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

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.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
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:
The protein E3 ubiquitin-protein ligase CBL-C, also recognized as RING-type E3 ubiquitin transferase CBL-C, is crucial for ubiquitination processes, affecting protein degradation via the proteasome. It is functionally associated with E2 ubiquitin-protein ligases UB2D1, UB2D2, and UB2D3 and plays a regulatory role in EGFR signal transduction. Its activity influences MAPK1 activation and the ubiquitination of phosphorylated SRC, thereby modulating cellular signaling pathways.

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

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