Focused On-demand Library for 3'-5' exoribonuclease 1

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.

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

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

3'-5' exonuclease ERI1; Eri-1 homolog; Histone mRNA 3'-end-specific exoribonuclease; Histone mRNA 3'-exonuclease 1; Protein 3'hExo

Alternative UPACC:

Q8IV48; A8K4U7; Q9NSX3


3'-5' exoribonuclease 1, also known as ERI1, plays a pivotal role in RNA metabolism, specifically in the degradation of histone mRNAs post-replication. It exhibits a unique preference for RNA substrates with a 2' and 3'-hydroxyl group at the last nucleotide, essential for efficient RNA decay. ERI1's ability to degrade siRNAs suggests a regulatory role in RNA interference, a critical pathway in gene expression. Furthermore, its binding affinity for specific RNA sequences and stem-loop structures underscores its importance in RNA processing.

Therapeutic significance:

Understanding the role of 3'-5' exoribonuclease 1 could open doors to potential therapeutic strategies.

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