Focused On-demand Library for Hyaluronan-binding protein 2

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

PARTNER
Receptor.AI
 
UPACC
Q14520

UPID:
HABP2_HUMAN

ALTERNATIVE NAMES:
Factor VII-activating protease; Factor seven-activating protease; Hepatocyte growth factor activator-like protein; Plasma hyaluronan-binding protein

ALTERNATIVE UPACC:
Q14520; A8K467; B7Z8U5; F5H5M6; O00663

BACKGROUND:
The Hyaluronan-binding protein 2, with alternative names such as Factor VII-activating protease, is instrumental in the regulation of blood coagulation and cellular processes. It does not directly cause fibrinolysis but activates crucial factors in the coagulation pathway and may act as a tumor suppressor by regulating cell growth and migration. Its activity highlights its importance in maintaining physiological balance and cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
The involvement of Hyaluronan-binding protein 2 in non-medullary thyroid cancer underscores its potential as a therapeutic target. The protein's ability to influence cell proliferation and migration, coupled with its role in the coagulation cascade, makes it a candidate for the development of novel therapeutic approaches aimed at treating thyroid cancer and exploring its utility in other cancer types.

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