Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Conference object . 2023
License: CC BY
Data sources: Datacite
ZENODO
Conference object . 2023
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Development of miRNA-based Therapeutics against Zika Virus using Bioinformatics approaches.

Authors: Pritam, Manisha; Verma, Ananya; Dutta, Somenath;

Development of miRNA-based Therapeutics against Zika Virus using Bioinformatics approaches.

Abstract

ABSTRACT Zika virus infection is characterized by numerous symptoms including fever, joint pain, conjunctivitis, andneurological complications like the Guillain-Barre syndrome in rare cases. To date, 89 countries and territories have been infected with this virus. There is no specific treatment or approved vaccine available forthe Zika virus. Therefore, there is an urgent need to develop an efficient therapeutic against Zika virus.Previously, it was reported that during infection, viruses or other pathogens downregulate the human miRNAfor better growth. If we increase the level of these downregulated miRNAs, it can inhibit the growth of pathogens or viruses. In the present study, we have used 3'UTR (10367 to 10794) and polyprotein(YP_002790881.1) sequence of Zika virus (NC_012532) for the prediction of human miRNA using the miRNAProtPred webserver. We predicted 193 and 569 unique human miRNAs for the 3'UTR and polyprotein sequences, respectively. 22 human miRNAs were identified as common in both groups. Interestingly, several predicted human miRNAs were reported as downregulated miRNAs during Zika infection or inhibitors of the Zika virus replication/protein expression such as miR-30e-3p. This supports the reliability of the current approach, and the potential of the predicted miRNA to inhibit the growth of Zika virus. However, furthere xperimental validation is required before going to different stages of clinical trials. The current approach will facilitate the development of miRNA-based therapeutics against pathogenic diseases.

Keywords

miRNA, miRNA mimics, Zika virus, inhibitor

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green