A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect

Objective. The purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD). Methods. The components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape...

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Main Authors: Tiancheng Ma, Yu Sun, Chang Jiang, Weilin Xiong, Tingxu Yan, Bo Wu, Ying Jia
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Evidence-Based Complementary and Alternative Medicine
Online Access:http://dx.doi.org/10.1155/2021/7127129
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spelling doaj-2ee9c0ae4f884acaaaccc35f16f63fe72021-07-12T02:13:24ZengHindawi LimitedEvidence-Based Complementary and Alternative Medicine1741-42882021-01-01202110.1155/2021/7127129A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant EffectTiancheng Ma0Yu Sun1Chang Jiang2Weilin Xiong3Tingxu Yan4Bo Wu5Ying Jia6School of Traditional Chinese Materia MedicaResearch Institute of Medicine and PharmacySchool of Traditional Chinese Materia MedicaSchool of Traditional Chinese Materia MedicaSchool of Functional Food and WineSchool of Functional Food and WineSchool of Functional Food and WineObjective. The purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD). Methods. The components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking. Results. A total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study. Conclusions. It predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.http://dx.doi.org/10.1155/2021/7127129
collection DOAJ
language English
format Article
sources DOAJ
author Tiancheng Ma
Yu Sun
Chang Jiang
Weilin Xiong
Tingxu Yan
Bo Wu
Ying Jia
spellingShingle Tiancheng Ma
Yu Sun
Chang Jiang
Weilin Xiong
Tingxu Yan
Bo Wu
Ying Jia
A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
Evidence-Based Complementary and Alternative Medicine
author_facet Tiancheng Ma
Yu Sun
Chang Jiang
Weilin Xiong
Tingxu Yan
Bo Wu
Ying Jia
author_sort Tiancheng Ma
title A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
title_short A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
title_full A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
title_fullStr A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
title_full_unstemmed A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect
title_sort combined network pharmacology and molecular docking approach to investigate candidate active components and multitarget mechanisms of hemerocallis flowers on antidepressant effect
publisher Hindawi Limited
series Evidence-Based Complementary and Alternative Medicine
issn 1741-4288
publishDate 2021-01-01
description Objective. The purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD). Methods. The components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking. Results. A total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study. Conclusions. It predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.
url http://dx.doi.org/10.1155/2021/7127129
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