Focused On-demand Library for Fetuin-B

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.







Alternative names:

16G2; Fetuin-like protein IRL685; Gugu

Alternative UPACC:

Q9UGM5; B2RCW6; E9PG06; Q1RMZ0; Q5J876; Q6DK58; Q6GRB6; Q9Y6Z0


Fetuin-B, also known by alternative names such as 16G2, Fetuin-like protein IRL685, and Gugu, plays a crucial role in reproductive biology. It acts as a protease inhibitor essential for egg fertilization, specifically preventing premature hardening of the zona pellucida by inhibiting the protease activity of ASTL. This process is vital for ensuring successful fertilization, as it prevents the zona pellucida from becoming impenetrable to sperm.

Therapeutic significance:

Understanding the role of Fetuin-B could open doors to potential therapeutic strategies. Its critical function in preventing premature zona pellucida hardening suggests its potential in addressing fertility issues. By targeting the mechanisms by which Fetuin-B operates, new treatments for infertility could be developed, offering hope to those struggling to conceive.

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