Computational modeling of human-nCoV protein-protein interaction network
| Autor: | Sovan Saha, Anup Kumar Halder, Soumyendu Sekhar Bandyopadhyay, Piyali Chatterjee, Mita Nasipuri, Subhadip Basu |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
FOS: Computer and information sciences
PPIN Protein-Protein Interaction Networks Computer Science - Artificial Intelligence Protein interaction network analysis Molecular Networks (q-bio.MN) MERS Middle East Respiratory Syndrome Drug target Susceptible-infected-susceptible model Article General Biochemistry Genetics and Molecular Biology BC Betweenness Centrality SARS Severe Acute Respiratory Syndrome Fuzzy model Humans Quantitative Biology - Molecular Networks Computer Simulation Spreadability index Protein Interaction Maps Molecular Biology Human-nCoV interactions SARS-CoV-2 COVID-19 Proteins CC Closeness centrality High-quality interactions Artificial Intelligence (cs.AI) FOS: Biological sciences SARS-CoV2 Spreader nodes RNA Viral Gene ontology LAC Local average centrality |
| Zdroj: | Methods (San Diego, Calif.) |
| ISSN: | 1046-2023 |
| DOI: | 10.1016/j.ymeth.2021.12.003 |
| Popis: | COVID-19 has created a global pandemic with high morbidity and mortality in 2020. Novel coronavirus (nCoV), also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), is responsible for this deadly disease. International Committee on Taxonomy of Viruses (ICTV) has declared that nCoV is highly genetically similar to SARS-CoV epidemic in 2003 (89% similarity). Limited number of clinically validated Human-nCoV protein interaction data is available in the literature. With this hypothesis, the present work focuses on developing a computational model for nCoV-Human protein interaction network, using the experimentally validated SARS-CoV-Human protein interactions. Initially, level-1 and level-2 human spreader proteins are identified in SARS-CoV-Human interaction network, using Susceptible-Infected-Susceptible (SIS) model. These proteins are considered as potential human targets for nCoV bait proteins. A gene-ontology based fuzzy affinity function has been used to construct the nCoV-Human protein interaction network at 99.98% specificity threshold. This also identifies the level-1 human spreaders for COVID-19 in human protein-interaction network. Level-2 human spreaders are subsequently identified using the SIS model. The derived host-pathogen interaction network is finally validated using 7 potential FDA listed drugs for COVID-19 with significant overlap between the known drug target proteins and the identified spreader proteins. Comment: Total number of pages is 12. Total number of figures is 7. Total number of tables is 1 |
| Databáze: | OpenAIRE |
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