Focused On-demand Library for Interleukin-1 receptor-associated kinase 3

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


Our top-notch dedicated system is used to design specialised 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
Q9Y616

UPID:
IRAK3_HUMAN

ALTERNATIVE NAMES:
IL-1 receptor-associated kinase M; Inactive IL-1 receptor-associated kinase 3

ALTERNATIVE UPACC:
Q9Y616; B4DQ57

BACKGROUND:
The protein Interleukin-1 receptor-associated kinase 3, with alternative names IL-1 receptor-associated kinase M and Inactive IL-1 receptor-associated kinase 3, is a putative inactive protein kinase. It is key in regulating signaling pathways following activation by immune receptors such as IL1R and Toll-like receptors, crucially affecting the immune system's response to inflammation and infection.

THERAPEUTIC SIGNIFICANCE:
IRAK3's involvement in asthma-related traits underscores its significance in disease susceptibility, highlighting its potential as a therapeutic target. The exploration of IRAK3's functions and mechanisms offers promising avenues for developing novel treatments for asthma and related inflammatory conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 7946 of 8789