Focused On-demand Library for Alpha-galactosidase A

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


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
P06280

UPID:
AGAL_HUMAN

ALTERNATIVE NAMES:
Alpha-D-galactosidase A; Alpha-D-galactoside galactohydrolase; Galactosylgalactosylglucosylceramidase GLA; Melibiase

ALTERNATIVE UPACC:
P06280; Q6LER7

BACKGROUND:
Alpha-galactosidase A, identified by its alternative names such as Alpha-D-galactosidase A and Melibiase, is essential for the hydrolysis and effective degradation of glycosphingolipids within lysosomes. Its role is critical in maintaining cellular and systemic homeostasis by preventing the harmful accumulation of glycolipids.

THERAPEUTIC SIGNIFICANCE:
Mutations affecting Alpha-galactosidase A result in Fabry disease, a condition marked by the buildup of glycosphingolipids leading to severe systemic symptoms and potential mortality from organ failure. The enzyme's direct involvement in this disease highlights its potential as a target for therapeutic intervention, including enzyme replacement and gene therapy, to alleviate or prevent the progression of Fabry disease.

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