Focused On-demand Library for Probable 18S rRNA (guanine-N(7))-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.

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 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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.







Alternative names:

Bud site selection protein 23 homolog; Metastasis-related methyltransferase 1; Williams-Beuren syndrome chromosomal region 22 protein; rRNA methyltransferase and ribosome maturation factor

Alternative UPACC:

O43709; A8K501; C9K060; Q96P12; Q9BQ58; Q9HBP9


Probable 18S rRNA (guanine-N(7))-methyltransferase, also known as Bud site selection protein 23 homolog, plays a crucial role in the methylation of the N(7) position of guanine in 18S rRNA, essential for the biogenesis and export of the 40S ribosomal subunit. It functions as a locus-specific steroid receptor coactivator, enhancing the activity of various steroid receptors and is vital for maintaining open chromatin for efficient gene expression.

Therapeutic significance:

Understanding the role of Probable 18S rRNA (guanine-N(7))-methyltransferase could open doors to potential therapeutic strategies, especially in disorders where steroid receptor signaling and ribosome biogenesis are implicated.

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