Integrative In Silico Investigation Reveals the Host-Virus Interactions in Repurposed Drugs Against SARS-CoV-2

The ongoing COVID-19 outbreak have posed a significant threat to public health worldwide. Recently Toll-like receptor (TLR) has been proposed to be the drug target of SARS-CoV-2 treatment, the specificity and efficacy of such treatments remain unknown. In the present study we performed the investiga...

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Bibliographic Details
Published inFrontiers in bioinformatics Vol. 1; p. 763540
Main Authors Yu, Wenhui, Bai, Yuxin, Raha, Arjun, Su, Zhi, Geng, Fei
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 11.01.2022
Subjects
Bioinformatics
chloroquine
hydroxychloroquine
in silico
interactome mapping
SARS-CoV-2
toll-like receptor 9
chloroquine
interactome mapping
SARS-CoV-2
in silico
hydroxychloroquine
toll-like receptor 9
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Summary:The ongoing COVID-19 outbreak have posed a significant threat to public health worldwide. Recently Toll-like receptor (TLR) has been proposed to be the drug target of SARS-CoV-2 treatment, the specificity and efficacy of such treatments remain unknown. In the present study we performed the investigation of repurposed drugs via a framework comprising of Search Tool for Interacting Chemicals (STITCH), Kyoto Encyclopedia of Genes and Genomes (KEGG), molecular docking, and virus-host-drug interactome mapping. Chloroquine (CQ) and hydroxychloroquine (HCQ) were utilized as probes to explore the interaction network that is linked to SARS-CoV-2. 47 drug targets were shown to be overlapped with SARS-CoV-2 network and were enriched in TLR signaling pathway. Molecular docking analysis and molecular dynamics simulation determined the direct binding affinity of TLR9 to CQ and HCQ. Furthermore, we established SARS-CoV-2-human-drug protein interaction map and identified the axis of TLR9-ERC1-Nsp13 and TLR9-RIPK1-Nsp12. Therefore, the elucidation of the interactions of SARS-CoV-2 with TLR9 axis will not only provide pivotal insights into SARS-CoV-2 infection and pathogenesis but also improve the treatment against COVID-19.
Bibliography:Min Wu, Institute for Infocomm Research (A∗STAR), Singapore
These authors have contributed equally to this work
This article was submitted to Integrative Bioinformatics, a section of the journal Frontiers in Bioinformatics
Reviewed by: Suprabhat Mukherjee, Kazi Nazrul University, India
Edited by: Philippe Youkharibache, National Cancer Institute (NIH), United States
ISSN:2673-7647
2673-7647
DOI:10.3389/fbinf.2021.763540