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Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia

Dementia is a major cause of disability and dependency among older people. If the lives of people with dementia are to be improved, research and its translation into druggable target are crucial. Ancient systems of healthcare (Ayurveda, Siddha, Unani and Sowa-Rigpa) have been used from centuries for...

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Autores principales: Lagunin, Alexey A., Ivanov, Sergey M., Gloriozova, Tatyana A., Pogodin, Pavel V., Filimonov, Dmitry A., Kumar, Sandeep, Goel, Rajesh K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959222/
https://www.ncbi.nlm.nih.gov/pubmed/31937840
http://dx.doi.org/10.1038/s41598-019-57199-9
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author Lagunin, Alexey A.
Ivanov, Sergey M.
Gloriozova, Tatyana A.
Pogodin, Pavel V.
Filimonov, Dmitry A.
Kumar, Sandeep
Goel, Rajesh K.
author_facet Lagunin, Alexey A.
Ivanov, Sergey M.
Gloriozova, Tatyana A.
Pogodin, Pavel V.
Filimonov, Dmitry A.
Kumar, Sandeep
Goel, Rajesh K.
author_sort Lagunin, Alexey A.
collection PubMed
description Dementia is a major cause of disability and dependency among older people. If the lives of people with dementia are to be improved, research and its translation into druggable target are crucial. Ancient systems of healthcare (Ayurveda, Siddha, Unani and Sowa-Rigpa) have been used from centuries for the treatment vascular diseases and dementia. This traditional knowledge can be transformed into novel targets through robust interplay of network pharmacology (NetP) with reverse pharmacology (RevP), without ignoring cutting edge biomedical data. This work demonstrates interaction between recent and traditional data, and aimed at selection of most promising targets for guiding wet lab validations. PROTEOME, DisGeNE, DISEASES and DrugBank databases were used for selection of genes associated with pathogenesis and treatment of vascular dementia (VaD). The selection of new potential drug targets was made by methods of NetP (DIAMOnD algorithm, enrichment analysis of KEGG pathways and biological processes of Gene Ontology) and manual expert analysis. The structures of 1976 phytomolecules from the 573 Indian medicinal plants traditionally used for the treatment of dementia and vascular diseases were used for computational estimation of their interactions with new predicted VaD-related drug targets by RevP approach based on PASS (Prediction of Activity Spectra for Substances) software. We found 147 known genes associated with vascular dementia based on the analysis of the databases with gene-disease associations. Six hundred novel targets were selected by NetP methods based on 147 gene associations. The analysis of the predicted interactions between 1976 phytomolecules and 600 NetP predicted targets leaded to the selection of 10 potential drug targets for the treatment of VaD. The translational value of these targets is discussed herewith. Twenty four drugs interacting with 10 selected targets were identified from DrugBank. These drugs have not been yet studied for the treatment of VaD and may be investigated in this field for their repositioning. The relation between inhibition of two selected targets (GSK-3, PTP1B) and the treatment of VaD was confirmed by the experimental studies on animals and reported separately in our recent publications.
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spelling pubmed-69592222020-01-16 Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia Lagunin, Alexey A. Ivanov, Sergey M. Gloriozova, Tatyana A. Pogodin, Pavel V. Filimonov, Dmitry A. Kumar, Sandeep Goel, Rajesh K. Sci Rep Article Dementia is a major cause of disability and dependency among older people. If the lives of people with dementia are to be improved, research and its translation into druggable target are crucial. Ancient systems of healthcare (Ayurveda, Siddha, Unani and Sowa-Rigpa) have been used from centuries for the treatment vascular diseases and dementia. This traditional knowledge can be transformed into novel targets through robust interplay of network pharmacology (NetP) with reverse pharmacology (RevP), without ignoring cutting edge biomedical data. This work demonstrates interaction between recent and traditional data, and aimed at selection of most promising targets for guiding wet lab validations. PROTEOME, DisGeNE, DISEASES and DrugBank databases were used for selection of genes associated with pathogenesis and treatment of vascular dementia (VaD). The selection of new potential drug targets was made by methods of NetP (DIAMOnD algorithm, enrichment analysis of KEGG pathways and biological processes of Gene Ontology) and manual expert analysis. The structures of 1976 phytomolecules from the 573 Indian medicinal plants traditionally used for the treatment of dementia and vascular diseases were used for computational estimation of their interactions with new predicted VaD-related drug targets by RevP approach based on PASS (Prediction of Activity Spectra for Substances) software. We found 147 known genes associated with vascular dementia based on the analysis of the databases with gene-disease associations. Six hundred novel targets were selected by NetP methods based on 147 gene associations. The analysis of the predicted interactions between 1976 phytomolecules and 600 NetP predicted targets leaded to the selection of 10 potential drug targets for the treatment of VaD. The translational value of these targets is discussed herewith. Twenty four drugs interacting with 10 selected targets were identified from DrugBank. These drugs have not been yet studied for the treatment of VaD and may be investigated in this field for their repositioning. The relation between inhibition of two selected targets (GSK-3, PTP1B) and the treatment of VaD was confirmed by the experimental studies on animals and reported separately in our recent publications. Nature Publishing Group UK 2020-01-14 /pmc/articles/PMC6959222/ /pubmed/31937840 http://dx.doi.org/10.1038/s41598-019-57199-9 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Lagunin, Alexey A.
Ivanov, Sergey M.
Gloriozova, Tatyana A.
Pogodin, Pavel V.
Filimonov, Dmitry A.
Kumar, Sandeep
Goel, Rajesh K.
Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title_full Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title_fullStr Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title_full_unstemmed Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title_short Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
title_sort combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959222/
https://www.ncbi.nlm.nih.gov/pubmed/31937840
http://dx.doi.org/10.1038/s41598-019-57199-9
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