Focused On-demand Library for Galectin-9

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 use our state-of-the-art dedicated workflow for designing focused libraries for protein-protein interfaces.

 Fig. 1. The sreening workflow of Receptor.AI

This process entails comprehensive molecular simulations of the target protein, individually and in complex with essential partner proteins, along with ensemble virtual screening that focuses on conformational mobility in both its free and complex states. Potential binding pockets are considered at the protein-protein interaction interface and in remote allosteric locations to address every conceivable mechanism of action.

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.







Alternative names:

Ecalectin; Tumor antigen HOM-HD-21

Alternative UPACC:

O00182; A7VJG6; F8W9W4; O14532; O75028; Q3B8N1; Q53FQ0; Q8WYQ7; Q9NQ58


Galectin-9, also known as Ecalectin and Tumor antigen HOM-HD-21, plays a pivotal role in immune regulation and cell signaling. It binds galactosides with high affinity, influencing T-helper cell death, macrophage activation, and regulatory T-cell stability. Its interactions with proteins like HAVCR2, P4HB, and CD44 modulate various immune responses, including cytokine production, cell migration, and apoptosis.

Therapeutic significance:

Understanding the role of Galectin-9 could open doors to potential therapeutic strategies. Its ability to modulate immune responses, suppress T-cell proliferation, and transform NK cell phenotype highlights its potential in treating immune-related disorders and enhancing transplant acceptance.

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