Focused On-demand Library for Proteasome subunit beta type-10

Details

Focused On-demand Libraries - Receptor.AI 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.


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

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
P40306

UPID:
PSB10_HUMAN

ALTERNATIVE NAMES:
Low molecular mass protein 10; Macropain subunit MECl-1; Multicatalytic endopeptidase complex subunit MECl-1; Proteasome MECl-1; Proteasome subunit beta-2i

ALTERNATIVE UPACC:
P40306; B2R5J4; Q5U098

BACKGROUND:
The Proteasome subunit beta type-10, known under various names such as Macropain subunit MECl-1, is integral to the proteasome's ATP-dependent proteolytic activity. It is pivotal in cleaving peptides with specific amino acids, facilitating antigen processing for immune system activation.

THERAPEUTIC SIGNIFICANCE:
Linked to the autoinflammatory syndrome Proteasome-associated autoinflammatory syndrome 5, characterized by skin rashes and organ enlargement, the study of Proteasome subunit beta type-10 holds promise for unveiling novel therapeutic avenues. Its role in disease pathogenesis underscores its potential as a therapeutic target.

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