文献类型：期刊文献

英文题名：Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking

作者：Han, Lin[1];Wei, Xiu-Xiu[2];Zheng, Yu-Jiao[2];Zhang, Li-Li[1];Wang, Xin-Miao[1];Yang, Hao-Yu[2];Ma, Xu[3];Zhao, Lin-Hua[1];Tong, Xiao-Lin[1]

第一作者：Han, Lin

通信作者：Zhao, LH[1];Tong, XL[1]

机构：[1]China Acad Chinese Med Sci, Guanganmen Hosp, Beijing 100053, Peoples R China;[2]Beijing Univ Chinese Med, Beijing 100029, Peoples R China;[3]Gansu Univ Chinese Med, Lanzhou 730000, Peoples R China

第一机构：China Acad Chinese Med Sci, Guanganmen Hosp, Beijing 100053, Peoples R China

通信机构：[1]corresponding author), China Acad Chinese Med Sci, Guanganmen Hosp, Beijing 100053, Peoples R China.

年份：2020

卷号：15

期号：1

外文期刊名：CHINESE MEDICINE

收录：;Scopus(收录号：2-s2.0-85089745541);WOS:【SCI-EXPANDED(收录号:WOS:000557462300001)】；

基金：This work was funded by the Special Project for Emergency of the Ministry of Science and Technology (2020YFC0845000).

语种：英文

外文关键词：COVID-19; Cold-Damp Plague Formula (CDPF); Network pharmacology; Molecular mechanism; Molecular docking

摘要：Background Coronavirus disease 2019 (COVID-19) is a new global public health emergency. The therapeutic benefits of Cold-Damp Plague Formula (CDPF) against COVID-19, which was used to treat "cold-dampness stagnation in the lung" in Trial Versions 6 and 7 of the "Diagnosis and Treatment Protocol for COVID-19", have been demonstrated, but the effective components and their mechanism of action remain unclear. Methods In this study, a network pharmacology approach was employed, including drug-likeness evaluation, oral bioavailability prediction, protein-protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and virtual docking, to predict the bioactive components, potential targets, and molecular mechanism of CDPF for COVID-19 treatment. Results The active compound of herbs in CDPF and their candidate targets were obtained through database mining, and an herbs-ingredients-targets network was constructed. Subsequently, the candidate targets of the active compounds were compared to those relevant to COVID-19, to identify the potential targets of CDPF for COVID-19 treatment. Subsequently, the PPI network was constructed, which provided a basis for cluster analysis and hub gene screening. The seed targets in the most significant module were selected for further functional annotation. GO enrichment analysis identified four main areas: (1) cellular responses to external stimuli, (2) regulation of blood production and circulation, (3) free radical regulation, (4) immune regulation and anti-inflammatory effects. KEGG pathway analysis also revealed that CDPF could play pharmacological roles against COVID-19 through "multi components-multi targets-multi pathways" at the molecular level, mainly involving anti-viral, immune-regulatory, and anti-inflammatory pathways; consequently, a "CDPF-herbs-ingredients-targets-pathways-COVID-19" network was constructed. In hub target analysis, the top hub target IL6, and ACE2, the receptor via which SARS-CoV-2 typically enters host cells, were selected for molecular docking analyses, and revealed good binding activities. Conclusions This study revealed the active ingredients and potential molecular mechanism by which CDPF treatment is effective against COVID-19, and provides a reference basis for the wider application and further mechanistic investigations of CDPF in the fight against COVID-19.