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.


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 Reaxense.


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.


We employ our advanced, specialised process to create 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
Q8TCB7

UPID:
METL6_HUMAN

ALTERNATIVE NAMES:
Methyltransferase-like protein 6

ALTERNATIVE UPACC:
Q8TCB7; Q96LU4

BACKGROUND:
tRNA N(3)-methylcytidine methyltransferase METTL6, alternatively named Methyltransferase-like protein 6, is a key enzyme in the methylation of tRNA, specifically targeting the anticodon loop of tRNA(Ser). This S-adenosyl-L-methionine-dependent methyltransferase's activity is crucial for the proper decoding of mRNA, thereby ensuring the fidelity of protein synthesis. Its interaction with SARS1/SerRS is necessary for its methyltransferase activity, indicating a tightly regulated process.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of tRNA N(3)-methylcytidine methyltransferase METTL6 holds promise for unveiling new therapeutic avenues. Given its central role in the methylation of tRNA, targeting METTL6 could lead to innovative treatments that modulate protein synthesis, potentially addressing a wide range of diseases.

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