Identifying Active Compounds and Mechanism of Camellia nitidissima Chi on Anti-Colon Cancer by Network Pharmacology and Experimental Validation
Camellia nitidissima Chi (CNC) is a traditional Chinese medicine (TCM) with anticancer property. However, its underlying mechanisms of anti-colon cancer (CC) remain unknown. Therefore, a systematic approach is proposed in the present study to elucidate the anticancer mechanisms of CNC based on netwo...
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| Veröffentlicht in: | Evidence-based complementary and alternative medicine 2021-08, Vol.2021, p.1-15 |
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| creator | Chen, Yiwei Hao, Erwei Zhang, Fan Du, Zhengcai Xie, Jinling Chen, Feng Yu, Chunlin Hou, Xiaotao Deng, Jiagang |
| description | Camellia nitidissima Chi (CNC) is a traditional Chinese medicine (TCM) with anticancer property. However, its underlying mechanisms of anti-colon cancer (CC) remain unknown. Therefore, a systematic approach is proposed in the present study to elucidate the anticancer mechanisms of CNC based on network pharmacology and experimental validation. Initially, the potential active ingredients of CNC were verified via the TCMSP database based on the oral bioavailability (OB) and drug-likeness (DL) terms. Hub targets of CNC were acquired from SwissTarget prediction and TCMSP databases, and target genes related to CC were gathered from GeneCards and OMIM databases. Cytoscape was used to establish the compound-target networks. Next, the hub target genes collected from the CNC and CC were parsed via GO and KEGG analysis. Results of GO and KEGG analysis reveal that quercetin and luteolin in CNC, VEGFA and AKT1 targets, and PI3K-Akt pathway were associated with the suppression of CC. Besides, the result of molecular docking unveils that VEGFA demonstrates the most powerful binding affinity among the binding outcomes. This finding was successfully validated using in vitro HCT116 cell model experiment. In conclusion, this study proved the usefulness of integrating network pharmacology with in vitro experiments in the elucidation of underlying molecular mechanisms of TCM. |
| doi_str_mv | 10.1155/2021/7169211 |
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However, its underlying mechanisms of anti-colon cancer (CC) remain unknown. Therefore, a systematic approach is proposed in the present study to elucidate the anticancer mechanisms of CNC based on network pharmacology and experimental validation. Initially, the potential active ingredients of CNC were verified via the TCMSP database based on the oral bioavailability (OB) and drug-likeness (DL) terms. Hub targets of CNC were acquired from SwissTarget prediction and TCMSP databases, and target genes related to CC were gathered from GeneCards and OMIM databases. Cytoscape was used to establish the compound-target networks. Next, the hub target genes collected from the CNC and CC were parsed via GO and KEGG analysis. Results of GO and KEGG analysis reveal that quercetin and luteolin in CNC, VEGFA and AKT1 targets, and PI3K-Akt pathway were associated with the suppression of CC. Besides, the result of molecular docking unveils that VEGFA demonstrates the most powerful binding affinity among the binding outcomes. This finding was successfully validated using in vitro HCT116 cell model experiment. In conclusion, this study proved the usefulness of integrating network pharmacology with in vitro experiments in the elucidation of underlying molecular mechanisms of TCM.</description><identifier>ISSN: 1741-427X</identifier><identifier>EISSN: 1741-4288</identifier><identifier>DOI: 10.1155/2021/7169211</identifier><identifier>PMID: 34484402</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>1-Phosphatidylinositol 3-kinase ; AKT protein ; AKT1 protein ; Bioavailability ; Bioinformatics ; Camellia ; Cancer therapies ; Chinese medicine ; Colon cancer ; Colorectal cancer ; Exports ; Genomes ; Ligands ; Molecular modelling ; Pharmacology ; Proteins ; Quercetin ; Software ; Traditional Chinese medicine</subject><ispartof>Evidence-based complementary and alternative medicine, 2021-08, Vol.2021, p.1-15</ispartof><rights>Copyright © 2021 Yiwei Chen et al.