Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
Q7L5D6

UPID:
GET4_HUMAN

ALTERNATIVE NAMES:
Conserved edge-expressed protein; Transmembrane domain recognition complex 35 kDa subunit

ALTERNATIVE UPACC:
Q7L5D6; A4D2Q1; B3KNC7; Q9UFC9; Q9Y309

BACKGROUND:
The Golgi to ER traffic protein 4 homolog, integral to the BAG6/BAT3 complex, is essential for managing misfolded and hydrophobic proteins. It ensures these proteins are either correctly delivered to the endoplasmic reticulum or directed to the proteasome for degradation. Its role extends to the delivery of tail-anchored proteins and the endoplasmic reticulum-associated degradation pathway, highlighting its significance in cellular protein quality control.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Golgi to ER traffic protein 4 homolog could open doors to potential therapeutic strategies, especially in the context of congenital disorders of glycosylation, where its dysfunction is implicated.

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