Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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.


PARTNER
Receptor.AI
 
UPACC
Q13332

UPID:
PTPRS_HUMAN

ALTERNATIVE NAMES:
Receptor-type tyrosine-protein phosphatase sigma

ALTERNATIVE UPACC:
Q13332; O75255; O75870; Q15718; Q16341; Q2M3R7

BACKGROUND:
Receptor-type tyrosine-protein phosphatase S, a crucial enzyme in cellular signaling, binds to glycosaminoglycans affecting neurite outgrowth through its interaction with chondroitin sulfate and heparan sulfate proteoglycans. It plays a significant role in brain development, particularly in the formation of the pituitary gland and olfactory bulb. As a tyrosine phosphatase, it is involved in the dephosphorylation of NTRK1, NTRK2, and NTRK3, and regulates signaling pathways leading to Akt and MAP kinases activation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Receptor-type tyrosine-protein phosphatase S could open doors to potential therapeutic strategies.

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