AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for mRNA (2'-O-methyladenosine-N(6)-)-methyltransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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 high-tech, dedicated method is applied to construct targeted 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9H4Z3

UPID:

CAPAM_HUMAN

Alternative names:

Cap-specific adenosine methyltransferase; Phosphorylated CTD-interacting factor 1; Protein phosphatase 1 regulatory subunit 121

Alternative UPACC:

Q9H4Z3; E1P5P1; Q54AB9; Q9NT85

Background:

The mRNA (2'-O-methyladenosine-N(6)-)-methyltransferase, also known as Cap-specific adenosine methyltransferase, plays a pivotal role in mRNA processing. It catalyzes the formation of N(6),2'-O-dimethyladenosine cap (m6A(m)) on the second transcribed position of capped mRNAs. This enzyme is integral to the early elongation complex of RNA polymerase II, highlighting its essential function in gene expression regulation.

Therapeutic significance:

Understanding the role of mRNA (2'-O-methyladenosine-N(6)-)-methyltransferase could open doors to potential therapeutic strategies. Its critical function in mRNA processing and gene expression regulation makes it a promising target for drug discovery, offering new avenues for treating diseases at the genetic and molecular levels.

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