AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein phosphatase PTC7 homolog

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening 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.

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

Q8NI37

UPID:

PPTC7_HUMAN

Alternative names:

T-cell activation protein phosphatase 2C; T-cell activation protein phosphatase 2C-like

Alternative UPACC:

Q8NI37; B3KWC5; Q68DZ7; Q6UY82

Background:

Protein phosphatase PTC7 homolog, also known as T-cell activation protein phosphatase 2C, plays a pivotal role in the biosynthesis of ubiquinone, coenzyme Q. It achieves this by dephosphorylating the ubiquinone biosynthesis protein COQ7, likely leading to its activation. This process is crucial for cellular energy production and antioxidant defense.

Therapeutic significance:

Understanding the role of Protein phosphatase PTC7 homolog could open doors to potential therapeutic strategies. Its involvement in coenzyme Q biosynthesis suggests a significant impact on cellular metabolism and diseases related to mitochondrial dysfunction.

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