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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Current Computer-Aided Drug Design</journal-id><journal-title-group><journal-title xml:lang="en">Current Computer-Aided Drug Design</journal-title><trans-title-group xml:lang="ru"><trans-title>Current Computer-Aided Drug Design</trans-title></trans-title-group></journal-title-group><issn publication-format="print">1573-4099</issn><issn publication-format="electronic">1875-6697</issn><publisher><publisher-name xml:lang="en">Bentham Science</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">644557</article-id><article-id pub-id-type="doi">10.2174/0115734099272592231004170422</article-id><article-categories><subj-group subj-group-type="toc-heading"><subject>Chemistry</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Exploring the Molecular Mechanism of Niuxi-Mugua Formula in Treating Coronavirus Disease 2019 via Network Pharmacology, Computational Biology, and Surface Plasmon Resonance Verification</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Wang</surname><given-names>Wei</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Cao</surname><given-names>Xu</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Cao</surname><given-names>Yi-nan</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name><surname>Liu</surname><given-names>Lian-lian</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff3"/></contrib><contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Shu-ling</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff4"/></contrib><contrib contrib-type="author"><name><surname>Qi</surname><given-names>Wen-ying</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Jia-xin</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Yang</surname><given-names>Xian-zhao</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Li</surname><given-names>Xiao-ke</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Zao</surname><given-names>Xiao-bin</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff5"/></contrib><contrib contrib-type="author"><name><surname>Ye</surname><given-names>Yong-an</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff id="aff1"><institution>Gastroenterology Department, Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine</institution></aff><aff id="aff2"><institution>Sun Simiao Hospital, Beijing University of Chinese Medicine</institution></aff><aff id="aff3"><institution>Third School of Clinical Medicine, Beijing University of Chinese Medicine</institution></aff><aff id="aff4"><institution>Chinese pharmacy, Sun Simiao Hospital, Beijing University of Chinese Medicine, Tongchuan 727031, China</institution></aff><aff id="aff5"><institution>Dongzhimen Hospital,, Beijing University of Chinese Medicine</institution></aff><pub-date date-type="pub" iso-8601-date="2024-07-01" publication-format="electronic"><day>01</day><month>07</month><year>2024</year></pub-date><volume>20</volume><issue>7</issue><issue-title xml:lang="ru"/><fpage>1113</fpage><lpage>1129</lpage><history><date date-type="received" iso-8601-date="2025-01-07"><day>07</day><month>01</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Bentham Science Publishers</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Bentham Science Publishers</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/></permissions><self-uri xlink:href="https://rjeid.com/1573-4099/article/view/644557">https://rjeid.com/1573-4099/article/view/644557</self-uri><abstract xml:lang="en"><p id="idm46041443651488">Background:In China, Niuxi-Mugua formula (NMF) has been widely used to prevent and treat coronavirus disease 2019 (COVID-19). However, the mechanism of NMF for treating COVID-19 is not yet fully understood.</p><p id="idm46041443655488">Objective:This study aimed to explore the potential mechanism of NMF for treating COVID- 19 by network pharmacology, computational biology, and surface plasmon resonance (SPR) verification.</p><p id="idm46041443659456">Materials and Methods:The NMF-compound-target network was constructed to screen the key compounds, and the Molecular Complex Detection (MCODE) tool was used to screen the preliminary key genes. The overlapped genes (OGEs) and the preliminary key genes were further analyzed by enrichment analysis. Then, the correlation analysis of immune signatures and the preliminary key genes was performed. Molecular docking and molecular dynamic (MD) simulation assays were applied to clarify the interactions between key compounds and key genes. Moreover, the SPR interaction experiment was used for further affinity kinetic verification.</p><p id="idm46041443664512">Results:Lipid and atherosclerosis, TNF, IL-17, and NF-kappa B signaling pathways were the main pathways of NMF in the treatment of COVID-19. There was a positive correlation between almost the majority of immune signatures and all preliminary key genes. The key compounds and the key genes were screened out, and they were involved in the main pathways of NMF for treating COVID-19. Moreover, the binding affinities of most key compounds binding to key genes were good, and IL1B-Quercetin had the best binding stability. SPR analysis further demonstrated that IL1B-Quercetin showed good binding affinity.</p><p id="idm46041443673888">Conclusion:Our findings provided theoretical grounds for NMF in the treatment of COVID- 19.</p></abstract><kwd-group xml:lang="en"><kwd>Coronavirus disease 2019</kwd><kwd>Niuxi-Mugua formula</kwd><kwd>network pharmacology</kwd><kwd>computational biology</kwd><kwd>molecular docking</kwd><kwd>molecular dynamic simulation</kwd><kwd>surface plasmon resonance.</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Tsai, T.I.; Khalili, J.S.; Gilchrist, M.; Waight, A.B.; Cohen, D.; Zhuo, S.; Zhang, Y.; Ding, M.; Zhu, H.; Mak, A.N.S.; Zhu, Y.; Goulet, D.R. ACE2-Fc fusion protein overcomes viral escape by potently neutralizing SARS-CoV-2 variants of concern. 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