Focused On-demand Library for X-linked interleukin-1 receptor accessory protein-like 2

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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Q9NP60

UPID:
IRPL2_HUMAN

ALTERNATIVE NAMES:
IL1RAPL-2-related protein; Interleukin-1 receptor 9; Three immunoglobulin domain-containing IL-1 receptor-related 1

ALTERNATIVE UPACC:
Q9NP60; Q2M3U3; Q9NZN0

BACKGROUND:
The protein known as X-linked interleukin-1 receptor accessory protein-like 2, with alternative names including IL1RAPL-2-related protein, Interleukin-1 receptor 9, and Three immunoglobulin domain-containing IL-1 receptor-related 1, is integral to the immune system's response mechanisms. It is implicated in various signaling pathways that are essential for initiating and regulating inflammation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of X-linked interleukin-1 receptor accessory protein-like 2 holds the key to unlocking new therapeutic avenues. Given its central role in the immune response, targeting this protein could lead to innovative treatments for a range of inflammatory conditions.

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