Focused On-demand Library for Dual specificity protein phosphatase 23

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

PARTNER
Receptor.AI
 
UPACC
Q9BVJ7

UPID:
DUS23_HUMAN

ALTERNATIVE NAMES:
Low molecular mass dual specificity phosphatase 3; VH1-like phosphatase Z

ALTERNATIVE UPACC:
Q9BVJ7; Q9NX48

BACKGROUND:
The protein Dual specificity protein phosphatase 23, with alternative names Low molecular mass dual specificity phosphatase 3 and VH1-like phosphatase Z, is pivotal in the dephosphorylation of Tyr and Ser/Thr phosphorylated proteins. Notably, it can dephosphorylate p44-ERK1 (MAPK3) but not p54 SAPK-beta (MAPK10) in vitro, distinguishing its substrate specificity. Its role in enhancing the activation of JNK and p38 (MAPK14) underscores its significance in modulating key signaling pathways.

THERAPEUTIC SIGNIFICANCE:
The exploration of Dual specificity protein phosphatase 23's function offers promising avenues for therapeutic intervention. By targeting the specific mechanisms through which DUSP23 influences signaling pathways, particularly those involving p44-ERK1, JNK, and p38, novel therapeutic strategies could be developed to manage diseases where these pathways are dysregulated.

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