Focused On-demand Library for Palmitoyltransferase ZDHHC17

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.

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.







Alternative names:

Acyltransferase ZDHHC17; DHHC domain-containing cysteine-rich protein 17; Huntingtin yeast partner H; Huntingtin-interacting protein 14; Huntingtin-interacting protein 3; Huntingtin-interacting protein H; Putative MAPK-activating protein PM11; Putative NF-kappa-B-activating protein 205; Zinc finger DHHC domain-containing protein 17

Alternative UPACC:

Q8IUH5; B4DR39; O75407; Q7Z2I0; Q86W89; Q86YK0; Q9P088; Q9UPZ8


Palmitoyltransferase ZDHHC17, known by various names such as Acyltransferase ZDHHC17 and Huntingtin-interacting protein 14, plays a pivotal role in cellular processes by catalyzing the addition of palmitate and other fatty acids onto protein substrates. This enzyme's activity is crucial for the modification of neuronal proteins like SNAP25 and GAD2, influencing axonogenesis and endocytosis initiation.

Therapeutic significance:

Understanding the role of Palmitoyltransferase ZDHHC17 could open doors to potential therapeutic strategies.

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