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A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19
The alarming pandemic situation of novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection, high drug development cost and slow process of drug discovery have made repositioning of existing drugs for therapeutics a popular alternative. It involves the repurposing of existing sa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9093055/ https://www.ncbi.nlm.nih.gov/pubmed/35578630 http://dx.doi.org/10.1016/j.heliyon.2022.e09387 |
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author | Khurana, Pankaj Varshney, Rajeev Gupta, Apoorv |
author_facet | Khurana, Pankaj Varshney, Rajeev Gupta, Apoorv |
author_sort | Khurana, Pankaj |
collection | PubMed |
description | The alarming pandemic situation of novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection, high drug development cost and slow process of drug discovery have made repositioning of existing drugs for therapeutics a popular alternative. It involves the repurposing of existing safe compounds which results in low overall development costs and shorter development timeline. In the present study, a computational network-biology approach has been used for comparing three candidate drugs i.e. quercetin, N-acetyl cysteine (NAC), and 2-deoxy-glucose (2-DG) to be effectively repurposed against COVID-19. For this, the associations between these drugs and genes of Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS) diseases were retrieved and a directed drug-gene-gene-disease interaction network was constructed. Further, to quantify the associations between a target gene and a disease gene, the shortest paths from the target gene to the disease genes were identified. A vector DV was calculated to represent the extent to which a disease gene was influenced by these drugs. Quercetin was quantified as the best among the three drugs, suited for repurposing with DV of -70.19, followed by NAC with DV of -39.99 and 2-DG with DV of -13.71. The drugs were also assessed for their safety and efficacy balance (in terms of therapeutic index) using network properties. It was found that quercetin was a forerunner than other two drugs. |
format | Online Article Text |
id | pubmed-9093055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90930552022-05-12 A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 Khurana, Pankaj Varshney, Rajeev Gupta, Apoorv Heliyon Research Article The alarming pandemic situation of novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection, high drug development cost and slow process of drug discovery have made repositioning of existing drugs for therapeutics a popular alternative. It involves the repurposing of existing safe compounds which results in low overall development costs and shorter development timeline. In the present study, a computational network-biology approach has been used for comparing three candidate drugs i.e. quercetin, N-acetyl cysteine (NAC), and 2-deoxy-glucose (2-DG) to be effectively repurposed against COVID-19. For this, the associations between these drugs and genes of Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS) diseases were retrieved and a directed drug-gene-gene-disease interaction network was constructed. Further, to quantify the associations between a target gene and a disease gene, the shortest paths from the target gene to the disease genes were identified. A vector DV was calculated to represent the extent to which a disease gene was influenced by these drugs. Quercetin was quantified as the best among the three drugs, suited for repurposing with DV of -70.19, followed by NAC with DV of -39.99 and 2-DG with DV of -13.71. The drugs were also assessed for their safety and efficacy balance (in terms of therapeutic index) using network properties. It was found that quercetin was a forerunner than other two drugs. Elsevier 2022-05-11 /pmc/articles/PMC9093055/ /pubmed/35578630 http://dx.doi.org/10.1016/j.heliyon.2022.e09387 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Khurana, Pankaj Varshney, Rajeev Gupta, Apoorv A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title | A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title_full | A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title_fullStr | A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title_full_unstemmed | A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title_short | A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19 |
title_sort | network-biology led computational drug repurposing strategy to prioritize therapeutic options for covid-19 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9093055/ https://www.ncbi.nlm.nih.gov/pubmed/35578630 http://dx.doi.org/10.1016/j.heliyon.2022.e09387 |
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