Computational gene expression profiling in the exploration of biomarkers, non-coding functional RNAs and drug perturbagens for COVID-19.


Journal

Journal of biomolecular structure & dynamics
ISSN: 1538-0254
Titre abrégé: J Biomol Struct Dyn
Pays: England
ID NLM: 8404176

Informations de publication

Date de publication:
05 2022
Historique:
pubmed: 25 11 2020
medline: 23 4 2022
entrez: 24 11 2020
Statut: ppublish

Résumé

The coronavirus disease, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a global health crisis that is being endured with an increased alarm of transmission each day. Though the pandemic has activated innumerable research attention to decipher an antidote, fundamental understanding of the molecular mechanisms is necessary to halt the disease progression. The study focused on comparison of the COVID-19 infected lung tissue gene expression datasets -GSE155241 and GSE150316 with the GEO2R-limma package. The significant up- and downregulated genes were annotated. Further evaluation of the enriched pathways, transcription factors, kinases, noncoding RNAs and drug perturbations revealed the significant molecular mechanisms of the host response. The results revealed a surge in mitochondrial respiration, cytokines, neurodegenerative mechanisms and deprived oxygen, iron, copper, and glucose transport. Hijack of ubiquitination by SARS-CoV-2, hox gene differentiation, histone modification, and miRNA biogenesis were the notable molecular mechanisms inferred. Long non-coding RNAs such as C058791.1, TTTY15 and TPTEP1 were predicted to be efficient in regulating the disease mechanisms. Drugs-F-1566-0341, Digoxin, Proscillaridin and Linifanib that reverse the gene expression signatures were predicted from drug perturbations analysis. The binding efficiency and interaction of proscillaridin and digoxin as obtained from the molecular docking studies confirmed their therapeutic potential. Two overlapping upregulated genes MDH1, SGCE and one downregulated gene PFKFB3 were appraised as potential biomarkers candidates. The upregulation of PGM5, ISLR and ANK2 as measured from their expressions in normal lungs affirmed their possible prognostic biomarker competence. The study explored significant insights for better diagnosis, and therapeutic options for COVID-19. Communicated by Ramaswamy H. Sarma.

Identifiants

pubmed: 33228475
doi: 10.1080/07391102.2020.1850360
pmc: PMC7754930
doi:

Substances chimiques

Biomarkers 0
MicroRNAs 0
Digoxin 73K4184T59
Proscillaridin KC6BL281EN

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3681-3696

Auteurs

S Aishwarya (S)

Department of Bioinformatics, Stella Maris College, Chennai, Tamil Nadu, India.
Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.

K Gunasekaran (K)

Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.

A Anita Margret (AA)

Department of Biotechnology, Bishop Heber College, Tiruchirappalli, Tamil Nadu, India.

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Classifications MeSH