Dataset Information

Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis.

ABSTRACT:

Background

Since the outbreak of coronavirus disease 2019 (COVID-19) in China, numerous research institutions have invested in the development of anti-COVID-19 vaccines and screening for efficacious drugs to manage the virus.

Objective

To explore the potential targets and therapeutic drugs for the prevention and treatment of COVID-19 through data mining and bioinformatics.

Methods

We integrated and profoundly analyzed 10 drugs previously assessed to have promising therapeutic potential in COVID-19 management, and have been recommended for clinical trials. To explore the mechanisms by which these drugs may be involved in the treatment of COVID-19, gene-drug interactions were identified using the DGIdb database after which functional enrichment analysis, protein-protein interaction (PPI) network, and miRNA-gene network construction were performed. We adopted the DGIdb database to explore the candidate drugs for COVID-19.

Results

A total of 43 genes associated with the 10 potential COVID-19 drugs were identified. Function enrichment analysis revealed that these genes were mainly enriched in response to other invasions, toll-like receptor pathways, and they play positive roles in the production of cytokines such as IL-6, IL-8, and INF-?. TNF, TLR3, TLR7, TLR9, and CXCL10 were identified as crucial genes in COVID-19. Through the DGIdb database, we predicted 87 molecules as promising druggable molecules for managing COVID-19.

Conclusions

Findings from this work may provide new insights into COVID-19 mechanisms and treatments. Further, the already identified candidate drugs may improve the efficiency of pharmaceutical treatment in this rapidly evolving global situation.

SUBMITTER: Tan S

PROVIDER: S-EPMC7797890 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis.

Tan Siyou S Chen Wenyan W Xiang Hongxian H Kong Gaoyin G Zou Lianhong L Wei Lai L

Genes & genomics 20210111 1

<h4>Background</h4>Since the outbreak of coronavirus disease 2019 (COVID-19) in China, numerous research institutions have invested in the development of anti-COVID-19 vaccines and screening for efficacious drugs to manage the virus.<h4>Objective</h4>To explore the potential targets and therapeutic drugs for the prevention and treatment of COVID-19 through data mining and bioinformatics.<h4>Methods</h4>We integrated and profoundly analyzed 10 drugs previously assessed to have promising therapeut ...[more]

PMID: 33428154

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Dataset Information

Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis.

Similar Datasets

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