Focused On-demand Library for Tyrosine-protein phosphatase non-receptor type 11

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 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 our associate Reaxense.

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.

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

 Fig. 1. The sreening 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.

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:

Protein-tyrosine phosphatase 1D; Protein-tyrosine phosphatase 2C; SH-PTP2; SH-PTP3

Alternative UPACC:

Q06124; A8K1D9; Q96HD7


Tyrosine-protein phosphatase non-receptor type 11, also known as Protein-tyrosine phosphatase 1D, Protein-tyrosine phosphatase 2C, SH-PTP2, and SH-PTP3, plays a pivotal role in signal transduction from the cell surface to the nucleus. It acts downstream of various receptor and cytoplasmic protein tyrosine kinases, positively regulating the MAPK signal transduction pathway. This protein is involved in the dephosphorylation of several key proteins including GAB1, ARHGAP35, EGFR, ROCK2, CDC73, SOX9, and NEDD9/CAS-L, influencing various cellular processes.

Therapeutic significance:

Tyrosine-protein phosphatase non-receptor type 11 is implicated in several diseases such as LEOPARD syndrome 1, Noonan syndrome 1, juvenile myelomonocytic leukemia, and metachondromatosis. These associations highlight its critical role in disease mechanisms and underscore the potential of targeting this protein for therapeutic interventions in these genetic disorders.

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