Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.


PARTNER
Receptor.AI
 
UPACC
Q5VTY9

UPID:
HHAT_HUMAN

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

BACKGROUND:
The enzyme Protein-cysteine N-palmitoyltransferase HHAT, known alternatively as Skinny hedgehog protein 1, is integral to the palmitoylation process of SHH and DHH, facilitating Hedgehog signaling. This signaling is vital for embryonic development and the formation of various organs.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of HHAT could open doors to potential therapeutic strategies for conditions like Nivelon-Nivelon-Mabille syndrome, where HHAT's gene variants play a causative role. Exploring HHAT inhibitors or modulators may provide new insights into treating developmental and skeletal disorders.

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