Harnessing natural-product-inspired combinatorial chemistry and computation-guided synthesis to develop N -glycan modulators as anticancer agents.
Wei-An ChenYu-Hsin ChenChiao-Yun HsiehPi-Fang HungChiao-Wen ChenChien-Hung ChenJung-Lee LinTing-Jen R ChengTsui-Ling HsuYing-Ta WuChia-Ning ShenWei-Chieh ChengPublished in: Chemical science (2022)
Modulation of N -glycosylation using human Golgi α-mannosidase II (α-hGMII) inhibitors is a potential anticancer approach, but the clinical utility of current α-hGMII inhibitors is limited by their co-inhibition of human lysosomal α-mannosidase (α-hLM), resulting in abnormal storage of oligomannoses. We describe the synthesis and screening of a small library of novel bicyclic iminosugar-based scaffolds, prepared via natural product-inspired combinatorial chemistry (NPICC), which resulted in the identification of a primary α-hGMII inhibitor with 13.5-fold selectivity over α-hLM. Derivatization of this primary inhibitor using computation-guided synthesis (CGS) yielded an advanced α-hGMII inhibitor with nanomolar potency and 106-fold selectivity over α-hLM. In vitro studies demonstrated its N -glycan modulation and inhibitory effect on hepatocellular carcinoma (HCC) cells. In vivo studies confirmed its encouraging anti-HCC activity, without evidence of oligomannose accumulation.
Keyphrases
- endothelial cells
- induced apoptosis
- induced pluripotent stem cells
- pluripotent stem cells
- small molecule
- liquid chromatography tandem mass spectrometry
- risk assessment
- cell cycle arrest
- oxidative stress
- machine learning
- climate change
- simultaneous determination
- cell surface
- signaling pathway
- mass spectrometry
- cell proliferation
- cell death
- human health
- structural basis