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A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19

Understanding the molecular mechanism of COVID-19 pathogenesis helps in the rapid therapeutic target identification. Usually, viral protein targets host proteins in an organized fashion. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the gr...

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Autores principales: Das, Jayanta Kumar, Chakraborty, Subhadip, Roy, Swarup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102073/
https://www.ncbi.nlm.nih.gov/pubmed/33965637
http://dx.doi.org/10.1016/j.jbi.2021.103801
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author Das, Jayanta Kumar
Chakraborty, Subhadip
Roy, Swarup
author_facet Das, Jayanta Kumar
Chakraborty, Subhadip
Roy, Swarup
author_sort Das, Jayanta Kumar
collection PubMed
description Understanding the molecular mechanism of COVID-19 pathogenesis helps in the rapid therapeutic target identification. Usually, viral protein targets host proteins in an organized fashion. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the great significance of codon usage biases in establishing host-viral protein–protein interactions (PPI). Exploring the codon usage patterns between a pair of co-evolved host and viral proteins may present novel insight into the host-viral protein interactomes during disease pathogenesis. Leveraging the similarity in codon usage patterns, we propose a computational scheme to recreate the host-viral protein–protein interaction network. We use host proteins from seventeen (17) essential signaling pathways for our current work towards understanding the possible targeting mechanism of SARS-CoV-2 proteins. We infer both negatively and positively interacting edges in the network. Further, extensive analysis is performed to understand the host PPI network topologically and the attacking behavior of the viral proteins. Our study reveals that viral proteins mostly utilize codons, rare in the targeted host proteins (negatively correlated interaction). Among them, non-structural proteins, NSP3 and structural protein, Spike (S), are the most influential proteins in interacting with multiple host proteins. While ranking the most affected pathways, MAPK pathways observe to be the worst affected during the SARS-CoV-2 infection. Several proteins participating in multiple pathways are highly central in host PPI and mostly targeted by multiple viral proteins. We observe many potential targets (host proteins) from the affected pathways associated with the various drug molecules, including Arsenic trioxide, Dexamethasone, Hydroxychloroquine, Ritonavir, and Interferon beta, which are either under clinical trial or in use during COVID-19.
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spelling pubmed-81020732021-05-07 A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19 Das, Jayanta Kumar Chakraborty, Subhadip Roy, Swarup J Biomed Inform Original Research Understanding the molecular mechanism of COVID-19 pathogenesis helps in the rapid therapeutic target identification. Usually, viral protein targets host proteins in an organized fashion. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the great significance of codon usage biases in establishing host-viral protein–protein interactions (PPI). Exploring the codon usage patterns between a pair of co-evolved host and viral proteins may present novel insight into the host-viral protein interactomes during disease pathogenesis. Leveraging the similarity in codon usage patterns, we propose a computational scheme to recreate the host-viral protein–protein interaction network. We use host proteins from seventeen (17) essential signaling pathways for our current work towards understanding the possible targeting mechanism of SARS-CoV-2 proteins. We infer both negatively and positively interacting edges in the network. Further, extensive analysis is performed to understand the host PPI network topologically and the attacking behavior of the viral proteins. Our study reveals that viral proteins mostly utilize codons, rare in the targeted host proteins (negatively correlated interaction). Among them, non-structural proteins, NSP3 and structural protein, Spike (S), are the most influential proteins in interacting with multiple host proteins. While ranking the most affected pathways, MAPK pathways observe to be the worst affected during the SARS-CoV-2 infection. Several proteins participating in multiple pathways are highly central in host PPI and mostly targeted by multiple viral proteins. We observe many potential targets (host proteins) from the affected pathways associated with the various drug molecules, including Arsenic trioxide, Dexamethasone, Hydroxychloroquine, Ritonavir, and Interferon beta, which are either under clinical trial or in use during COVID-19. Elsevier Inc. 2021-06 2021-05-07 /pmc/articles/PMC8102073/ /pubmed/33965637 http://dx.doi.org/10.1016/j.jbi.2021.103801 Text en © 2021 Elsevier Inc. 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 Original Research
Das, Jayanta Kumar
Chakraborty, Subhadip
Roy, Swarup
A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title_full A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title_fullStr A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title_full_unstemmed A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title_short A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19
title_sort scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during covid-19
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102073/
https://www.ncbi.nlm.nih.gov/pubmed/33965637
http://dx.doi.org/10.1016/j.jbi.2021.103801
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