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Author
Tanabe, Shihori Division of Risk Assessment, Center for Biological Safety and Research, National Institute of Health Sciences
Quader, Sabina Innovation Centre of NanoMedicine (iCONM), Kawasaki Institute of Industrial Promotion
Ono, Ryuichi Division of Cellular and Molecular Toxicology, Center for Biological Safety and Research, National Institute of Health Sciences
Tanaka, Hiroyoshi Y. Department of Pharmaceutical Biomedicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
Cabral, Horacio Department of Bioengineering, Graduate School of Engineering, The University of Tokyo
Abstract
Eukaryotic initiation factor 2 (EIF2) signaling plays a crucial role in regulating mRNA translation and initiating eukaryotic protein synthesis. Computational molecular network pathway analysis of the canonical pathways of the coronaviral infection revealed that EIF2 signaling is inactivated when the coronavirus pathogenesis pathway is activated and vice versa. Our computational analyses indicated that the coronavirus pathogenesis pathway and EIF2 signaling had inverse activation states. Computational investigation of upstream or downstream microRNA (miRNA) revealed that EIF2 signaling directly interacted with miRNAs, including let-7, miR-1292-3p (miRNAs with the seed CGCGCCC), miR-15, miR-34, miR-378, miR-493, miR-497, miR-7, miR-8, and MIRLET7. A total of 36 nodes, including 8 molecules (ATF4, BCL2, CCND1, DDIT3, EIF2A, EIF2AK3, EIF4E, and ERK1/2), 1 complex (the ribosomal 40s subunit), and 1 function (apoptosis) in the coronavirus pathogenesis pathway, overlapped with EIF2 signaling. Alterations in EIF2 signaling may play a role in the pathogenesis of coronavirus.
Keywords
coronavirus
EIF2 signaling
microRNA
molecular pathway
network activation
Published Date
2026-02-04
Publication Title
International Journal of Molecular Sciences
Volume
volume27
Issue
issue3
Publisher
MDPI AG
Start Page
1525
ISSN
1422-0067
NCID
AA12038549
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
File Version
publisher
PubMed ID
DOI
CRID
License
https://creativecommons.org/licenses/by/4.0/
Citation
Tanabe, S.; Quader, S.; Ono, R.; Tanaka, H.Y.; Cabral, H. Bioinformatic Prediction of Activation States in Molecular Network Pathways of Eukaryotic Initiation Factor 2 (EIF2) Signaling and Coronavirus Pathogenesis. Int. J. Mol. Sci. 2026, 27, 1525. https://doi.org/10.3390/ijms27031525
助成情報
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22mk0101216: 医薬品等の安全性予測評価に係る分子ネットワークパスウェイ解析に関する研究開発 ( 国立研究開発法人日本医療研究開発機構 / Japan Agency for Medical Research and Development )
23mk0101216: 医薬品等の安全性予測評価に係る分子ネットワークパスウェイ解析に関する研究開発 ( 国立研究開発法人日本医療研究開発機構 / Japan Agency for Medical Research and Development )
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