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Network-based drug repurposing for the treatment of COVID-19 patients in different clinical stages.
Wang, Xin; Wang, Han; Yin, Guosheng; Zhang, Yan Dora.
  • Wang X; Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China.
  • Wang H; Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China.
  • Yin G; Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China.
  • Zhang YD; Department of Mathematics, Imperial College London, London, The United Kingdom.
Heliyon ; 9(3): e14059, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-2286207
ABSTRACT
In the severe acute respiratory coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need to develop effective treatments. Through a network-based drug repurposing approach, several effective drug candidates are identified for treating COVID-19 patients in different clinical stages. The proposed approach takes advantage of computational prediction methods by integrating publicly available clinical transcriptome and experimental data. We identify 51 drugs that regulate proteins interacted with SARS-CoV-2 protein through biological pathways against COVID-19, some of which have been experimented in clinical trials. Among the repurposed drug candidates, lovastatin leads to differential gene expression in clinical transcriptome for mild COVID-19 patients, and estradiol cypionate mainly regulates hormone-related biological functions to treat severe COVID-19 patients. Multi-target mechanisms of drug candidates are also explored. Erlotinib targets the viral protein interacted with cytokine and cytokine receptors to affect SARS-CoV-2 attachment and invasion. Lovastatin and testosterone block the angiotensin system to suppress the SARS-CoV-2 infection. In summary, our study has identified effective drug candidates against COVID-19 for patients in different clinical stages and provides comprehensive understanding of potential drug mechanisms.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Heliyon Year: 2023 Document Type: Article Affiliation country: J.heliyon.2023.e14059

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Heliyon Year: 2023 Document Type: Article Affiliation country: J.heliyon.2023.e14059