Focused On-demand Library for Proteasome subunit beta type-9

Details

Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We use our state-of-the-art dedicated workflow for designing 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
P28065

UPID:
PSB9_HUMAN

ALTERNATIVE NAMES:
Low molecular mass protein 2; Macropain chain 7; Multicatalytic endopeptidase complex chain 7; Proteasome chain 7; Proteasome subunit beta-1i; Really interesting new gene 12 protein

ALTERNATIVE UPACC:
P28065; B0V0T1; Q16523; Q5JNW4

BACKGROUND:
Proteasome subunit beta type-9, alternatively named as Macropain chain 7 or Proteasome chain 7, is integral to the proteasome's ATP-dependent proteolytic activity. It is specifically involved in antigen processing, facilitating the generation of peptides that bind to class I molecules. This activity is crucial for the immune system's ability to recognize and respond to pathogens.

THERAPEUTIC SIGNIFICANCE:
The involvement of Proteasome subunit beta type-9 in Proteasome-associated autoinflammatory syndrome 3 highlights its potential as a target for therapeutic intervention. By elucidating the protein's role in disease, researchers can develop strategies to modulate its function, offering hope for treatments that could alleviate symptoms and manage the progression of autoinflammatory conditions.

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