AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-(1,6)-fucosyltransferase

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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 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

Q9BYC5

UPID:

FUT8_HUMAN

Alternative names:

Fucosyltransferase 8; GDP-L-Fuc:N-acetyl-beta-D-glucosaminide alpha1,6-fucosyltransferase; GDP-fucose--glycoprotein fucosyltransferase; Glycoprotein 6-alpha-L-fucosyltransferase

Alternative UPACC:

Q9BYC5; B4DFS7; G3V5N0; O00235; Q8IUA5; Q9BYC6; Q9P2U5; Q9P2U6

Background:

Alpha-(1,6)-fucosyltransferase, also known as Fucosyltransferase 8, plays a pivotal role in glycoprotein biosynthesis. It catalyzes the addition of fucose in alpha 1-6 linkage to the first GlcNAc residue on N-glycans. This enzymatic activity is crucial for the proper function and structural integrity of glycoproteins, which are involved in numerous cellular processes.

Therapeutic significance:

The enzyme's dysfunction is linked to Congenital disorder of glycosylation with defective fucosylation 1, characterized by developmental delays, skeletal anomalies, and immunodeficiency. Understanding the role of Alpha-(1,6)-fucosyltransferase could open doors to potential therapeutic strategies for this disorder and related glycosylation abnormalities.

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