Harnessing natural-product-inspired combinatorial chemistry and computation-guided synthesis to develop N-glycan modulators as anticancer agents
- PMID: 35733906
- PMCID: PMC9159088
- DOI: 10.1039/d1sc05894k
Harnessing natural-product-inspired combinatorial chemistry and computation-guided synthesis to develop N-glycan modulators as anticancer agents
Abstract
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.
This journal is © The Royal Society of Chemistry.
Conflict of interest statement
There are no conflicts to declare.
Figures
References
LinkOut - more resources
Full Text Sources
Other Literature Sources
