Focused On-demand Library for Protein arginine N-methyltransferase 8

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted 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.


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
Q9NR22

UPID:
ANM8_HUMAN

ALTERNATIVE NAMES:
Heterogeneous nuclear ribonucleoprotein methyltransferase-like protein 4

ALTERNATIVE UPACC:
Q9NR22; B2RDP0; Q8TBJ8

BACKGROUND:
The enzyme Protein arginine N-methyltransferase 8, with alternative name Heterogeneous nuclear ribonucleoprotein methyltransferase-like protein 4, plays a pivotal role in the methylation of arginine residues on various proteins, including NIFK, myelin basic protein, and histones. This S-adenosyl-L-methionine-dependent and membrane-associated arginine methyltransferase is crucial for the regulation of protein function through the generation of omega-N monomethylarginine and asymmetrical dimethylarginine.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Protein arginine N-methyltransferase 8 unveils potential pathways for therapeutic intervention.

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