Focused On-demand Library for E3 ubiquitin-protein ligase RNF43

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We utilise our cutting-edge, exclusive workflow to develop focused 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

RING finger protein 43; RING-type E3 ubiquitin transferase RNF43

Alternative UPACC:

Q68DV7; A8K4R2; B7Z443; B7Z5D5; B7Z5J5; Q65ZA4; Q6AI04; Q9NXD0


E3 ubiquitin-protein ligase RNF43, also known as RING finger protein 43, plays a pivotal role in the regulation of the Wnt signaling pathway. It achieves this by mediating the ubiquitination, endocytosis, and subsequent degradation of Wnt receptor complex components, impacting both canonical and non-canonical Wnt signaling pathways. This protein's activity is crucial in governing limb specification, alongside RSPO2 and ZNRF3.

Therapeutic significance:

RNF43 is linked to Sessile Serrated Polyposis Cancer Syndrome (SSPCS), a condition marked by an increased risk of colorectal cancer due to the presence of multiple or large serrated polyps in the colon. Understanding the role of RNF43 could open doors to potential therapeutic strategies for SSPCS, leveraging its critical function in Wnt signaling pathway regulation.

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