A metabolic exposure-oriented network regulation strategy for the identification of effective combination in the extract of Ginkgo biloba L.

Multimodal integrated strategy for the discovery and identification of quality markers in traditional Chinese medicine

“…In the decoction, 11 ingredients were finally confirmed in bioequivalence with Da-Cheng-Qi decoction and served as Q-markers. Yang and co-workers [ 35 ] used a metabolic exposure-oriented network pharmacology strategy to reveal the effective combination in the Ginkgo biloba extract, where a combination of 12 active compounds was found to be bioequivalent to that of the original herb used in the treatment of ischemic stroke and could act as Q-markers.…”

Ginkgo biloba extract promotes Treg differentiation to ameliorate ischemic stroke via inhibition of HIF‐1α/HK2 pathway

“…Terpene lactones and flavonol glycosides are known as the effective compounds of EGb, which attenuates the neuronal apoptosis induced by oxygen–glucose deprivation/reoxygenation in vitro. We and other groups have, however, demonstrated that the levels of ginkgo compounds in the brain were far lower than the concentrations used in vitro experiment (Chen et al, 2013; X. G. Liu et al, 2018; Ude et al, 2013; Wu et al, 2017). Given that, we considered the central‐peripheral axis in this study when exploring the neuroprotective mechanisms of EGb on ischemic stroke.…”

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review

“…With the attempt to find the effectual-combination ingredients (ECIs) from CHM, a strategy was proposed by Liu et al [64] ; it was defined as metabolic exposure-oriented network regulation for identification of ECIs, including network topology score (NTS) and component exposure score (CES) (see equations [13] , [14] ). NTS represents the topological importance of a compound’s targets in CHM-regulated network, by calculating “Betweenness” (B), “Closeness” (C), “Degree” (D), and “Eigenvector centrality” (E) of all regulated genes through principal component analysis (PCA).…”