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Mechanistic insight of the potential of geraniol against Alzheimer’s disease
BACKGROUND: Alzheimer’s disease (AD) as a neurodegenerative disease occupies 3/5–4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstan...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9199166/ https://www.ncbi.nlm.nih.gov/pubmed/35701806 http://dx.doi.org/10.1186/s40001-022-00699-8 |
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author | Liu, Ying Zhou, Shujing Huang, Xufeng Rehman, Hafiz Muzzammel |
author_facet | Liu, Ying Zhou, Shujing Huang, Xufeng Rehman, Hafiz Muzzammel |
author_sort | Liu, Ying |
collection | PubMed |
description | BACKGROUND: Alzheimer’s disease (AD) as a neurodegenerative disease occupies 3/5–4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstanding neuroprotective effects as well as ameliorating influence in memory impairment. Therefore, the present study aims to elucidate the potential of geraniol against AD by network pharmacology-based approach combined with molecular modeling study. MATERIALS AND METHODS: Firstly, we evaluated the druggability of geraniol by ADME method. Then, we obtained the geraniol targets and AD-related targets from multiple open data sources. Afterward, we calculated the intersection through a Venn diagram to find common targets, and via Panther classification system to categorize them. In order to gain a macroscopic understanding of these common targets, we carried out GO terms and KEGG pathways enrichment analyses, according to which we constructed a compound–target–pathway–disease network. In addition, we built a preliminary PPI network which was further analyzed both functionally and topologically. Consequently, five hub targets were sorted out. Finally, we conducted molecular docking and molecular dynamic simulation to validate our findings. RESULTS: In the present study, the pharmacological properties of geraniol were assessed according to ADME and Lipinski’s rule, which demonstrate promising druggability. Then, from 10,972 AD-related targets and 33 geraniol targets, 29 common targets were identified, among which 38.1% of them are metabolite interconversion enzymes, 23.8% are protein modifying enzymes, 33.3% are transmembrane receptors, and the rest are transporters. Enrichment analyses hint that geraniol is involved in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction. We also built a preliminary PPI network to investigate the interplay between these targets and their extensive interactions. Then, by functionally clustering the preliminary PPI network, we gained a cluster of proteins which formed a subnetwork with score of 8.476, and 22 nodes. Its results of GO terms and KEGG pathways enrichment analyses once again suggests that geraniol actively participates in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction, which are believed to be strongly associated with AD pathogenesis. Besides, topological analyses of the preliminary PPI network helped find 5 hub targets (i.e., CHRM3, PRKCA, PRKCD, JAK1, JAK2). To verify their interaction with geraniol molecule, we conducted molecular docking, and found that CHRM3 possesses the highest affinity in binding, indicating that geraniol molecules are closely bound to each hub target, and CHRM3 may serve as a key target of geraniol against AD. It was then further confirmed by molecular dynamic simulation, the result of which supports our hypothesis. CONCLUSION: The present study shares a mechanistic insight of the potential of geraniol against AD, giving a reference to future experimental studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-022-00699-8. |
format | Online Article Text |
id | pubmed-9199166 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91991662022-06-16 Mechanistic insight of the potential of geraniol against Alzheimer’s disease Liu, Ying Zhou, Shujing Huang, Xufeng Rehman, Hafiz Muzzammel Eur J Med Res Research BACKGROUND: Alzheimer’s disease (AD) as a neurodegenerative disease occupies 3/5–4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstanding neuroprotective effects as well as ameliorating influence in memory impairment. Therefore, the present study aims to elucidate the potential of geraniol against AD by network pharmacology-based approach combined with molecular modeling study. MATERIALS AND METHODS: Firstly, we evaluated the druggability of geraniol by ADME method. Then, we obtained the geraniol targets and AD-related targets from multiple open data sources. Afterward, we calculated the intersection through a Venn diagram to find common targets, and via Panther classification system to categorize them. In order to gain a macroscopic understanding of these common targets, we carried out GO terms and KEGG pathways enrichment analyses, according to which we constructed a compound–target–pathway–disease network. In addition, we built a preliminary PPI network which was further analyzed both functionally and topologically. Consequently, five hub targets were sorted out. Finally, we conducted molecular docking and molecular dynamic simulation to validate our findings. RESULTS: In the present study, the pharmacological properties of geraniol were assessed according to ADME and Lipinski’s rule, which demonstrate promising druggability. Then, from 10,972 AD-related targets and 33 geraniol targets, 29 common targets were identified, among which 38.1% of them are metabolite interconversion enzymes, 23.8% are protein modifying enzymes, 33.3% are transmembrane receptors, and the rest are transporters. Enrichment analyses hint that geraniol is involved in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction. We also built a preliminary PPI network to investigate the interplay between these targets and their extensive interactions. Then, by functionally clustering the preliminary PPI network, we gained a cluster of proteins which formed a subnetwork with score of 8.476, and 22 nodes. Its results of GO terms and KEGG pathways enrichment analyses once again suggests that geraniol actively participates in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction, which are believed to be strongly associated with AD pathogenesis. Besides, topological analyses of the preliminary PPI network helped find 5 hub targets (i.e., CHRM3, PRKCA, PRKCD, JAK1, JAK2). To verify their interaction with geraniol molecule, we conducted molecular docking, and found that CHRM3 possesses the highest affinity in binding, indicating that geraniol molecules are closely bound to each hub target, and CHRM3 may serve as a key target of geraniol against AD. It was then further confirmed by molecular dynamic simulation, the result of which supports our hypothesis. CONCLUSION: The present study shares a mechanistic insight of the potential of geraniol against AD, giving a reference to future experimental studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-022-00699-8. BioMed Central 2022-06-14 /pmc/articles/PMC9199166/ /pubmed/35701806 http://dx.doi.org/10.1186/s40001-022-00699-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Liu, Ying Zhou, Shujing Huang, Xufeng Rehman, Hafiz Muzzammel Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title | Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title_full | Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title_fullStr | Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title_full_unstemmed | Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title_short | Mechanistic insight of the potential of geraniol against Alzheimer’s disease |
title_sort | mechanistic insight of the potential of geraniol against alzheimer’s disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9199166/ https://www.ncbi.nlm.nih.gov/pubmed/35701806 http://dx.doi.org/10.1186/s40001-022-00699-8 |
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