Focused On-demand Library for N-acetylgalactosaminyltransferase 7

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


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


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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

PARTNER
Receptor.AI
 
UPACC
Q86SF2

UPID:
GALT7_HUMAN

ALTERNATIVE NAMES:
Polypeptide GalNAc transferase 7; Protein-UDP acetylgalactosaminyltransferase 7; UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase 7

ALTERNATIVE UPACC:
Q86SF2; B3KQU3; Q7Z5W7; Q9UJ28

BACKGROUND:
The enzyme N-acetylgalactosaminyltransferase 7, also referred to as Polypeptide GalNAc transferase 7 or UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase 7, is integral to the process of O-linked oligosaccharide biosynthesis. It is distinguished by its ability to transfer N-acetyl-D-galactosamine to glycosylated peptides, a process that necessitates an initial GalNAc residue on the peptide, setting it apart from other family members.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of N-acetylgalactosaminyltransferase 7 holds the promise of unveiling novel therapeutic avenues.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 7618 of 8789