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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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.


Our top-notch dedicated system is used to design specialised 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
O60260

UPID:
PRKN_HUMAN

ALTERNATIVE NAMES:
Parkin RBR E3 ubiquitin-protein ligase; Parkinson juvenile disease protein 2

ALTERNATIVE UPACC:
O60260; A3FG77; A8K975; D3JZW7; D3K2X0; Q5TFV8; Q5VVX4; Q6Q2I6; Q8NI41; Q8NI43; Q8NI44; Q8WW07

BACKGROUND:
The protein E3 ubiquitin-protein ligase parkin, with alternative names Parkin RBR E3 ubiquitin-protein ligase and Parkinson juvenile disease protein 2, is central to cellular mechanisms for protein quality control. By mediating various types of ubiquitination, it targets misfolded or damaged proteins for degradation, playing a key role in protecting against mitochondrial dysfunction and promoting autophagy.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in the pathogenesis of Parkinson disease and Parkinson disease 2, E3 ubiquitin-protein ligase parkin represents a promising therapeutic target. The protein's ability to modulate mitochondrial quality control and autophagy pathways offers a novel avenue for the development of treatments aimed at neurodegenerative diseases, underscoring the therapeutic significance of further research into its mechanisms.

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