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.


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.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
Q9NYY1

UPID:
IL20_HUMAN

ALTERNATIVE NAMES:
Cytokine Zcyto10

ALTERNATIVE UPACC:
Q9NYY1; Q17RB3; Q2THG6; Q96QZ6

BACKGROUND:
The protein Interleukin-20, alternatively named Cytokine Zcyto10, is central to immune system regulation, playing a critical role in inflammatory responses, blood cell formation, and skin cell differentiation. It is key in promoting tissue repair and maintaining the integrity of epithelial layers under stress conditions. Interleukin-20 exerts its biological effects through interactions with two types of receptor complexes, leading to the activation of multiple signaling cascades that are essential for cellular processes such as actin reorganization in neutrophils, inhibiting their phagocytosis, granule exocytosis, and migration.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Interleukin-20 could open doors to potential therapeutic strategies.

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