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

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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.


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


 

Fig. 1. The screening 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 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.

PARTNER
Receptor.AI
 
UPACC
Q92932

UPID:
PTPR2_HUMAN

ALTERNATIVE NAMES:
Islet cell autoantigen-related protein; Phogrin

ALTERNATIVE UPACC:
Q92932; E9PC57; Q8N4I5; Q92662; Q9Y4F8; Q9Y4I6

BACKGROUND:
The protein Receptor-type tyrosine-protein phosphatase N2, known alternatively as Phogrin, is integral to the regulation of secretory vesicle accumulation in various tissues, including the hippocampus and pancreatic islets. It ensures the proper levels of insulin-containing vesicles, playing a key role in glucose-stimulated insulin secretion. Furthermore, it is involved in the accumulation of neurotransmitters in the brain and the regulation of pituitary hormone secretion in females. Its enzymatic activity includes phosphatidylinositol phosphatase activity, crucial for its regulatory functions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Receptor-type tyrosine-protein phosphatase N2 offers a promising avenue for developing novel therapeutic approaches, particularly in treating endocrine disorders and potentially impacting mental health through its effect on neurotransmitter levels.

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