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A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease

OBJECTIVE: To investigate the potential active compounds and underlying mechanisms of Paeonia lactiflora Pall. (PLP) on the treatment of Alzheimer's disease (AD) based on network pharmacology. METHODS: The active components of PLP were collected from Traditional Chinese Medicine System Pharmaco...

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Detalles Bibliográficos
Autores principales: Zeng, Qiang, Li, Longfei, Jin, Yu, Chen, Zongzheng, Duan, Lihong, Cao, Meiqun, Ma, Min, Wu, Zhengzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6885190/
https://www.ncbi.nlm.nih.gov/pubmed/31827565
http://dx.doi.org/10.1155/2019/8706589
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author Zeng, Qiang
Li, Longfei
Jin, Yu
Chen, Zongzheng
Duan, Lihong
Cao, Meiqun
Ma, Min
Wu, Zhengzhi
author_facet Zeng, Qiang
Li, Longfei
Jin, Yu
Chen, Zongzheng
Duan, Lihong
Cao, Meiqun
Ma, Min
Wu, Zhengzhi
author_sort Zeng, Qiang
collection PubMed
description OBJECTIVE: To investigate the potential active compounds and underlying mechanisms of Paeonia lactiflora Pall. (PLP) on the treatment of Alzheimer's disease (AD) based on network pharmacology. METHODS: The active components of PLP were collected from Traditional Chinese Medicine System Pharmacology (TCMSP) database, and their possible target proteins were predicted using TCMSP, SwissTargetPrediction, and STITCH databases. The putative AD-related target proteins were identified from Therapeutic Target Database (TTD), GeneCards, and MalaCards database. The compound-target-disease network interactions were established to obtain the key targets about PLP acting on AD by network topology analysis. Then, the function annotation and signaling pathways of key targets were performed by GO and KEGG enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking using SystemsDock tools. RESULTS: There were 7 active compounds involving in 151 predicted targets identified in PLP. Besides, a total of 160 AD-related targets were identified. Among these targets, 30 shared targets of PLP and AD were acquired. After topological analysis of the PLP potential target-AD target network, 33 key targets that were highly responsible for the therapeutic effects of PLP on AD were obtained. Further GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in cell apoptosis and inflammatory response and maintained the function of neurons to accomplish the anti-AD activity. The molecular docking analysis verified that the 7 active compounds had definite affinity with the key targets. CONCLUSIONS: The ameliorative effects of PLP on AD were predicted to be associated with regulating neural cell apoptosis, inflammatory response, and neurotrophy via various pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, and neurotrophin signaling pathway.
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spelling pubmed-68851902019-12-11 A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease Zeng, Qiang Li, Longfei Jin, Yu Chen, Zongzheng Duan, Lihong Cao, Meiqun Ma, Min Wu, Zhengzhi Evid Based Complement Alternat Med Research Article OBJECTIVE: To investigate the potential active compounds and underlying mechanisms of Paeonia lactiflora Pall. (PLP) on the treatment of Alzheimer's disease (AD) based on network pharmacology. METHODS: The active components of PLP were collected from Traditional Chinese Medicine System Pharmacology (TCMSP) database, and their possible target proteins were predicted using TCMSP, SwissTargetPrediction, and STITCH databases. The putative AD-related target proteins were identified from Therapeutic Target Database (TTD), GeneCards, and MalaCards database. The compound-target-disease network interactions were established to obtain the key targets about PLP acting on AD by network topology analysis. Then, the function annotation and signaling pathways of key targets were performed by GO and KEGG enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking using SystemsDock tools. RESULTS: There were 7 active compounds involving in 151 predicted targets identified in PLP. Besides, a total of 160 AD-related targets were identified. Among these targets, 30 shared targets of PLP and AD were acquired. After topological analysis of the PLP potential target-AD target network, 33 key targets that were highly responsible for the therapeutic effects of PLP on AD were obtained. Further GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in cell apoptosis and inflammatory response and maintained the function of neurons to accomplish the anti-AD activity. The molecular docking analysis verified that the 7 active compounds had definite affinity with the key targets. CONCLUSIONS: The ameliorative effects of PLP on AD were predicted to be associated with regulating neural cell apoptosis, inflammatory response, and neurotrophy via various pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, and neurotrophin signaling pathway. Hindawi 2019-11-16 /pmc/articles/PMC6885190/ /pubmed/31827565 http://dx.doi.org/10.1155/2019/8706589 Text en Copyright © 2019 Qiang Zeng et al. http://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
Zeng, Qiang
Li, Longfei
Jin, Yu
Chen, Zongzheng
Duan, Lihong
Cao, Meiqun
Ma, Min
Wu, Zhengzhi
A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title_full A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title_fullStr A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title_full_unstemmed A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title_short A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer's Disease
title_sort network pharmacology approach to reveal the underlying mechanisms of paeonia lactiflora pall. on the treatment of alzheimer's disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6885190/
https://www.ncbi.nlm.nih.gov/pubmed/31827565
http://dx.doi.org/10.1155/2019/8706589
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