Focused On-demand Library for mRNA cap guanine-N7 methyltransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

Our high-tech, dedicated method is applied to construct targeted 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:

RG7MT1; mRNA (guanine-N(7))-methyltransferase; mRNA cap methyltransferase

Alternative UPACC:

O43148; B0YJ90; D3DUJ5; O94996; Q9UIJ9


mRNA cap guanine-N7 methyltransferase, also known as RG7MT1, plays a crucial role in the post-transcriptional modification of mRNA. It is the catalytic subunit of the mRNA-capping methyltransferase RNMT:RAMAC complex, responsible for methylating the N7 position of the guanosine added to the 5'-cap structure of mRNAs. This protein binds RNA containing 5'-terminal GpppC, highlighting its specificity in mRNA modification.

Therapeutic significance:

Understanding the role of mRNA cap guanine-N7 methyltransferase could open doors to potential therapeutic strategies. Its pivotal function in mRNA processing suggests that modulating its activity could influence gene expression, offering avenues for intervention in diseases where gene expression is dysregulated.

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