric or oligomeric receptors, the full functional complex is constructed, and tentative binding sites are determined on and between the subunits to cover the entire spectrum of potential mechanisms of action.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q8NAC3

UPID:
I17RC_HUMAN

ALTERNATIVE NAMES:
Interleukin-17 receptor homolog; Interleukin-17 receptor-like protein; ZcytoR14

ALTERNATIVE UPACC:
Q8NAC3; A8BWC1; A8BWC9; A8BWD5; E9PHG1; E9PHJ6; Q6UVY3; Q6UWD4; Q8NFS1; Q9BR97

BACKGROUND:
The Interleukin-17 receptor C, known alternatively as ZcytoR14, is integral to the body's defense mechanisms against pathogens. It binds IL17A and IL17F, triggering immune responses essential for combating infections and maintaining tissue health. Its role in activating cytokines and chemokines through the NF-kappa-B pathway positions IL-17RC as a key player in immune regulation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Interleukin-17 receptor C could open doors to potential therapeutic strategies. Its direct involvement in familial Candidiasis underscores the importance of IL-17RC in immune system disorders, offering a promising target for drug development aimed at enhancing antifungal immunity.

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