Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
Q96DT6

UPID:
ATG4C_HUMAN

ALTERNATIVE NAMES:
AUT-like 3 cysteine endopeptidase; Autophagy-related cysteine endopeptidase 3; Autophagy-related protein 4 homolog C

ALTERNATIVE UPACC:
Q96DT6; A6NLR8; D3DQ58; Q96K04

BACKGROUND:
The protein Cysteine protease ATG4C, with alternative names such as Autophagy-related cysteine endopeptidase 3, is integral to autophagy. It facilitates the activation and delipidation of ATG8 family proteins, crucial for their function in autophagy. ATG4C's ability to expose a C-terminal glycine in ATG8 proteins is vital for their conjugation to PE and membrane insertion. Its delipidation activity, particularly stronger than ATG4B, underscores its unique role in macroautophagy.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Cysteine protease ATG4C could open doors to potential therapeutic strategies.

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