Network pharmacology and molecular docking-based investigations of Kochiae Fructus's active phytomolecules, molecular targets, and pathways in treating COVID-19

被引:13
|
作者
Khan, Shakeel Ahmad [1 ]
Lee, Terence Kin Wah [1 ,2 ]
机构
[1] Hong Kong Polytech Univ, Dept Appl Biol & Chem Technol, Kowloon, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, State Key Lab Chem Biol & Drug Discovery, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Kochiae Fructus; COVID-19; network pharmacology; molecular docking; molecular pathways; CYTOKINE STORM; BIOINFORMATICS; INHIBITION;
D O I
10.3389/fmicb.2022.972576
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
COVID-19 disease is caused by SARS-CoV-2. Hyper-inflammation mediated by proinflammatory cytokines is humans' primary etiology of SARS-CoV2 infection. Kochiae Fructus is widely used in China as traditional Chinese medicine (TCM) to treat inflammatory diseases. Due to its anti-inflammatory properties, we hypothesized that Kochiae Fructus would be a promising therapeutic agent for COVID-19. The active phytomolecules, targets, and molecular pathways of Kochiae Fructus in treating COVID-19 have not been explored yet. Network pharmacology analysis was performed to determine the active phytomolecules, molecular targets, and pathways of Kochiae Fructus. The phytomolecules in Kochiae Fructus were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and their potential targets were predicted with the SwissTargetPrediction webserver. COVID-19-related targets were recovered from the GeneCards database. Intersecting targets were determined with the VENNY tool. The Protein-protein interaction (PPI) and Molecular Complex Detection (MCODE) network analyses were constructed using the Cytoscape software. Using the DAVID tool, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the intersecting targets. AutoDock Vina (version 1.2.0.) was used for molecular docking analysis. Six active phytomolecules and 165 their potential targets, 1,745 COVID-19-related targets, and 34 intersecting targets were identified. Network analysis determined 13 anti-COVID-19 core targets and three key active phytomolecules (Oleanolic acid, 9E,12Z-octadecadienoic acid, and 11,14-eicosadienoic acid). Three key pathways (pathways in cancer, the TNF signaling pathway, and lipid and atherosclerosis) and the top six antiCOVID-19 core targets (IL-6, PPARG, MAPK3, PTGS2, ICAM1, and MAPK1) were determined to be involved in the treatment of COVID-19 with active phytomolecules of Kochiae Fructus. Molecular docking analysis revealed that three key active phytomolecules of Kochiae Fructus had a regulatory effect on the identified anti-COVID-19 core targets. Hence, these findings offer a foundation for developing anti-COVID-19 drugs based on phytomolecules of Kochiae Fructus.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Network pharmacology and molecular docking-based prediction of active compounds and mechanisms of action of Cnidii Fructus in treating atopic dermatitis
    Shakeel Ahmad Khan
    Ying Wu
    Amy Sze-Man Li
    Xiu-Qiong Fu
    Zhi-Ling Yu
    BMC Complementary Medicine and Therapies, 22
  • [2] Network pharmacology and molecular docking-based prediction of active compounds and mechanisms of action of Cnidii Fructus in treating atopic dermatitis
    Khan, Shakeel Ahmad
    Wu, Ying
    Li, Amy Sze-Man
    Fu, Xiu-Qiong
    Yu, Zhi-Ling
    BMC COMPLEMENTARY MEDICINE AND THERAPIES, 2022, 22 (01)
  • [3] Network Pharmacology and Reverse Molecular Docking-Based Prediction of the Molecular Targets and Pathways for Avicularin Against Cancer
    Duan, Chaohui
    Li, Yang
    Dong, Xiaorui
    Xu, Weibin
    Ma, Yingli
    COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2019, 22 (01) : 4 - 12
  • [4] Network Pharmacology and Molecular Docking-Based Prediction of the Molecular Targets and Signaling Pathways of Ginseng in the Treatment of Parkinson's Disease
    Zhang, Wei
    Chen, Jingya
    Liu, Hongquan
    NATURAL PRODUCT COMMUNICATIONS, 2022, 17 (05)
  • [5] Analysis of mechanisms of Shenhuang Granule in treating severe COVID-19 based on network pharmacology and molecular docking
    Xiang-ru Xu
    Wen Zhang
    Xin-xin Wu
    Hong-qiang Yang
    Yu-ting Sun
    Yu-ting Pu
    Bei Wang
    Wei Peng
    Li-hua Sun
    Quan Guo
    Shuang Zhou
    Bang-jiang Fang
    Journal of Integrative Medicine, 2022, 20 (06) : 561 - 574
  • [6] Analysis of mechanisms of Shenhuang Granule in treating severe COVID-19 based on network pharmacology and molecular docking
    Xu, Xiang-ru
    Zhang, Wen
    Wu, Xin-xin
    Yang, Hong-qiang
    Sun, Yu-ting
    Pu, Yu-ting
    Wang, Bei
    Peng, Wei
    Sun, Li-hua
    Guo, Quan
    Zhou, Shuang
    Fang, Bang-jiang
    JOURNAL OF INTEGRATIVE MEDICINE-JIM, 2022, 20 (06): : 561 - 574
  • [7] Network Pharmacology, Molecular Docking and Molecular Dynamics Simulation Studies of the Molecular Targets and Mechanisms of ChuanKeZhi in the Treatment of COVID-19
    Yuan, Jiaying
    Zhu, Yiqing
    Zhao, Jiayi
    Li, Li
    Zhu, Chengjie
    Chen, Mingxia
    Zhang, Yi
    Shang, Yan
    NATURAL PRODUCT COMMUNICATIONS, 2022, 17 (08)
  • [8] Predicting the Molecular Mechanism of Shenling Baizhu San in Treating Convalescent Patients With COVID-19 Based on Network Pharmacology and Molecular Docking
    Zhang, Ying
    Lu, Li
    Liu, YiWen
    Yang, AiXia
    Yang, Yanfang
    NATURAL PRODUCT COMMUNICATIONS, 2021, 16 (10)
  • [9] Investigations of nitazoxanide molecular targets and pathways for the treatment of hepatocellular carcinoma using network pharmacology and molecular docking
    Khan, Shakeel Ahmad
    Lee, Terence Kin Wah
    FRONTIERS IN PHARMACOLOGY, 2022, 13
  • [10] Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Huashi Baidu formula in the treatment of COVID-19
    Tao, Quyuan
    Du, Jiaxin
    Li, Xiantao
    Zeng, Jingyan
    Tan, Bo
    Xu, Jianhua
    Lin, Wenjia
    Chen, Xin-lin
    DRUG DEVELOPMENT AND INDUSTRIAL PHARMACY, 2020, 46 (08) : 1345 - 1353