Focused On-demand Library for N-acetylglucosamine-1-phosphotransferase subunits alpha/beta

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

GlcNAc-1-phosphotransferase subunits alpha/beta; Stealth protein GNPTAB; UDP-N-acetylglucosamine-1-phosphotransferase subunits alpha/beta

Alternative UPACC:

Q3T906; A2RRQ9; Q3ZQK2; Q6IPW5; Q86TQ2; Q96N13; Q9ULL2


N-acetylglucosamine-1-phosphotransferase, known by its subunits alpha/beta, plays a pivotal role in lysosomal enzyme targeting. It catalyzes the formation of mannose 6-phosphate markers, essential for the vesicular transport of lysosomal enzymes. This protein's alternative names include GlcNAc-1-phosphotransferase subunits alpha/beta and Stealth protein GNPTAB.

Therapeutic significance:

Mutations in this protein are linked to Mucolipidosis type II and III, severe lysosomal storage disorders. Understanding its function could lead to breakthroughs in treating these debilitating diseases.

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