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. 2022 Jan 1;19(2):213-224.
doi: 10.7150/ijms.67116. eCollection 2022.

Potential mechanism of action of Jing Fang Bai Du San in the treatment of COVID-19 using docking and network pharmacology

Affiliations

Potential mechanism of action of Jing Fang Bai Du San in the treatment of COVID-19 using docking and network pharmacology

Jiaojiao Li et al. Int J Med Sci. .

Abstract

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severely infects people and has rapidly spread worldwide. JingFangBaiDu San (JFBDS) has been used to treat prevalent epidemic pathogens, common cold, headache, cough due to lung-cold, and other symptoms; however, its treatment for COVID-19 is unknown. Molecular docking and network pharmacology were applied to obtain ingredient-protein structures and the herb-ingredient-disease target network model, respectively, to explore the potential mechanism of JFBDS in COVID-19 treatment. Network pharmacology analysis showed that acacetin, wogonin, and isorhamnetin were the main active ingredients of JFBDS, and EGFR, PIK3CA, LCK, MAPK1, MAPK3, MAPK8, STAT3, TNF, IL2, and RELA were speculated to be crucial therapeutic targets. Moreover, the Toll-like receptors, HIF-1, PIK3K/AKT, MAPK, NF-κB and NOD-like receptor signaling pathways were important for JFBDS in COVID-19 treatment. Molecular docking analysis indicated that ingredients of JFBDS could bind to angiotensin converting enzyme II, spike protein, and chymotrypsin like protease (3CLpro), which inhibits virus entry and replication in host cells. This study provides a new perspective for understanding potential therapeutic effects and mechanisms of JFBDS in COVID-19 and may facilitate its clinical application.

Keywords: COVID-19; JingFangBaiDu San; molecular docking; network pharmacology.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
The experiment design of JFBDS on COVID-19 by network pharmacology and molecular docking
Figure 2
Figure 2
The PPI network of ingredient-disease-targets (A). The interaction network of herb-ingredient-disease targets (B). Among this, red color nodes represented ingredient-disease-targets; light blue nodes represented Bupleurum chinense DC. (Chaihu), dark bule nodes represented Citrus aurantium L. (Zhiqiao), light purple nodes represented Ligusticum chuanxiong Hort. (Chuanxiong), dark purple nodes represented Notopterygium inchum Ting ex H.T. Chang (Qianghuo), light pink nodes represented Saposhnikovia divaricata (Turcz.) Schischk. (Fangfeng), dark pink nodes represented Angelica pubescens Maxim.f.biserrata Shan et Yuan (Duhuo), light yellow nodes represented Poria cocos (Schw.) Wolf (Fuling), dark yellow nodes represented Peucedanum praeruptorum Dunn (Qianhu), light green nodes represented Glycyrrhiza uralensis Fisch. (Gancao), dark green nodes represented Platycodon grandiflorum (Jacq.) A. DC. (Jiegeng) and bright green nodes represented Schizonepeta tenuifolia Briq. (Jingjie).
Figure 3
Figure 3
GO and KEGG functional annotation analysis of ingredient-disease-targets in JFBDS for treating COVID-19. GO enrichment of putative targets was divided into biological process (A), molecular function (B) and cellular component (C). The pathway of putative targets was predicted by KEGG enrichment (D).
Figure 4
Figure 4
Molecular docking of 18α-hydroxy glycyrrhetic acid bound with ACE2 (A). Molecular docking of Glyuranolide bound with 3CLpro and S1(B, C).
Figure 5
Figure 5
The ingredients, targets and signalling pathway of JFBDS on COVID-19.

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