Focused On-demand Library for Protein arginine N-methyltransferase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.







Alternative names:

Heterogeneous nuclear ribonucleoprotein methyltransferase-like protein 3

Alternative UPACC:

O60678; A0A0A0MSN7; B4DUC7


Protein arginine N-methyltransferase 3 (PRMT3), also known as Heterogeneous nuclear ribonucleoprotein methyltransferase-like protein 3, plays a pivotal role in the methylation of arginine residues in target proteins. This enzyme belongs to the type I methyltransferases, capable of catalyzing both monomethylation and asymmetric dimethylation. PRMT3's activity is crucial for modulating retinoic acid synthesis and signaling pathways, primarily through the inhibition of ALDH1A1 retinal dehydrogenase activity.

Therapeutic significance:

Understanding the role of Protein arginine N-methyltransferase 3 could open doors to potential therapeutic strategies. Its involvement in retinoic acid synthesis and signaling pathways highlights its potential as a target for developing treatments for conditions related to these biological processes.

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