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Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

BACKGROUND: Aloe vera has long been considered an anticancer herb in different parts of the world. OBJECTIVE: To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. METHODS: The active ingredients and corresponding prote...

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Detalles Bibliográficos
Autores principales: Xie, Jing, Wu, Jun, Yang, Sihui, Zhou, Huaijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654547/
https://www.ncbi.nlm.nih.gov/pubmed/34899953
http://dx.doi.org/10.1155/2021/6077698
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author Xie, Jing
Wu, Jun
Yang, Sihui
Zhou, Huaijun
author_facet Xie, Jing
Wu, Jun
Yang, Sihui
Zhou, Huaijun
author_sort Xie, Jing
collection PubMed
description BACKGROUND: Aloe vera has long been considered an anticancer herb in different parts of the world. OBJECTIVE: To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. METHODS: The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. RESULTS: By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. CONCLUSION: This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.
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spelling pubmed-86545472021-12-09 Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer Xie, Jing Wu, Jun Yang, Sihui Zhou, Huaijun Evid Based Complement Alternat Med Research Article BACKGROUND: Aloe vera has long been considered an anticancer herb in different parts of the world. OBJECTIVE: To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. METHODS: The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. RESULTS: By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. CONCLUSION: This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research. Hindawi 2021-12-01 /pmc/articles/PMC8654547/ /pubmed/34899953 http://dx.doi.org/10.1155/2021/6077698 Text en Copyright © 2021 Jing Xie et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xie, Jing
Wu, Jun
Yang, Sihui
Zhou, Huaijun
Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title_full Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title_fullStr Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title_full_unstemmed Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title_short Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer
title_sort network pharmacology-based study on the mechanism of aloe vera for treating cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654547/
https://www.ncbi.nlm.nih.gov/pubmed/34899953
http://dx.doi.org/10.1155/2021/6077698
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