Focused On-demand Library for Dual specificity protein phosphatase 23

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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.







Alternative names:

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

Alternative UPACC:

Q9BVJ7; Q9NX48


Dual specificity protein phosphatase 23 (DUSP23), also known as Low molecular mass dual specificity phosphatase 3 and VH1-like phosphatase Z, plays a crucial role in cellular processes by mediating the dephosphorylation of proteins phosphorylated on Tyr and Ser/Thr residues. It has a specific ability to dephosphorylate p44-ERK1 (MAPK3) in vitro, showcasing its selective action on signaling molecules. Furthermore, DUSP23 enhances the activation of JNK and p38 (MAPK14), indicating its involvement in critical signaling pathways.

Therapeutic significance:

Understanding the role of Dual specificity protein phosphatase 23 could open doors to potential therapeutic strategies. Its selective action on key signaling molecules like p44-ERK1 and its ability to modulate JNK and p38 pathways highlight its potential as a target in designing drugs aimed at regulating cellular processes and signaling pathways involved in various diseases.

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