Focused On-demand Library for tRNA (cytidine(32)/guanosine(34)-2'-O)-methyltransferase

Details

Focused On-demand Libraries - Receptor.AI 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.


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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q9UET6

UPID:
TRM7_HUMAN

ALTERNATIVE NAMES:
2'-O-ribose RNA methyltransferase TRM7 homolog; Protein ftsJ homolog 1

ALTERNATIVE UPACC:
Q9UET6; B2RCJ0; O75670

BACKGROUND:
tRNA (cytidine(32)/guanosine(34)-2'-O)-methyltransferase, known alternatively as 2'-O-ribose RNA methyltransferase TRM7 homolog or Protein ftsJ homolog 1, is pivotal in tRNA modification, specifically methylating the 2'-O-ribose of nucleotides at critical positions within the anticodon loop. This enzymatic activity is vital for the fidelity of protein synthesis, playing roles in neurogenesis, gene expression related to mitochondrial function and lipid metabolism, and RNA-mediated gene silencing.

THERAPEUTIC SIGNIFICANCE:
The protein's link to Intellectual developmental disorder, X-linked 9 highlights its potential as a target for therapeutic intervention. Exploring the function of tRNA (cytidine(32)/guanosine(34)-2'-O)-methyltransferase offers promising avenues for developing treatments aimed at intellectual developmental disorders and possibly other neurogenetic conditions.

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