Focused On-demand Library for Roquin-2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 our partner Reaxense.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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.







Alternative names:

Membrane-associated nucleic acid-binding protein; RING finger and CCCH-type zinc finger domain-containing protein 2; RING finger protein 164; RING-type E3 ubiquitin transferase Roquin-2

Alternative UPACC:

Q9HBD1; Q4VXB1; Q5JPD7; Q86ST6; Q8N3D6; Q96F27; Q9H5J2; Q9HBD2; Q9NWN9; Q9NXE1


Roquin-2, known for its roles as a post-transcriptional repressor and ubiquitin E3 ligase, is pivotal in mRNA degradation and ubiquitination processes. It binds to a conserved stem loop motif in mRNAs, promoting their deadenylation and degradation, crucial for controlling inflammation in macrophages and preventing autoimmunity by repressing ICOS and TNFRSF4 expression in T cells. Additionally, Roquin-2 regulates microRNA homeostasis and enhances DICER-mediated processing, showcasing its multifaceted biological functions.

Therapeutic significance:

Understanding the role of Roquin-2 could open doors to potential therapeutic strategies.

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