Focused On-demand Library for Proteasome subunit beta type-4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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:

26 kDa prosomal protein; Macropain beta chain; Multicatalytic endopeptidase complex beta chain; Proteasome beta chain; Proteasome chain 3

Alternative UPACC:

P28070; B2R9L3; P31148; Q5SZS5; Q6IBI4; Q969L6


Proteasome subunit beta type-4, also known as the 26 kDa prosomal protein, plays a pivotal role in intracellular protein degradation. It is a non-catalytic component of the 20S core proteasome complex, crucial for maintaining cellular functions by removing misfolded or damaged proteins. This protein is involved in both ATP-dependent and independent pathways, essential for processes like spermatogenesis and antigen presentation.

Therapeutic significance:

The protein's association with Proteasome-associated autoinflammatory syndrome 3 highlights its importance in immune regulation and inflammation. Understanding the role of Proteasome subunit beta type-4 could open doors to potential therapeutic strategies for treating autoinflammatory disorders and enhancing immune system precision.

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