Focused On-demand Library for Ubiquitin-conjugating enzyme E2 Q2

Details

Focused On-demand Libraries - Receptor.AI 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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
Receptor.AI
 
UPACC
Q8WVN8

UPID:
UB2Q2_HUMAN

ALTERNATIVE NAMES:
E2 ubiquitin-conjugating enzyme Q2; Ubiquitin carrier protein Q2; Ubiquitin-protein ligase Q2

ALTERNATIVE UPACC:
Q8WVN8; B7Z3Q2; H3BRG2; Q8N4G6; Q96J08

BACKGROUND:
The Ubiquitin-conjugating enzyme E2 Q2, known for its roles in the ubiquitin-proteasome pathway, is essential for the 'Lys-48'-linked polyubiquitination process. This enzyme, functioning as a critical intermediary, facilitates the transfer of ubiquitin to target proteins, thereby marking them for degradation or altering their function.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Ubiquitin-conjugating enzyme E2 Q2 offers a promising avenue for drug discovery. Its key role in protein ubiquitination processes makes it a potential target for therapeutic intervention in diseases where protein homeostasis is disrupted.

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