Focused On-demand Library for Protein-cysteine N-palmitoyltransferase HHAT

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 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 in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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:

Hedgehog acyltransferase; Melanoma antigen recognized by T-cells 2; Skinny hedgehog protein 1

Alternative UPACC:

Q5VTY9; B7Z4D5; B7Z5I1; B7Z868; B7ZA75; D3DT91; F5H444; Q17RZ7; Q4G0K3; Q5CZ95; Q5TGI2; Q9NVH9; Q9Y3N8


Protein-cysteine N-palmitoyltransferase HHAT, also known as Hedgehog acyltransferase, plays a pivotal role in embryonic development and testicular organogenesis through its enzymatic activity. It catalyzes the N-terminal palmitoylation of SHH and DHH, essential for Hedgehog signaling, a pathway critical for cell differentiation and tissue development.

Therapeutic significance:

Given its crucial role in Hedgehog signaling, HHAT's dysfunction is linked to Nivelon-Nivelon-Mabille syndrome, characterized by microcephaly, skeletal dysplasia, and gonadal dysgenesis. Targeting HHAT could offer novel therapeutic avenues for treating this syndrome and potentially other developmental disorders.

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