Focused On-demand Library for Alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 2

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.


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 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.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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
Q9UJ37

UPID:
SIA7B_HUMAN

ALTERNATIVE NAMES:
GalNAc alpha-2,6-sialyltransferase II; ST6GalNAc II; SThM; Sialyltransferase 7B

ALTERNATIVE UPACC:
Q9UJ37; Q12971

BACKGROUND:
The enzyme Alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 2, known among researchers as ST6GalNAc II, is integral to the process of glycoprotein modification. It facilitates the addition of N-acetylneuraminyl groups to glycan chains, with a specificity for GalNAc residues. This specificity underlines the enzyme's role in determining the structure and function of cell surface glycoproteins.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 2 holds promise for unveiling new therapeutic avenues. Given its critical role in glycoprotein modification, targeting this enzyme could lead to innovative treatments that manipulate cell surface characteristics for therapeutic benefit.

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