Focused On-demand Library for E3 ubiquitin-protein ligase TRIM33

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 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 top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Ectodermin homolog; RET-fused gene 7 protein; RING-type E3 ubiquitin transferase TRIM33; Transcription intermediary factor 1-gamma; Tripartite motif-containing protein 33

Alternative UPACC:

Q9UPN9; O95855; Q5TG72; Q5TG73; Q5TG74; Q9C017; Q9UJ79


E3 ubiquitin-protein ligase TRIM33, also known as Ectodermin homolog, plays a pivotal role in cellular processes by acting as an E3 ubiquitin-protein ligase. It is involved in promoting SMAD4 ubiquitination, nuclear exclusion, and degradation, thereby inhibiting the TGF-beta/BMP signaling cascade. This protein's interaction with SMAD2 and SMAD3 is crucial for erythroid differentiation of hematopoietic stem/progenitor cells.

Therapeutic significance:

Understanding the role of E3 ubiquitin-protein ligase TRIM33 could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.