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 high-tech, dedicated method is applied to construct targeted 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.


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.


PARTNER
Receptor.AI
 
UPACC
P28062

UPID:
PSB8_HUMAN

ALTERNATIVE NAMES:
Low molecular mass protein 7; Macropain subunit C13; Multicatalytic endopeptidase complex subunit C13; Proteasome component C13; Proteasome subunit beta-5i; Really interesting new gene 10 protein

ALTERNATIVE UPACC:
P28062; B0UZC0; Q29824; Q5JNW6; Q5QNR8; Q96J48

BACKGROUND:
The Proteasome subunit beta type-8, known for its alternative names such as Low molecular mass protein 7 and Really interesting new gene 10 protein, is a critical component of the proteasome complex. It is involved in the cleavage of peptides, antigen processing, and plays a vital role in interferon gamma-induced sensitivity, apoptosis, and the inflammatory response.

THERAPEUTIC SIGNIFICANCE:
Linked to Proteasome-associated autoinflammatory syndrome 1, PSMB8's mutation underscores its importance in immune regulation. Exploring PSMB8's functions and mechanisms offers promising avenues for developing targeted therapies for autoinflammatory diseases and enhancing our understanding of immune system dysregulation.

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