AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Hyaluronidase-2

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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

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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q12891

UPID:

HYAL2_HUMAN

Alternative names:

Hyaluronoglucosaminidase-2; Lung carcinoma protein 2

Alternative UPACC:

Q12891; B3KRZ2; O15177; Q9BW29

Background:

Hyaluronidase-2, also known as Hyaluronoglucosaminidase-2 or Lung carcinoma protein 2, plays a crucial role in the hydrolysis of high molecular weight hyaluronic acid. This process produces intermediate-sized products, which are further broken down into small oligosaccharides by sperm hyaluronidase. Despite its low activity levels, Hyaluronidase-2 is significant for its association with and regulation of MST1R.

Therapeutic significance:

Understanding the role of Hyaluronidase-2 could open doors to potential therapeutic strategies. Its involvement in the breakdown of hyaluronic acid and regulation of MST1R highlights its potential as a target in therapeutic interventions.

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