AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-like-conjugating enzyme ATG3

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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9NT62

UPID:

ATG3_HUMAN

Alternative names:

Autophagy-related protein 3; Protein PC3-96

Alternative UPACC:

Q9NT62; Q6PKC5; Q9H6L9

Background:

Ubiquitin-like-conjugating enzyme ATG3, also known as Autophagy-related protein 3 or Protein PC3-96, plays a pivotal role in autophagy, mitochondrial homeostasis, and the cytoplasm to vacuole transport (Cvt). It is essential for the E2-like covalent binding of phosphatidylethanolamine to ATG8-like proteins, facilitating their membrane association, which is crucial for autophagy and Cvt. ATG3 also acts as an autocatalytic E2-like enzyme in the conjugation of ATG12, affecting mitochondrial homeostasis.

Therapeutic significance:

Understanding the role of Ubiquitin-like-conjugating enzyme ATG3 could open doors to potential therapeutic strategies.

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