AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for N-acetylgalactosaminyltransferase 7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 our partner Reaxense.

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 sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

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:

N-acetylgalactosaminyltransferase 7, known alternatively as Polypeptide GalNAc transferase 7, Protein-UDP acetylgalactosaminyltransferase 7, or UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase 7, plays a crucial role in O-linked oligosaccharide biosynthesis. This enzyme uniquely catalyzes the addition of N-acetyl-D-galactosamine residues to glycosylated peptides, requiring a pre-existing GalNAc on a peptide for further GalNAc additions, unlike its family counterparts.

Therapeutic significance:

Understanding the role of N-acetylgalactosaminyltransferase 7 could open doors to potential therapeutic strategies.

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