Integrated Chemical Interpretation and Network Pharmacology Analysis to Reveal the Anti-Liver Fibrosis Effect of Penthorum chinense - Du, Zenan; Huang, Doudou; Shi, Pengjie; Dong, Zhiying; Wang, Xiujuan; Li, Mengshuang; Chen, Wansheng; Zhang, Feng; Sun, Lianna (Frontiers in Pharmacology, 2022)
Network pharmacology can effectively predict the target of drugs, which is benefit to clarify the mechanism of action of traditional Chinese medicine (TCM) by constructing compound-target associations. Therefore, a detailed description of the components of TCM will help to more accurately clarify its mechanism of action. As we all known, LC-MS method can quickly demonstrate the chemicals of TCM, in which ms2 plays an important role in the derivation of the structure. In the current study, we developed a highly efficient method, called DDA-assisted DIA, which can both broaden mass spectrometry coverage and ms2 quality. In DDA-assisted DIA, data dependent acquisition (DDA) and data independent acquisition (DIA) was merged to construct molecular network, in which 1094 mass features were retained in Penthorum chinense Pursh (P. chinense). In which, 169 compounds were identified based on both ms1 and ms2 analysis. After that, based on a network pharmacology study, 94 bioactive compounds and 440 targets of the P. chinense associated with liver fibrosis were obtained, forming a tight compound-target network. Meanwhile, the network pharmacology experimental results showed that multiple pathways were interacted with HIF-1 pathway, which was first identified involved in P. chinese. It could be observed that some proteins, such as TNF-α, TIMP-1, and HO-1, were involved in the HIF-1 pathway. Furthermore, the pharmacological effects of P. chinense on these proteins were verified by CCl4 induced rat liver fibrosis, and P. chinense were found to improve liver function through regulating TNF-α, TIMP-1, and HO-1 expressions. In summary, DDA-assisted DIA could provide more detailed compound information, which will help us to annotate the ingredients of TCM, combined with computerized network pharmacology provided a theoretical basis for revealing the mechanism of P. chinense.