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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


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.


PARTNER
Receptor.AI
 
UPACC
Q9NZH8

UPID:
IL36G_HUMAN

ALTERNATIVE NAMES:
IL-1-related protein 2; Interleukin-1 epsilon; Interleukin-1 family member 9; Interleukin-1 homolog 1

ALTERNATIVE UPACC:
Q9NZH8; Q56B91; Q6UVX7; Q7RTZ9

BACKGROUND:
The protein Interleukin-36 gamma, with alternative names such as Interleukin-1 epsilon and Interleukin-1 family member 9, is integral to the IL-36 signaling system. It is thought to be present in epithelial barriers, participating in the local inflammatory response. By influencing keratinocytes, dendritic cells, and T-cells, it drives tissue infiltration and cell proliferation. Moreover, it stimulates the expression of chemokines and pro-inflammatory markers, playing a pivotal role in neutrophilic airway inflammation.

THERAPEUTIC SIGNIFICANCE:
The exploration of Interleukin-36 gamma's function offers promising pathways for therapeutic intervention. Given its critical role in inflammatory processes, targeting this protein could lead to innovative treatments for inflammatory diseases, marking a significant step forward in medical science.

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