Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS

Sinead M O'Donovan; Hunter Eby; Nicholas D Henkel; Justin Creeden; Ali Imami; Sophie Asah; Xiaolu Zhang; Xiaojun Wu; Rawan Alnafisah; R Travis Taylor; James Reigle; Alexander Thorman; Behrouz Shamsaei; Jarek Meller; Robert E McCullumsmith

doi:10.21203/rs.3.rs-25643/v1

Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS

Sinead M O'Donovan, Hunter Eby, Nicholas D Henkel, Justin Creeden, Ali Imami, Sophie Asah, Xiaolu Zhang, Xiaojun Wu, Rawan Alnafisah, R Travis Taylor, James Reigle, Alexander Thorman, Behrouz Shamsaei, Jarek Meller, Robert E McCullumsmith

Research output: Contribution to journal › Article

Abstract

The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.

Original language	English
Journal	Research square
DOIs	https://doi.org/10.21203/rs.3.rs-25643/v1
Publication status	Published - 30 Apr 2020
Externally published	Yes

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title = "Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS",

abstract = "The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an {"}omics{"} repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.",

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doi = "10.21203/rs.3.rs-25643/v1",

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TY - JOUR

T1 - Identification of new drug treatments to combat COVID19

T2 - A signature-based approach using iLINCS

AU - O'Donovan, Sinead M

AU - Eby, Hunter

AU - Henkel, Nicholas D

AU - Creeden, Justin

AU - Imami, Ali

AU - Asah, Sophie

AU - Zhang, Xiaolu

AU - Wu, Xiaojun

AU - Alnafisah, Rawan

AU - Taylor, R Travis

AU - Reigle, James

AU - Thorman, Alexander

AU - Shamsaei, Behrouz

AU - Meller, Jarek

AU - McCullumsmith, Robert E

PY - 2020/4/30

Y1 - 2020/4/30

N2 - The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.

AB - The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.

U2 - 10.21203/rs.3.rs-25643/v1

DO - 10.21203/rs.3.rs-25643/v1

M3 - Article

C2 - 32702077

SN - 2693-5015

JO - Research square

JF - Research square

ER -

Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS

Abstract

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