Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We utilise our cutting-edge, exclusive workflow to develop 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
Q9Y6H1

UPID:
CHCH2_HUMAN

ALTERNATIVE NAMES:
Aging-associated gene 10 protein; HCV NS2 trans-regulated protein

ALTERNATIVE UPACC:
Q9Y6H1; Q498C3; Q6NZ50

BACKGROUND:
The protein known as Coiled-coil-helix-coiled-coil-helix domain-containing protein 2, with alternative names Aging-associated gene 10 protein and HCV NS2 trans-regulated protein, functions as a transcription factor. It binds to the oxygen responsive element of COX4I2, activating its transcription in both low and normal oxygen levels, indicating its critical role in cellular oxygen sensing mechanisms.

THERAPEUTIC SIGNIFICANCE:
Its association with Parkinson disease 22, characterized by significant motor symptoms and neuronal loss, underscores the protein's potential as a target for therapeutic intervention. Exploring the function of this protein could lead to breakthroughs in treatments for Parkinson's disease, offering hope for patients and advancing our understanding of neurodegenerative disorders.

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