Focused On-demand Library for tRNA N(3)-methylcytidine methyltransferase METTL2A

Details

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 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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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.


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
Q96IZ6

UPID:
MET2A_HUMAN

ALTERNATIVE NAMES:
Methyltransferase-like protein 2A

ALTERNATIVE UPACC:
Q96IZ6; A6NNC4; Q9H9G9; Q9NUI8; Q9P0B5

BACKGROUND:
METTL2A, identified as a key S-adenosyl-L-methionine-dependent methyltransferase, is pivotal in the N(3)-methylcytidine modification of tRNA molecules. This enzyme targets the anticodon loop of specific tRNAs, including tRNA(Thr)(UGU) and tRNA(Arg)(CCU), necessitating prior t6A37 modification by the EKC/KEOPS complex. Such modifications are critical for the fidelity of protein synthesis, underscoring the enzyme's importance in cellular function and genetic expression.

THERAPEUTIC SIGNIFICANCE:
The exploration of tRNA N(3)-methylcytidine methyltransferase METTL2A's function illuminates its potential as a target for therapeutic intervention. Given its central role in the regulation of protein synthesis, strategies to modulate its activity could lead to innovative treatments for diseases linked to genetic translation errors.

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