Focused On-demand Library for tRNA (guanine(26)-N(2))-dimethyltransferase

Details

Focused On-demand Libraries - Receptor.AI 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 screening 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.


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
Receptor.AI
 
UPACC
Q9NXH9

UPID:
TRM1_HUMAN

ALTERNATIVE NAMES:
tRNA 2,2-dimethylguanosine-26 methyltransferase; tRNA(guanine-26,N(2)-N(2)) methyltransferase; tRNA(m(2,2)G26)dimethyltransferase

ALTERNATIVE UPACC:
Q9NXH9; O76103; Q548Y5; Q8WVA6

BACKGROUND:
tRNA(m(2,2)G26)dimethyltransferase, with alternative names such as tRNA(guanine-26,N(2)-N(2)) methyltransferase, is essential for the chemical modification of transfer RNAs (tRNAs). This enzyme specifically targets the guanine residue at the 26th position of most tRNAs for dimethylation, a process critical for tRNA maturation and function.

THERAPEUTIC SIGNIFICANCE:
The exploration of tRNA(m(2,2)G26)dimethyltransferase's function offers a promising avenue for drug discovery. Given its link to Intellectual developmental disorder, autosomal recessive 68, targeting this enzyme could lead to innovative treatments for intellectual disabilities, showcasing the therapeutic potential of understanding its biological role.

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