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.


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.


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.


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
Q86U44

UPID:
MTA70_HUMAN

ALTERNATIVE NAMES:
Methyltransferase-like protein 3; N6-adenosine-methyltransferase 70 kDa subunit

ALTERNATIVE UPACC:
Q86U44; O14736; Q86V05; Q9HB32

BACKGROUND:
N6-adenosine-methyltransferase catalytic subunit, known as METTL3, forms a crucial component of the methyltransferase complex, impacting RNA stability and processing. This enzyme's activity is essential for various physiological processes, including T-cell differentiation and spermatogenesis, by regulating mRNA methylation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of N6-adenosine-methyltransferase catalytic subunit unveils promising avenues for drug discovery. Its central role in mRNA processing and stem cell differentiation positions it as a key target in developing treatments for immune disorders and infertility.

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