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Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

BACKGROUND: Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. Howe...

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Autores principales: Wang, Biting, Wu, Zengrui, Wang, Jiye, Li, Weihua, Liu, Guixia, Zhang, Bo, Tang, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590697/
https://www.ncbi.nlm.nih.gov/pubmed/33109189
http://dx.doi.org/10.1186/s12906-020-03106-z
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author Wang, Biting
Wu, Zengrui
Wang, Jiye
Li, Weihua
Liu, Guixia
Zhang, Bo
Tang, Yun
author_facet Wang, Biting
Wu, Zengrui
Wang, Jiye
Li, Weihua
Liu, Guixia
Zhang, Bo
Tang, Yun
author_sort Wang, Biting
collection PubMed
description BACKGROUND: Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the components of A. euchroma on leukemia has not been explored systematically. METHODS: In this study, we analyzed the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) with our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentration information through Cytoscape. Additionally, molecular docking simulation was performed to calculate whether the components and predicted targets have interactions or not. RESULTS: A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which were involved in 157 targets and 779 compound-target interactions (CTIs). Following the calculation of eight central attributes of targets in A. euchroma-leukemia PPI network, 37 targets with all central attributes greater than the median values were selected to construct the weighted compound-target bipartite network and do the KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling, PI3K-Akt signaling, IL-17 signaling, and T cell receptor signaling pathways. Moreover, molecular docking simulation demonstrated that there were eight pairs of predicted CTIs had the strong binding free energy. CONCLUSIONS: This study deciphered that the efficacy of A. euchroma in the treatment of leukemia might be attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.
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spelling pubmed-75906972020-10-27 Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach Wang, Biting Wu, Zengrui Wang, Jiye Li, Weihua Liu, Guixia Zhang, Bo Tang, Yun BMC Complement Med Ther Research Article BACKGROUND: Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the components of A. euchroma on leukemia has not been explored systematically. METHODS: In this study, we analyzed the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) with our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentration information through Cytoscape. Additionally, molecular docking simulation was performed to calculate whether the components and predicted targets have interactions or not. RESULTS: A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which were involved in 157 targets and 779 compound-target interactions (CTIs). Following the calculation of eight central attributes of targets in A. euchroma-leukemia PPI network, 37 targets with all central attributes greater than the median values were selected to construct the weighted compound-target bipartite network and do the KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling, PI3K-Akt signaling, IL-17 signaling, and T cell receptor signaling pathways. Moreover, molecular docking simulation demonstrated that there were eight pairs of predicted CTIs had the strong binding free energy. CONCLUSIONS: This study deciphered that the efficacy of A. euchroma in the treatment of leukemia might be attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis. BioMed Central 2020-10-27 /pmc/articles/PMC7590697/ /pubmed/33109189 http://dx.doi.org/10.1186/s12906-020-03106-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Biting
Wu, Zengrui
Wang, Jiye
Li, Weihua
Liu, Guixia
Zhang, Bo
Tang, Yun
Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title_full Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title_fullStr Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title_full_unstemmed Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title_short Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach
title_sort insights into the mechanism of arnebia euchroma on leukemia via network pharmacology approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590697/
https://www.ncbi.nlm.nih.gov/pubmed/33109189
http://dx.doi.org/10.1186/s12906-020-03106-z
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