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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
P08575

UPID:
PTPRC_HUMAN

ALTERNATIVE NAMES:
Leukocyte common antigen; T200

ALTERNATIVE UPACC:
P08575; A0A0A0MT22; A8K7W6; Q16614; Q9H0Y6; X6R433

BACKGROUND:
The protein Receptor-type tyrosine-protein phosphatase C, with alternative names Leukocyte common antigen and T200, is essential for T-cell activation through antigen receptor signaling. It serves as a receptor for human cytomegalovirus protein UL11, influencing T-cell proliferation and immune response.

THERAPEUTIC SIGNIFICANCE:
Receptor-type tyrosine-protein phosphatase C's involvement in Multiple sclerosis and Immunodeficiency 105 highlights its potential as a therapeutic target. Exploring its role in these diseases could lead to innovative treatments that modulate the immune system, offering hope for patients with these challenging conditions.

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