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Decoding the mechanism of Qingjie formula in the prevention of COVID-19 based on network pharmacology and molecular docking

Oct 2024  
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Quercetin for COVID-19
24th treatment shown to reduce risk in July 2021
 
*, now with p = 0.0031 from 11 studies.
No treatment is 100% effective. Protocols combine treatments. * >10% efficacy, ≥3 studies.
4,800+ studies for 102 treatments. c19early.org
In Silico study showing potential benefits of quercetin for COVID-19 prevention through network pharmacology and molecular docking. Authors identified quercetin as one of the key active ingredients in Qingjie formula (QJF). Quercetin was found to have the highest frequency of interaction with potential target proteins. The results suggest that quercetin may be beneficial for COVID-19 by inhibiting viral replication, reducing inflammatory responses, and decreasing reactive oxygen species production. Molecular docking results showed quercetin had good binding affinity with hub genes including AKT1, TP53, TNF, IL6, VEGFA, IL1B, and CASP3. These target proteins are involved in host immunity, inflammatory responses, and cellular stress processes. Authors propose that quercetin in QJF may act through multiple pathways including PI3K-Akt signaling, AGE-RAGE signaling, and IL-17 signaling to prevent COVID-19.
65 preclinical studies support the efficacy of quercetin for COVID-19:
In Silico studies predict inhibition of SARS-CoV-2, or minimization of side effects, with quercetin or metabolites via binding to the spikeA,5,6,18,20,21,26,34,35,37,38,56,57, MproB,3,5,7,9,11,13,14,16,19,20,26,30,32-34,38,39,41,57,58, RNA-dependent RNA polymeraseC,5,28, PLproD,33,41, ACE2E,18,19,24,33,37,57, TMPRSS2F,18, helicaseG,25,30, endoribonucleaseH,35, cathepsin LI,22, Wnt-3J,18, FZDK,18, LRP6L,18, ezrinM,36, ADRPN,34, NRP1O,37, EP300P,12, PTGS2Q,19, HSP90AA1R,12,19, matrix metalloproteinase 9S,27, IL-6T,17,31, IL-10U,17, VEGFAV,31, and RELAW,31 proteins. In Vitro studies demonstrate inhibition of the MproB,11,46,53 protein, and inhibition of spike-ACE2 interactionX,42. In Vitro studies demonstrate efficacy in Calu-3Y,45, A549Z,17, HEK293-ACE2+AA,52, Huh-7AB,21, Caco-2AC,44, Vero E6AD,15,38,44, mTECAE,47, and RAW264.7AF,47 cells. Animal studies demonstrate efficacy in K18-hACE2 miceAG,49, db/db miceAH,47,55, BALB/c miceAI,54, and rats59. Quercetin reduced proinflammatory cytokines and protected lung and kidney tissue against LPS-induced damage in mice54 and inhibits LPS-induced cytokine storm by modulating key inflammatory and antioxidant pathways in macrophages2.
Pan et al., 11 Oct 2024, peer-reviewed, 5 authors. Contact: dongyihua@126.com.
In Silico studies are an important part of preclinical research, however results may be very different in vivo.
This PaperQuercetinAll
Decoding the mechanism of Qingjie formula in the prevention of COVID-19 based on network pharmacology and molecular docking
Yu Pan, Wanchun Lin, Yueyue Huang, Jingye Pan, Yihua Dong
Heliyon, doi:10.1016/j.heliyon.2024.e39167
Traditional Chinese medicine (TCM) has played a positive role in preventing and controlling the coronavirus disease 2019 (COVID-19) epidemic. Qingjie formula (QJF) developed to prevent COVID-19 is widely used in Wenzhou, Zhejiang province, China. However, the biological active ingredients of QJF and their specific mechanisms for preventing COVID-19 remain unclear. The study focused on exploring the pharmacological mechanism of QJF for the prevention of COVID-19 based on network pharmacology and molecular docking. The active ingredients of QJF were screened by TCMSP database. Databases such as Genecards and Swiss Target Prediction predicted potential targets of QJF against COVID-19. The "drug-active ingredient-potential target" network was constructed by Cytoscape software. We used STRING database to construct the proteinprotein interaction (PPI) network. Enrichment of biological functions and signaling pathways were analyzed by using the DAVID database and R language. Then AutoDock Vina and Python software were used for molecular docking of hub targets and active ingredients. 147 active ingredients interacted with 316 potential targets of COVID-19. A PPI network consisting of 30 hub genes was constructed, and the top 10 hub genes were ALB, AKT1, TP53, TNF, IL6, VEGFA, IL1B, CASP3, JUN and STAT3. The results of GO analysis showed that these targets were mainly enriched in cell responses to oxidative stress, chemical stress, and other functions. KEGG analysis revealed that viral protein interactions with cytokines (e.g., human cytomegalovirus infection), endocrine resistance pathways (e.g., AGE-RAGE signaling pathway), PI3K-Akt signaling pathway, and lipid and atherosclerosis signaling pathway were the major signaling pathways. Moreover, the core active ingredients of QJF had good binding affinity with hub genes by molecular docking. QJF plays an important role in the prevention of COVID-19 by regulating host immune inflammatory response and oxidative stress response, inhibiting virus, improving immune function, regulating the hypoxia-cytokine storm, and inhibiting cell migration. Introduction Coronavirus disease 2019 (COVID-19) was first discovered in Wuhan, China, and is a highly contagious disease caused by severe
Ethics statement Not applicable. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Abbreviation
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