Focused On-demand Library for Receptor-type tyrosine-protein phosphatase N2

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 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.

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 utilise our cutting-edge, exclusive workflow to develop focused 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.

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:

Islet cell autoantigen-related protein; Phogrin

Alternative UPACC:

Q92932; E9PC57; Q8N4I5; Q92662; Q9Y4F8; Q9Y4I6


Receptor-type tyrosine-protein phosphatase N2, also known as Phogrin and Islet cell autoantigen-related protein, plays a crucial role in vesicle-mediated secretory processes. It is essential for the normal accumulation of secretory vesicles in the hippocampus, pituitary, and pancreatic islets, facilitating the accumulation of insulin-containing vesicles and preventing their degradation. This protein is pivotal in insulin secretion in response to glucose stimuli and maintains normal levels of neurotransmitters such as norepinephrine, dopamine, and serotonin in the brain. It also has a significant role in the regulation of pituitary hormones and renin expression.

Therapeutic significance:

Understanding the role of Receptor-type tyrosine-protein phosphatase N2 could open doors to potential therapeutic strategies, especially in the management of diabetes through its involvement in insulin secretion and the maintenance of neurotransmitter levels, which could influence psychiatric disorders.

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