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Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective
The current pandemic of 2019 novel coronavirus disease (COVID-19) caused by a novel virus strain, 2019-nCoV/SARS-CoV-2 have posed a serious threat to global public health and economy. It is largely unknown how the human immune system responds to this infection. A better understanding of the immune r...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319641/ https://www.ncbi.nlm.nih.gov/pubmed/32599245 http://dx.doi.org/10.1016/j.ijbiomac.2020.06.228 |
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author | Prasad, Kartikay Khatoon, Fatima Rashid, Summya Ali, Nemat AlAsmari, Abdullah F. Ahmed, Mohammad Z. Alqahtani, Ali S. Alqahtani, Mohammed S. Kumar, Vijay |
author_facet | Prasad, Kartikay Khatoon, Fatima Rashid, Summya Ali, Nemat AlAsmari, Abdullah F. Ahmed, Mohammad Z. Alqahtani, Ali S. Alqahtani, Mohammed S. Kumar, Vijay |
author_sort | Prasad, Kartikay |
collection | PubMed |
description | The current pandemic of 2019 novel coronavirus disease (COVID-19) caused by a novel virus strain, 2019-nCoV/SARS-CoV-2 have posed a serious threat to global public health and economy. It is largely unknown how the human immune system responds to this infection. A better understanding of the immune response to SARS-CoV-2 will be important to develop therapeutics against COVID-19. Here, we have used transcriptomic profile of human alveolar adenocarcinoma cells (A549) infected with SARS-CoV-2 and employed a network biology approach to generate human-virus interactome. Network topological analysis discovers 15 SARS-CoV-2 targets, which belongs to a subset of interferon (IFN) stimulated genes (ISGs). These ISGs (IFIT1, IFITM1, IRF7, ISG15, MX1, and OAS2) can be considered as potential candidates for drug targets in the treatments of COVID-19. We have identified significant interaction between ISGs and TLR3 agonists, like poly I: C, and imiquimod, and suggests that TLR3 agonists can be considered as a potential drug for drug repurposing in COVID-19. Our network centric analysis suggests that moderating the innate immune response is a valuable approach to target COVID-19. |
format | Online Article Text |
id | pubmed-7319641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73196412020-06-29 Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective Prasad, Kartikay Khatoon, Fatima Rashid, Summya Ali, Nemat AlAsmari, Abdullah F. Ahmed, Mohammad Z. Alqahtani, Ali S. Alqahtani, Mohammed S. Kumar, Vijay Int J Biol Macromol Article The current pandemic of 2019 novel coronavirus disease (COVID-19) caused by a novel virus strain, 2019-nCoV/SARS-CoV-2 have posed a serious threat to global public health and economy. It is largely unknown how the human immune system responds to this infection. A better understanding of the immune response to SARS-CoV-2 will be important to develop therapeutics against COVID-19. Here, we have used transcriptomic profile of human alveolar adenocarcinoma cells (A549) infected with SARS-CoV-2 and employed a network biology approach to generate human-virus interactome. Network topological analysis discovers 15 SARS-CoV-2 targets, which belongs to a subset of interferon (IFN) stimulated genes (ISGs). These ISGs (IFIT1, IFITM1, IRF7, ISG15, MX1, and OAS2) can be considered as potential candidates for drug targets in the treatments of COVID-19. We have identified significant interaction between ISGs and TLR3 agonists, like poly I: C, and imiquimod, and suggests that TLR3 agonists can be considered as a potential drug for drug repurposing in COVID-19. Our network centric analysis suggests that moderating the innate immune response is a valuable approach to target COVID-19. Elsevier B.V. 2020-11-15 2020-06-26 /pmc/articles/PMC7319641/ /pubmed/32599245 http://dx.doi.org/10.1016/j.ijbiomac.2020.06.228 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Prasad, Kartikay Khatoon, Fatima Rashid, Summya Ali, Nemat AlAsmari, Abdullah F. Ahmed, Mohammad Z. Alqahtani, Ali S. Alqahtani, Mohammed S. Kumar, Vijay Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title | Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title_full | Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title_fullStr | Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title_full_unstemmed | Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title_short | Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective |
title_sort | targeting hub genes and pathways of innate immune response in covid-19: a network biology perspective |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319641/ https://www.ncbi.nlm.nih.gov/pubmed/32599245 http://dx.doi.org/10.1016/j.ijbiomac.2020.06.228 |
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