Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
Q9Y5N5

UPID:
N6MT1_HUMAN

ALTERNATIVE NAMES:
HemK methyltransferase family member 2; Lysine N-methyltransferase 9; Methylarsonite methyltransferase N6AMT1; Protein N(5)-glutamine methyltransferase

ALTERNATIVE UPACC:
Q9Y5N5; B2RA97; Q96F73

BACKGROUND:
The enzyme Methyltransferase N6AMT1, alternatively named as Lysine N-methyltransferase 9 and Protein N(5)-glutamine methyltransferase, is pivotal in methylating proteins and arsenic. It forms a heterodimer with TRMT112 to monomethylate 'Lys-12' of histone H4 and catalyzes N5-methylation of Glu residues, crucial for cell cycle regulation and protein functionality. Its role in converting monomethylarsonous acid into less toxic forms highlights its potential in detoxification processes.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Methyltransferase N6AMT1 could open doors to potential therapeutic strategies.

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