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 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.


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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q13137

UPID:
CACO2_HUMAN

ALTERNATIVE NAMES:
Antigen nuclear dot 52 kDa protein; Nuclear domain 10 protein NDP52; Nuclear dot protein 52

ALTERNATIVE UPACC:
Q13137; B2RBT0; B4DDC4; B4DDT4; B4DP36; B4E0C0; E7ENK0; E7ETP5; E9PBE5; Q53FQ5; Q53HB5; Q6IBN9; Q9BTF7

BACKGROUND:
The protein Calcium-binding and coiled-coil domain-containing protein 2, known alternatively as Antigen nuclear dot 52 kDa protein, is essential for xenophagy, targeting LGALS8-associated bacteria for autophagy. It ensures the degradation of pathogens by regulating the maturation of pathogen-containing autophagosomes through interactions with specific MAP1LC3 and GABARAPL2 proteins. This protein's role extends to possibly regulating ruffle formation and actin organization, alongside a negative regulation of constitutive secretion.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Calcium-binding and coiled-coil domain-containing protein 2 unveils potential pathways for therapeutic intervention.

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