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The impact of the suppression of highly connected protein interactions on the corona virus infection.
Torres, Felipe; Kiwi, Miguel; Schuller, Ivan K.
  • Torres F; Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, 78000024, Santiago, Chile. ftorressanchez@physics.ucsd.edu.
  • Kiwi M; Centro de Nanociencia y Nanotecnología CEDENNA, Avda. Ecuador 3493, Estación Central, 9170124, Santiago, Chile. ftorressanchez@physics.ucsd.edu.
  • Schuller IK; Department of Physics and Center for Advanced Nanoscience, University of California San Diego, La Jolla, CA, 92093, USA. ftorressanchez@physics.ucsd.edu.
Sci Rep ; 12(1): 9188, 2022 06 02.
Article in English | MEDLINE | ID: covidwho-1873556
ABSTRACT
Several highly effective Covid-19 vaccines are in emergency use, although more-infectious coronavirus strains, could delay the end of the pandemic even further. Because of this, it is highly desirable to develop fast antiviral drug treatments to accelerate the lasting immunity against the virus. From a theoretical perspective, computational approaches are useful tools for antiviral drug development based on the data analysis of gene expression, chemical structure, molecular pathway, and protein interaction mapping. This work studies the structural stability of virus-host interactome networks based on the graphical representation of virus-host protein interactions as vertices or nodes connected by commonly shared proteins. These graphical network visualization methods are analogous to those use in the design of artificial neural networks in neuromorphic computing. In standard protein-node-based network representation, virus-host interaction merges with virus-protein and host-protein networks, introducing redundant links associated with the internal virus and host networks. On the contrary, our approach provides a direct geometrical representation of viral infection structure and allows the effective and fast detection of the structural robustness of the virus-host network through proteins removal. This method was validated by applying it to H1N1 and HIV viruses, in which we were able to pinpoint the changes in the Interactome Network produced by known vaccines. The application of this method to the SARS-CoV-2 virus-host protein interactome implies that nonstructural proteins nsp4, nsp12, nsp16, the nuclear pore membrane glycoprotein NUP210, and ubiquitin specific peptidase USP54 play a crucial role in the viral infection, and their removal may provide an efficient therapy. This method may be extended to any new mutations or other viruses for which the Interactome Network is experimentally determined. Since time is of the essence, because of the impact of more-infectious strains on controlling the spread of the virus, this method may be a useful tool for novel antiviral therapies.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viruses / Virus Diseases / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-13373-0

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viruses / Virus Diseases / Influenza A Virus, H1N1 Subtype / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-13373-0