Focused On-demand Library for Tetraspanin-12

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for protein-protein interfaces.

 Fig. 1. The sreening workflow of Receptor.AI

It includes extensive molecular simulations of the target alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that accounts for conformational mobility in free and bound forms. The tentative binding pockets are considered on the protein-protein interface itself and in remote allosteric locations in order to cover the whole spectrum of possible mechanisms of action.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Tetraspan NET-2; Transmembrane 4 superfamily member 12

Alternative UPACC:

O95859; A4D0V8; B4DRG6; Q549U9; Q8N5Y0


Tetraspanin-12, also known as Transmembrane 4 superfamily member 12, plays a pivotal role in retinal vascularization. It regulates cell surface receptor signal transduction, specifically through norrin (NDP) signal transduction, promoting FZD4 multimerization and beta-catenin accumulation. This process is crucial for LEF/TCF-mediated transcriptional programs. Additionally, Tetraspanin-12 is involved in activating cleavage activity of membrane proteinases such as ADAM10 and MMP14/MT1-MMP.

Therapeutic significance:

Tetraspanin-12 mutations are linked to Vitreoretinopathy, exudative 5, a disorder causing retinal detachment and blindness. Understanding the role of Tetraspanin-12 could open doors to potential therapeutic strategies for treating or managing this condition, highlighting its significance in medical research and drug discovery.

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