Focused On-demand Library for Protein arginine N-methyltransferase 5

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

72 kDa ICln-binding protein; Histone-arginine N-methyltransferase PRMT5; Jak-binding protein 1; Shk1 kinase-binding protein 1 homolog

Alternative UPACC:

O14744; A8MTP3; A8MZ91; B4DX49; B4DY30; B5BU10; D3DS33; E2QRE7; Q6IBR1; Q9UKH1


Protein arginine N-methyltransferase 5 (PRMT5) is a versatile enzyme, catalyzing the methylation of arginine residues on various substrates, including histones, signaling proteins, and ribonucleoproteins. Its activity influences cellular processes such as signal transduction, transcriptional regulation, and RNA splicing. PRMT5's ability to modify histones and affect gene expression positions it as a key player in epigenetic regulation.

Therapeutic significance:

Understanding the role of Protein arginine N-methyltransferase 5 could open doors to potential therapeutic strategies. Its involvement in crucial cellular processes and epigenetic regulation makes it a promising target for drug discovery efforts aimed at treating diseases with underlying epigenetic or signaling dysregulation.

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