Focused On-demand Library for Ubiquitin-conjugating enzyme E2 Z

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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.

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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

E2 ubiquitin-conjugating enzyme Z; Uba6-specific E2 conjugating enzyme 1; Ubiquitin carrier protein Z; Ubiquitin-protein ligase Z

Alternative UPACC:

Q9H832; A6N8M6; A6NC60; Q7L354; Q8TCM4; Q9H893


Ubiquitin-conjugating enzyme E2 Z, also known as E2 ubiquitin-conjugating enzyme Z, Uba6-specific E2 conjugating enzyme 1, Ubiquitin carrier protein Z, and Ubiquitin-protein ligase Z, plays a pivotal role in protein ubiquitination. This enzyme catalyzes the covalent attachment of ubiquitin to other proteins, a process crucial for protein degradation, cell cycle regulation, and DNA repair. It is a specific substrate for UBA6, distinguishing it from other enzymes charged by UBE1, and is implicated in apoptosis regulation.

Therapeutic significance:

Understanding the role of Ubiquitin-conjugating enzyme E2 Z could open doors to potential therapeutic strategies.

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