Focused On-demand Library for Heparanase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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 use our state-of-the-art dedicated workflow for designing 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.

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:

Endo-glucoronidase; Heparanase-1

Alternative UPACC:

Q9Y251; A9JIG7; C7F7I3; C7F7I4; E9PCA9; E9PGR1; Q53GE5; Q9UL39


Heparanase, also known as Endo-glucoronidase or Heparanase-1, is a pivotal enzyme in the degradation and remodeling of the extracellular matrix (ECM). It selectively cleaves heparan sulfate proteoglycans into heparan sulfate side chains and core proteoglycans, playing a crucial role in processes such as tumor invasion, wound healing, and inflammation. Its activity is enhanced under acidic conditions, facilitating cell migration, angiogenesis, and procoagulant activities.

Therapeutic significance:

Understanding the role of Heparanase could open doors to potential therapeutic strategies. Its involvement in ECM degradation, cell migration, and angiogenesis highlights its significance in cancer metastasis and inflammatory diseases, suggesting that targeting Heparanase could offer novel approaches for treatment.

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