AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-1,6-mannosyl-glycoprotein 2-beta-N-acetylglucosaminyltransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q10469

UPID:

MGAT2_HUMAN

Alternative names:

Beta-1,2-N-acetylglucosaminyltransferase II; GlcNAc-T II; Mannoside acetylglucosaminyltransferase 2; N-glycosyl-oligosaccharide-glycoprotein N-acetylglucosaminyltransferase II

Alternative UPACC:

Q10469; B3KPC5; B3KQM0

Background:

Alpha-1,6-mannosyl-glycoprotein 2-beta-N-acetylglucosaminyltransferase, also known as Beta-1,2-N-acetylglucosaminyltransferase II, plays a pivotal role in protein N-glycosylation. It catalyzes the addition of N-acetylglucosamine onto the terminal mannose in nascent N-linked glycan chains, crucial for complex glycan formation.

Therapeutic significance:

This enzyme's malfunction is linked to Congenital disorder of glycosylation 2A, a multisystem disorder affecting embryonic development and cell function maintenance. Understanding its role could lead to novel therapeutic strategies for managing this disorder and potentially other glycosylation-related diseases.

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