Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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.


PARTNER
Receptor.AI
 
UPACC
Q9UBP6

UPID:
TRMB_HUMAN

ALTERNATIVE NAMES:
Methyltransferase-like protein 1; mRNA (guanine-N(7)-)-methyltransferase; miRNA (guanine-N(7)-)-methyltransferase; tRNA (guanine(46)-N(7))-methyltransferase; tRNA(m7G46)-methyltransferase

ALTERNATIVE UPACC:
Q9UBP6; B2RBX1; H7BXF2; Q14105; Q53FS9

BACKGROUND:
tRNA (guanine-N(7)-)-methyltransferase, also known as Methyltransferase-like protein 1, plays a critical role in the methylation of N(7)-guanine in RNA. This enzymatic activity is essential for the proper folding and function of tRNAs, the regulation of mRNA translation efficiency, and the processing of miRNAs, such as let-7, which is crucial for gene expression regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of tRNA (guanine-N(7)-)-methyltransferase unveils potential pathways for therapeutic intervention. Its central role in RNA biology makes it a compelling target for addressing disorders linked to RNA metabolism and function.

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