Focused On-demand Library for Hepatocyte growth factor

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.

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.

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 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

Hepatopoietin-A; Scatter factor

Alternative UPACC:

P14210; A1L3U6; Q02935; Q13494; Q14519; Q3KRB2; Q8TCE2; Q9BYL9; Q9BYM0; Q9UDU6


Hepatocyte growth factor, also known as Hepatopoietin-A and Scatter factor, is a pivotal protein encoded by the gene with accession number P14210. It functions as a potent mitogen for mature parenchymal hepatocyte cells and acts as a hepatotrophic factor. Additionally, it serves as a growth factor for a wide range of tissues and cell types, and is the activating ligand for the receptor tyrosine kinase MET, promoting its dimerization and activating MAPK signaling.

Therapeutic significance:

The protein is linked to 'Deafness, autosomal recessive, 39', a profound prelingual sensorineural hearing loss, highlighting its potential in therapeutic strategies targeting genetic variants affecting this gene. Understanding the role of Hepatocyte growth factor could open doors to innovative treatments for sensorineural deafness and other related conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.