Repurposing Drugs as Potential Therapeutics for the SARS-Cov-2 Viral Infection: Automatizing a Blind Molecular Docking High-throughput Pipeline
In the context of the COVID-19 pandemic, scientists worldwide have been looking for ways to stop it using different approaches. One strategy is to look among drugs that have already proved safe for use in humans and tested for other illnesses. Several components from the virus and the infected cell...
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| Autores principales: | , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2022
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/82800 |
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| Sumario: | In the context of the COVID-19 pandemic, scientists worldwide have been looking for ways to stop it using different approaches. One strategy is to look among drugs that have already proved safe for use in humans and tested for other illnesses. Several components from the virus and the infected cell are the potential therapeutic targets from a molecular perspective. We explain how we implemented a cavity-guided blind molecular docking algorithm into a high-throughput computational pipeline to automatically screen and analyze a large set of drugs over a group of SARS-CoV-2 and cell proteins involved in the infection process. We discuss the need to significantly extend the conformational space sampling to find an accurate target-ligand complex. Our results identify nine drugs with potential multi-target activity against COVID-19 at different stages of the infection and immune system evasion. These results are relevant in understanding the SARS-CoV-2 drug’s molecular mechanisms and further clinical treatment development. The code developed is available on GitHub [https://github.com/tripplab/HTVS]. |
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| ISBN: | 978-1-80356-467-8 |
| DOI: | 10.5772/intechopen.105792 |