Focused On-demand Library for Protein arginine N-methyltransferase 7

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.


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 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.


We use our state-of-the-art dedicated workflow for designing focused 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
Q9NVM4

UPID:
ANM7_HUMAN

ALTERNATIVE NAMES:
Histone-arginine N-methyltransferase PRMT7; [Myelin basic protein]-arginine N-methyltransferase PRMT7

ALTERNATIVE UPACC:
Q9NVM4; B3KPR0; B3KUG9; B4E379; Q96PV5; Q9H9L0

BACKGROUND:
Histone-arginine N-methyltransferase PRMT7 plays a pivotal role in the post-translational modification of proteins through arginine methylation. This enzyme is crucial for the symmetric dimethylation of arginine residues in proteins such as Sm D1 and Sm D3, which are necessary for snRNP core particle biogenesis. Additionally, PRMT7's involvement in histone H4 methylation at the H19 imprinted control region suggests a significant role in gene imprinting and embryonic development.

THERAPEUTIC SIGNIFICANCE:
Given PRMT7's association with a genetic disorder leading to impaired intellectual development and skeletal issues, targeting this protein could offer novel therapeutic avenues. Understanding the role of PRMT7 could open doors to potential therapeutic strategies, providing hope for patients suffering from related genetic conditions.

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