Focused On-demand Library for N-acylneuraminate-9-phosphatase

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.

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

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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:

Haloacid dehalogenase-like hydrolase domain-containing protein 4; Neu5Ac-9-Pase

Alternative UPACC:

Q8TBE9; B3KP12; Q5JYN8; Q8TE97; Q9Y3N0


N-acylneuraminate-9-phosphatase, also known by its alternative names Haloacid dehalogenase-like hydrolase domain-containing protein 4 and Neu5Ac-9-Pase, plays a crucial role in the metabolism of sialic acids, which are key components of cell membranes and are involved in cellular communication and pathogen recognition. This protein's enzymatic activity is pivotal in the catabolism of sialic acids, facilitating their recycling within the cell.

Therapeutic significance:

Understanding the role of N-acylneuraminate-9-phosphatase could open doors to potential therapeutic strategies. Its involvement in the metabolism of sialic acids, crucial for cellular communication, suggests that modulating its activity could have implications for diseases where cell signaling is disrupted.

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