PMID- 31937840
OWN - NLM
STAT- MEDLINE
DCOM- 20201110
LR  - 20210113
IS  - 2045-2322 (Electronic)
IS  - 2045-2322 (Linking)
VI  - 10
IP  - 1
DP  - 2020 Jan 14
TI  - Combined network pharmacology and virtual reverse pharmacology approaches for 
      identification of potential targets to treat vascular dementia.
PG  - 257
LID - 10.1038/s41598-019-57199-9 [doi]
LID - 257
AB  - 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.
FAU - Lagunin, Alexey A
AU  - Lagunin AA
AD  - Pirogov Russian National Research Medical University, Department of 
      Bioinformatics, Moscow, 117997, Russia. alexey.lagunin@ibmc.msk.ru.
AD  - Institute of Biomedical Chemistry, Department of Bioinformatics, Moscow, 119121, 
      Russia. alexey.lagunin@ibmc.msk.ru.
FAU - Ivanov, Sergey M
AU  - Ivanov SM
AD  - Pirogov Russian National Research Medical University, Department of 
      Bioinformatics, Moscow, 117997, Russia.
AD  - Institute of Biomedical Chemistry, Department of Bioinformatics, Moscow, 119121, 
      Russia.
FAU - Gloriozova, Tatyana A
AU  - Gloriozova TA
AD  - Institute of Biomedical Chemistry, Department of Bioinformatics, Moscow, 119121, 
      Russia.
FAU - Pogodin, Pavel V
AU  - Pogodin PV
AD  - Institute of Biomedical Chemistry, Department of Bioinformatics, Moscow, 119121, 
      Russia.
FAU - Filimonov, Dmitry A
AU  - Filimonov DA
AD  - Institute of Biomedical Chemistry, Department of Bioinformatics, Moscow, 119121, 
      Russia.
FAU - Kumar, Sandeep
AU  - Kumar S
AD  - Punjabi University, Department of Pharmaceutical Sciences and Drug Research, 
      Patiala, 147002, India.
FAU - Goel, Rajesh K
AU  - Goel RK
AD  - Punjabi University, Department of Pharmaceutical Sciences and Drug Research, 
      Patiala, 147002, India. goelrkpup@gmail.com.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20200114
PL  - England
TA  - Sci Rep
JT  - Scientific reports
JID - 101563288
SB  - IM
MH  - Databases, Factual
MH  - Dementia, Vascular/*drug therapy
MH  - Drug Evaluation, Preclinical/*methods
MH  - *Molecular Targeted Therapy
MH  - Pharmacology
MH  - User-Computer Interface
PMC - PMC6959222
COIS- The authors declare no competing financial or non-financial interests.
EDAT- 2020/01/16 06:00
MHDA- 2020/11/11 06:00
PMCR- 2020/01/14
CRDT- 2020/01/16 06:00
PHST- 2019/08/02 00:00 [received]
PHST- 2019/12/21 00:00 [accepted]
PHST- 2020/01/16 06:00 [entrez]
PHST- 2020/01/16 06:00 [pubmed]
PHST- 2020/11/11 06:00 [medline]
PHST- 2020/01/14 00:00 [pmc-release]
AID - 10.1038/s41598-019-57199-9 [pii]
AID - 57199 [pii]
AID - 10.1038/s41598-019-57199-9 [doi]
PST - epublish
SO  - Sci Rep. 2020 Jan 14;10(1):257. doi: 10.1038/s41598-019-57199-9.