Focused On-demand Library for Ubiquitin-conjugating enzyme E2Q-like protein 1

Details

Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 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.


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
Receptor.AI
 
UPACC
A1L167

UPID:
U2QL1_HUMAN

ALTERNATIVE NAMES:
E2Q-like ubiquitin-conjugating enzyme 1

ALTERNATIVE UPACC:
A1L167

BACKGROUND:
The Ubiquitin-conjugating enzyme E2Q-like protein 1, identified by the alternative name E2Q-like ubiquitin-conjugating enzyme 1, is a probable E2 ubiquitin-protein ligase. It catalyzes the attachment of ubiquitin to target proteins, playing a key role in the ubiquitin-proteasome system. This enzyme's interaction with FBXW7 aids in the degradation of MTOR and CCNE1, crucial for cell cycle regulation and growth.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Ubiquitin-conjugating enzyme E2Q-like protein 1 offers a pathway to novel therapeutic approaches. Its critical role in protein degradation and cell cycle control underscores its potential as a target in disease treatment and management.

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