AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-protein ligase E3C

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Reaxense

upacc

Q15386

UPID:

UBE3C_HUMAN

Alternative names:

HECT-type ubiquitin transferase E3C; Homologous to E6AP carboxyl terminus homologous protein 2; RTA-associated ubiquitin ligase

Alternative UPACC:

Q15386; A4D235; A6NCP3; Q8TC15; Q96CR4; Q9UDU3

Background:

Ubiquitin-protein ligase E3C, known for its roles in protein ubiquitination, catalyzes 'Lys-29'- and 'Lys-48'-linked polyubiquitin chains. It interacts with the proteasome to promote ubiquitin chain elongation on substrates, facilitating their degradation. This protein also regulates autophagy and type I interferon response through targeted ubiquitination, showcasing its pivotal role in cellular processes.

Therapeutic significance:

Understanding the role of Ubiquitin-protein ligase E3C could open doors to potential therapeutic strategies.

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