Focused On-demand Library for Hephaestin

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.

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.

We use our state-of-the-art dedicated workflow for designing focused 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.

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.







Alternative names:


Alternative UPACC:

Q9BQS7; B1AJX8; D3DVT7; E9PHN8; O75180; Q6UW45; Q9C058


Hephaestin, identified by its gene symbol Q9BQS7, plays a crucial role in iron metabolism, acting as a ferroxidase that facilitates the conversion of ferrous (II) to ferric ion (III). This process is essential for iron homeostasis and is closely linked to copper transport within the body. Hephaestin's activity is pivotal in mediating iron efflux in conjunction with ferroportin 1, ensuring proper iron distribution and preventing iron overload.

Therapeutic significance:

Understanding the role of Hephaestin could open doors to potential therapeutic strategies. Its involvement in iron and copper homeostasis positions it as a key target for addressing disorders related to metal metabolism, such as anemia and Wilson's disease. By elucidating Hephaestin's mechanisms, novel treatments for these conditions could be developed, offering hope for patients suffering from metal-related disorders.

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