Focused On-demand Library for m7GpppX diphosphatase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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:

DCS-1; Decapping scavenger enzyme; Hint-related 7meGMP-directed hydrolase; Histidine triad nucleotide-binding protein 5; Histidine triad protein member 5; Scavenger mRNA-decapping enzyme DcpS

Alternative UPACC:

Q96C86; Q8NHL8; Q9Y2S5


The m7GpppX diphosphatase, also known as Decapping scavenger enzyme, plays a crucial role in mRNA decay by hydrolyzing residual cap structures after degradation. This enzyme specifically targets small capped oligoribonucleotides, releasing 5'-phosphorylated RNA fragments and 7-methylguanosine monophosphate (m7GMP), essential for mRNA turnover and cellular mRNA levels regulation.

Therapeutic significance:

Given its involvement in Al-Raqad syndrome, characterized by severe developmental delays and intellectual disability, targeting m7GpppX diphosphatase could offer novel therapeutic avenues. Understanding the enzyme's role in mRNA decay pathways may illuminate strategies to mitigate the syndrome's effects.

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