Focused On-demand Library for Protein arginine N-methyltransferase 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

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

 Fig. 1. The sreening 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Histone-arginine N-methyltransferase PRMT2

Alternative UPACC:

P55345; B7U630; B7U631; B7U632; P78350; Q498Y5; Q5U7D4; Q6FHF0; Q99781; Q9BW15; Q9UMC2


Protein arginine N-methyltransferase 2 (PRMT2), also known as Histone-arginine N-methyltransferase PRMT2, plays a pivotal role in the methylation of arginyl residues within proteins such as STAT3, FBL, and histone H4. It functions as a coactivator for hormone receptors including the androgen receptor (AR) and estrogen receptor (ER), enhancing their mediated transactivation. PRMT2 also contributes to the regulation of transcription factors like NF-kappa-B and E2F1, potentially influencing apoptosis and growth regulation.

Therapeutic significance:

Understanding the role of Protein arginine N-methyltransferase 2 could open doors to potential therapeutic strategies.

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