Focused On-demand Library for E3 ubiquitin-protein ligase CBL-C

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.

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.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Q9ULV8

UPID:

CBLC_HUMAN

Alternative names:

RING finger protein 57; RING-type E3 ubiquitin transferase CBL-C; SH3-binding protein CBL-3; SH3-binding protein CBL-C; Signal transduction protein CBL-C

Alternative UPACC:

Q9ULV8; Q8N1E5; Q9Y5Z2; Q9Y5Z3

Background:

E3 ubiquitin-protein ligase CBL-C, known by alternative names such as RING finger protein 57 and Signal transduction protein CBL-C, plays a pivotal role in cellular processes. It functions as an E3 ubiquitin-protein ligase, facilitating the transfer of ubiquitin from E2 ubiquitin-conjugating enzymes to substrates, thus promoting their degradation. This protein is integral to EGFR mediated signal transduction and regulates the degradation of RET and SRC proteins, impacting cell survival and proliferation.

Therapeutic significance:

Understanding the role of E3 ubiquitin-protein ligase CBL-C could open doors to potential therapeutic strategies.