Focused On-demand Library for Serine protease HTRA2, mitochondrial

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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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.

PARTNER
Receptor.AI
 
UPACC
O43464

UPID:
HTRA2_HUMAN

ALTERNATIVE NAMES:
High temperature requirement protein A2; Omi stress-regulated endoprotease; Serine protease 25; Serine proteinase OMI

ALTERNATIVE UPACC:
O43464; Q9HBZ4; Q9P0Y3; Q9P0Y4

BACKGROUND:
Known by various names including Omi stress-regulated endoprotease and Serine protease 25, Serine protease HTRA2 is pivotal in apoptosis and cellular stress responses. Its proteolytic inactivity in certain isoforms suggests a complex regulatory mechanism, indicating its multifaceted role in biological systems.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Serine protease HTRA2 could open doors to potential therapeutic strategies. Its association with diseases such as 3-methylglutaconic aciduria 8 and Parkinson disease 13 highlights its importance in disease mechanisms, offering a promising target for drug discovery efforts.

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