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.


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


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
Q14213

UPID:
IL27B_HUMAN

ALTERNATIVE NAMES:
Epstein-Barr virus-induced gene 3 protein

ALTERNATIVE UPACC:
Q14213; A0N0N2; O75269

BACKGROUND:
The Interleukin-27 subunit beta, known alternatively as the Epstein-Barr virus-induced gene 3 protein, is integral to the IL-27 cytokine's function in innate immunity. It has a broad impact on immune regulation, including the differentiation of T-helper cells, the proliferation of CD4 T-cells, and the production of interferon-gamma. Additionally, it plays a role in antitumor and antiangiogenic activities.

THERAPEUTIC SIGNIFICANCE:
The exploration of Interleukin-27 subunit beta's functions offers promising avenues for therapeutic intervention. Its significant role in immune modulation and its direct effects on tumor suppression and inhibition of angiogenesis make it a compelling target for drug discovery in oncology and immune disorders.

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