Network medicine framework for identifying drug-repurposing opportunities for COVID-19

Abstract

Significance The COVID-19 pandemic has highlighted the importance of prioritizing approved drugs to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. We experimentally screened 918 drugs, allowing us to evaluate the performance of the existing drug-repurposing methodologies, and used a consensus algorithm to increase the accuracy of the predictions. Finally, we screened in human cells the top-ranked drugs, identifying six drugs that reduced viral infection, four of which could be repurposed to treat COVID-19. The developed strategy has significance beyond COVID-19, allowing us to identify drug-repurposing candidates for neglected diseases.

Cited by papers we hold 6

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• Major Insights in Dynamics of Host Response to SARS-CoV-2: Impacts and Challenges · 2021
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• Deep learning identifies synergistic drug combinations for treating COVID-19 · 2021
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• A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19 · 2020
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• Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing · 2020
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