AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tyrosine-protein phosphatase non-receptor type 22

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 our partner 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 high-tech, dedicated method is applied to construct targeted 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9Y2R2

UPID:

PTN22_HUMAN

Alternative names:

Hematopoietic cell protein-tyrosine phosphatase 70Z-PEP; Lymphoid phosphatase; PEST-domain phosphatase

Alternative UPACC:

Q9Y2R2; A0N0K6; B1ALC8; D4NZ71; E9PLD8; E9PPI1; O95063; O95064; Q6IPX8; Q8WVM1

Background:

Tyrosine-protein phosphatase non-receptor type 22 (PTPN22) plays a pivotal role in immune response regulation. Known by its alternative names, Hematopoietic cell protein-tyrosine phosphatase 70Z-PEP, Lymphoid phosphatase, and PEST-domain phosphatase, PTPN22 is crucial for T-cell receptor signaling, acting as a negative regulator through dephosphorylation of key signaling molecules. Its involvement extends to toll-like receptor-induced type 1 interferon production, highlighting its multifaceted role in biological systems.

Therapeutic significance:

PTPN22's association with autoimmune diseases such as Systemic lupus erythematosus, Type 1 diabetes mellitus, Rheumatoid arthritis, and Vitiligo underscores its therapeutic significance. Understanding the role of PTPN22 could open doors to potential therapeutic strategies, offering hope for targeted treatments in these complex conditions.

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