Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19 Article Swipe

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Brian L. Le , Gaia Andreoletti , Tomiko Oskotsky , Albert Vallejo-Gracia , Romel Rosales , Katharine Yu , Idit Kosti , Kristoffer E. Leon , Daniel Bunis , Christine Li , G. Renuka Kumar , Kris M. White , Adolfo Garcı́a-Sastre , Mélanie Ott , Marina Sirota ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.1101/2020.10.23.352666

The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated sixteen of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.

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Computational Biology

Infectious Diseases (Medical Specialty)

Programming Language

Leprosy

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Drug repositioning Clofazimine Computational biology Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Pipeline (software) Transcriptome Drug Biology Bioinformatics Gene Computer science Medicine Gene expression Pharmacology Genetics Immunology Pathology Disease Infectious disease (medical specialty) Programming language Leprosy

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/2020.10.23.352666
PDF: https://www.biorxiv.org/content/biorxiv/early/2020/10/23/2020.10.23.352666.full.pdf
OA Status: green
Cited By: 7
References: 55
Related Works: 10
OpenAlex ID: https://openalex.org/W3093512696

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DOI: https://doi.org/10.1101/2020.10.23.352666

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Title: Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19

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Type: preprint

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Language: en

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Publication year: 2020

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Publication date: 2020-10-23

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Authors: Brian L. Le, Gaia Andreoletti, Tomiko Oskotsky, Albert Vallejo-Gracia, Romel Rosales, Katharine Yu, Idit Kosti, Kristoffer E. Leon, Daniel Bunis, Christine Li, G. Renuka Kumar, Kris M. White, Adolfo Garcı́a-Sastre, Mélanie Ott, Marina Sirota

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Landing page: https://doi.org/10.1101/2020.10.23.352666

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PDF URL: https://www.biorxiv.org/content/biorxiv/early/2020/10/23/2020.10.23.352666.full.pdf

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Concepts: Drug repositioning, Clofazimine, Computational biology, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Pipeline (software), Transcriptome, Drug, Biology, Bioinformatics, Gene, Computer science, Medicine, Gene expression, Pharmacology, Genetics, Immunology, Pathology, Disease, Infectious disease (medical specialty), Programming language, Leprosy

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Cited by: 7

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Citations by year (recent): 2025: 2, 2023: 1, 2022: 2, 2021: 2

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