</rights><rights>Copyright © 2021 Yiwei Chen et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Yiwei Chen et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c425t-9a2c1eda96ce356579e1fe9ccee0134692508f0cfe5380fbc26259f22629e0a33</citedby><cites>FETCH-LOGICAL-c425t-9a2c1eda96ce356579e1fe9ccee0134692508f0cfe5380fbc26259f22629e0a33</cites><orcidid>0000-0001-7230-7077 ; 0000-0002-7430-7473 ; 0000-0001-8399-3420 ; 0000-0002-9239-3336 ; 0000-0003-2079-981X ; 0000-0001-7394-6022 ; 0000-0001-5685-5962 ; 0000-0002-1097-3805 ; 0000-0001-8251-220X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413042/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413042/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,27905,27906,53772,53774</link.rule.ids></links><search><contributor>Chen, Jianping</contributor><contributor>Jianping Chen</contributor><creatorcontrib>Chen, Yiwei</creatorcontrib><creatorcontrib>Hao, Erwei</creatorcontrib><creatorcontrib>Zhang, Fan</creatorcontrib><creatorcontrib>Du, Zhengcai</creatorcontrib><creatorcontrib>Xie, Jinling</creatorcontrib><creatorcontrib>Chen, Feng</creatorcontrib><creatorcontrib>Yu, Chunlin</creatorcontrib><creatorcontrib>Hou, Xiaotao</creatorcontrib><creatorcontrib>Deng, Jiagang</creatorcontrib><title>Identifying Active Compounds and Mechanism of Camellia nitidissima Chi on Anti-Colon Cancer by Network Pharmacology and Experimental Validation</title><title>Evidence-based complementary and alternative medicine</title><description>Camellia nitidissima Chi (CNC) is a traditional Chinese medicine (TCM) with anticancer property. However, its underlying mechanisms of anti-colon cancer (CC) remain unknown. Therefore, a systematic approach is proposed in the present study to elucidate the anticancer mechanisms of CNC based on network pharmacology and experimental validation. Initially, the potential active ingredients of CNC were verified via the TCMSP database based on the oral bioavailability (OB) and drug-likeness (DL) terms. Hub targets of CNC were acquired from SwissTarget prediction and TCMSP databases, and target genes related to CC were gathered from GeneCards and OMIM databases. Cytoscape was used to establish the compound-target networks. Next, the hub target genes collected from the CNC and CC were parsed via GO and KEGG analysis. Results of GO and KEGG analysis reveal that quercetin and luteolin in CNC, VEGFA and AKT1 targets, and PI3K-Akt pathway were associated with the suppression of CC. Besides, the result of molecular docking unveils that VEGFA demonstrates the most powerful binding affinity among the binding outcomes. This finding was successfully validated using in vitro HCT116 cell model experiment. 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However, its underlying mechanisms of anti-colon cancer (CC) remain unknown. Therefore, a systematic approach is proposed in the present study to elucidate the anticancer mechanisms of CNC based on network pharmacology and experimental validation. Initially, the potential active ingredients of CNC were verified via the TCMSP database based on the oral bioavailability (OB) and drug-likeness (DL) terms. Hub targets of CNC were acquired from SwissTarget prediction and TCMSP databases, and target genes related to CC were gathered from GeneCards and OMIM databases. Cytoscape was used to establish the compound-target networks. Next, the hub target genes collected from the CNC and CC were parsed via GO and KEGG analysis. Results of GO and KEGG analysis reveal that quercetin and luteolin in CNC, VEGFA and AKT1 targets, and PI3K-Akt pathway were associated with the suppression of CC. Besides, the result of molecular docking unveils that VEGFA demonstrates the most powerful binding affinity among the binding outcomes. This finding was successfully validated using in vitro HCT116 cell model experiment. In conclusion, this study proved the usefulness of integrating network pharmacology with in vitro experiments in the elucidation of underlying molecular mechanisms of TCM.</abstract><cop>New York</cop><pub>Hindawi</pub><pmid>34484402</pmid><doi>10.1155/2021/7169211</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-7230-7077</orcidid><orcidid>https://orcid.org/0000-0002-7430-7473</orcidid><orcidid>https://orcid.org/0000-0001-8399-3420</orcidid><orcidid>https://orcid.org/0000-0002-9239-3336</orcidid><orcidid>https://orcid.org/0000-0003-2079-981X</orcidid><orcidid>https://orcid.org/0000-0001-7394-6022</orcidid><orcidid>https://orcid.org/0000-0001-5685-5962</orcidid><orcidid>https://orcid.org/0000-0002-1097-3805</orcidid><orcidid>https://orcid.org/0000-0001-8251-220X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 1-Phosphatidylinositol 3-kinase AKT protein AKT1 protein Bioavailability Bioinformatics Camellia Cancer therapies Chinese medicine Colon cancer Colorectal cancer Exports Genomes Ligands Molecular modelling Pharmacology Proteins Quercetin Software Traditional Chinese medicine |
| title | Identifying Active Compounds and Mechanism of Camellia nitidissima Chi on Anti-Colon Cancer by Network Pharmacology and Experimental Validation |
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