Focused On-demand Library for Hepatocyte growth factor

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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.

PARTNER
Receptor.AI
 
UPACC
P14210

UPID:
HGF_HUMAN

ALTERNATIVE NAMES:
Hepatopoietin-A; Scatter factor

ALTERNATIVE UPACC:
P14210; A1L3U6; Q02935; Q13494; Q14519; Q3KRB2; Q8TCE2; Q9BYL9; Q9BYM0; Q9UDU6

BACKGROUND:
The Hepatocyte growth factor, known alternatively as Hepatopoietin-A and Scatter factor, plays a crucial role in tissue regeneration and cellular growth. It is identified by the unique identifier P14210 and is a key activator of the receptor tyrosine kinase MET, facilitating its dimerization and subsequent activation of MAPK signaling. This protein is a broad-spectrum growth factor, influencing a variety of tissues and cell types.

THERAPEUTIC SIGNIFICANCE:
Associated with 'Deafness, autosomal recessive, 39', a condition characterized by sensorineural deafness due to genetic variants in its encoding gene, Hepatocyte growth factor's study offers promising avenues for developing targeted therapies. Its involvement in critical growth and signaling pathways underscores its potential in devising new therapeutic strategies.

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