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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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.


PARTNER
Receptor.AI
 
UPACC
Q969U7

UPID:
PSMG2_HUMAN

ALTERNATIVE NAMES:
Hepatocellular carcinoma-susceptibility protein 3; Tumor necrosis factor superfamily member 5-induced protein 1

ALTERNATIVE UPACC:
Q969U7; B0YJB3; Q6IAH4; Q9NRV1; V9GYH7

BACKGROUND:
The Proteasome assembly chaperone 2, with alternative names Hepatocellular carcinoma-susceptibility protein 3 and Tumor necrosis factor superfamily member 5-induced protein 1, is integral to the proteasome assembly process. It forms a heterodimer with PSMG1, targeting the PSMA5 and PSMA7 subunits to promote the formation of the proteasome alpha ring, a critical step in protein degradation pathways. This chaperone function is vital for protein homeostasis and cellular health.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Proteasome-associated autoinflammatory syndrome 4, characterized by severe autoinflammatory reactions and systemic symptoms, Proteasome assembly chaperone 2 represents a promising target for therapeutic intervention. Exploring the mechanisms by which PAC2 influences this disease could lead to novel treatments for autoinflammatory and autoimmune conditions.

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