AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-like-conjugating enzyme ATG10

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H0Y0

UPID:

ATG10_HUMAN

Alternative names:

Autophagy-related protein 10

Alternative UPACC:

Q9H0Y0; B2RE09; Q6PIX1; Q9H842

Background:

Ubiquitin-like-conjugating enzyme ATG10, also known as Autophagy-related protein 10, plays a pivotal role in autophagy, a critical cellular process for maintaining homeostasis and cell survival under stress conditions. It functions as an E2-like enzyme, facilitating the conjugation of ATG12 to ATG5, an essential step for the autophagy pathway. This enzyme is specifically recognized for its role in ATG5 conjugation, distinguishing it from other enzymes involved in autophagy.

Therapeutic significance:

Understanding the role of Ubiquitin-like-conjugating enzyme ATG10 could open doors to potential therapeutic strategies. Its involvement in autophagy, a process crucial for cellular health and response to stress, highlights its potential as a target for therapeutic intervention in diseases where autophagy regulation is disrupted.

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