Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 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.


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
Receptor.AI
 
UPACC
P35236

UPID:
PTN7_HUMAN

ALTERNATIVE NAMES:
Hematopoietic protein-tyrosine phosphatase; Protein-tyrosine phosphatase LC-PTP

ALTERNATIVE UPACC:
P35236; B3KXE1; Q53XK4; Q5SXQ0; Q5SXQ1; Q9BV05

BACKGROUND:
The enzyme Tyrosine-protein phosphatase non-receptor type 7, known alternatively as Hematopoietic protein-tyrosine phosphatase and Protein-tyrosine phosphatase LC-PTP, with the unique identifier P35236, acts primarily on tyrosine-phosphorylated MAPK1. It is instrumental in regulating the development and signal transduction of T and B-lymphocytes, highlighting its significance in cellular communication and immune regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Tyrosine-protein phosphatase non-receptor type 7 unveils potential avenues for therapeutic intervention. Given its essential role in lymphocyte signaling and development, targeting this protein could lead to innovative treatments for modulating the immune system.

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