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Yafeng Xue

Researcher at AstraZeneca

Publications -  60
Citations -  2804

Yafeng Xue is an academic researcher from AstraZeneca. The author has contributed to research in topics: Active site & Carbonic anhydrase. The author has an hindex of 30, co-authored 59 publications receiving 2602 citations. Previous affiliations of Yafeng Xue include Griffith University & Umeå University.

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Structural Insights and Biological Effects of Glycogen Synthase Kinase 3-specific Inhibitor AR-A014418

TL;DR: AR-A014418 is the first compound of a family of specific inhibitors of GSK3 that does not significantly inhibit closely related kinases such as cdk2 or cdk5 and may have important applications as a tool to elucidate the role of Gsk3 in cellular signaling and possibly in Alzheimer's disease.
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Exploitation of Structural and Regulatory Diversity in Glutamate Racemases

TL;DR: Three distinct mechanisms of regulation for the family of glutamate racemases are described: allosteric activation by metabolic precursors, kinetic regulation through substrate inhibition, and d-glutamate recycling using a d-amino acid transaminase.
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Inhibition and catalysis of carbonic anhydrase

TL;DR: The zinc enzyme carbonic anhydrase (carbonate hydrolyase) has been intensely investigated since its discovery and the kinetics and inhibition of the enzyme have been extensively studied and repeatedly reviewed.
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Discovery of novel potent and highly selective glycogen synthase kinase-3β (GSK3β) inhibitors for Alzheimer's disease: design, synthesis, and characterization of pyrazines.

TL;DR: This work has developed highly potent and selective inhibitors of GSK3β showing cellular efficacy and blood-brain barrier penetrance that are suitable for in vivo efficacy testing and may serve as a new treatment strategy for Alzheimer's disease.
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Interfering with the inhibitory mechanism of serpins: crystal structure of a complex formed between cleaved plasminogen activator inhibitor type 1 and a reactive-centre loop peptide

TL;DR: The characterisation of the two binding sites for the peptide inhibitor provides a solid foundation for computer-aided design of novel, low molecular weight PAI-1 inhibitors.