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Unveiling ancestral relations, host–pathogen interactions and comparative viral miRNA insights of dengue virus serotypes

Authors :
Rahman, Atikur
Susmi, Tasmina Ferdous
Yasmin, Farzana
Bhattacharjee, Arittra
Hossain, Mohammad Uzzal
Das, Keshob Chandra
Keya, Chaman Ara
Salimullah, Md.
Source :
Network Modeling and Analysis in Health Informatics and Bioinformatics; December 2021, Vol. 10 Issue: 1
Publication Year :
2021

Abstract

Dengue fever is the most widespread mosquito-borne viral disease caused by the four serotypes of Dengue virus that belong to the Genus Flavivirus(family Flaviviridae). The diversity of serotype makes the diseases fatal with the possibility to be infected four times and makes complications in the antiviral drug discovery process. In this study, we analyzed the genomic diversity along with phylogenetical relations of the complete genome of four dengue virus serotypes found in different regions in the world. Viral pathogen and its host (human, mosquito) protein–protein interactions (PPIs) have been performed to reveal the connection between the proteins of host and pathogen. The analysis revealed that DENV3 and DENV1 strains are closely related, whereas the other 2 strains (DENV2 and DENV4) are distinctly related. DENV-2 serotype has been supposed to be more virulent, because more epidemics of dengue hemorrhagic fever have been associated with it than with the other serotypes. PPIs between dengue virus proteins obtained from Bangladesh regions and its host revealed that dengue–human PPIs are more prevail in DENV2 and DENV3 serotypes, whereas dengue–mosquito PPIs are most predominant in DENV1 serotype. Moreover, precursor miRNAs and their respective mature miRNAs are also predicted that may provide more clear insight into dengue virus pathogenesis. The present analysis provides detailed pictures of the origin, evolution, and genetic mutations of the dengue virus serotypes. This study can facilitate one stepping stone in the development and production of preventive, affordable, and safe antiviral medications.

Details

Language :
English
ISSN :
21926662 and 21926670
Volume :
10
Issue :
1
Database :
Supplemental Index
Journal :
Network Modeling and Analysis in Health Informatics and Bioinformatics
Publication Type :
Periodical
Accession number :
ejs58452594
Full Text :
https://doi.org/10.1007/s13721-021-00297-4