AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Receptor-type tyrosine-protein phosphatase C

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, 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 utilise our cutting-edge, exclusive workflow to develop focused 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.

partner

Reaxense

upacc

P08575

UPID:

PTPRC_HUMAN

Alternative names:

Leukocyte common antigen; T200

Alternative UPACC:

P08575; A0A0A0MT22; A8K7W6; Q16614; Q9H0Y6; X6R433

Background:

Receptor-type tyrosine-protein phosphatase C, also known as Leukocyte common antigen or T200, plays a pivotal role in T-cell activation and immune response regulation. It acts as a positive regulator of T-cell coactivation upon binding to DPP4 and modulates the activity of several kinases, including LYN and FYN, crucial for T-cell function.

Therapeutic significance:

Given its critical role in T-cell activation and its involvement in diseases like Multiple sclerosis and Immunodeficiency 105, targeting Receptor-type tyrosine-protein phosphatase C could offer novel therapeutic avenues. Understanding its function and interaction pathways opens doors to potential strategies for modulating immune responses in these conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.