Focused On-demand Library for Inactive C-alpha-formylglycine-generating enzyme 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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:

Paralog of formylglycine-generating enzyme; Sulfatase-modifying factor 2

Alternative UPACC:

Q8NBJ7; B4DU41; B4DWQ0; Q14DW5; Q53ZE3; Q96BH2; Q9BRN3; Q9BWI1; Q9Y405


Inactive C-alpha-formylglycine-generating enzyme 2, also known as Sulfatase-modifying factor 2, plays a crucial role in the post-translational modification of sulfatases. It is characterized by its inability to activate newly synthesized sulfatases, a process essential for their enzymatic activity. This protein acts by inhibiting the activation of sulfatases by SUMF1, highlighting its unique function in cellular mechanisms.

Therapeutic significance:

Understanding the role of Inactive C-alpha-formylglycine-generating enzyme 2 could open doors to potential therapeutic strategies. Its involvement in the regulation of sulfatase activity suggests a pivotal role in metabolic pathways, which, if manipulated, could offer novel approaches to treating diseases linked to sulfatase dysfunction.

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