Selected article for: "binding affinity and docking simulation"
Author: Cava, Claudia; Bertoli, Gloria; Castiglioni, Isabella
Title: Potential drugs against COVID-19 revealed by gene expression profile, molecular docking and molecular dynamic simulation
  • Cord-id: sti84npj
  • Document date: 2021_7_20
    • ID: sti84npj
    Snippet: Aim: SARS-CoV-2, an emerging betacoronavirus, is the causative agent of COVID-19. Currently, there are few specific and selective antiviral drugs for the treatment and vaccines to prevent contagion. However, their long-term effects can be revealed after several years, and new drugs for COVID-19 should continue to be investigated. Materials & methods: In the first step of our study we identified, through a gene expression analysis, several drugs that could act on the biological pathways altered i
    Document: Aim: SARS-CoV-2, an emerging betacoronavirus, is the causative agent of COVID-19. Currently, there are few specific and selective antiviral drugs for the treatment and vaccines to prevent contagion. However, their long-term effects can be revealed after several years, and new drugs for COVID-19 should continue to be investigated. Materials & methods: In the first step of our study we identified, through a gene expression analysis, several drugs that could act on the biological pathways altered in COVID-19. In the second step, we performed a docking simulation to test the properties of the identified drugs to target SARS-CoV-2. Results: The drugs that showed a higher binding affinity are bardoxolone (-8.78 kcal/mol), irinotecan (-8.40 kcal/mol) and pyrotinib (-8.40 kcal/mol). Conclusion: We suggested some drugs that could be efficient in treating COVID-19.

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