Exploring the potential mechanism of emetine against coronavirus disease 2019 combined with lung adenocarcinoma: bioinformatics and molecular simulation analyses

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Abstract

Background: Patients with lung adenocarcinoma (LUAD) may be more predisposed to coronavirus disease 2019 (COVID-19) and have a poorer prognosis. Currently, there is still a lack of effective anti-LUAD/COVID-19 drugs. Thus, this study aimed to screen for an effective anti-LUAD/COVID-19 drug and explore the potential mechanisms. Methods: Firstly, we performed differentially expressed gene (DEG) analysis on LUAD transcriptome profiling data in The Cancer Genome Atlas (TCGA), where intersections with COVID-19-related genes were screened out. Then, we conducted Cox proportional hazards analyses on these LUAD/COVID-19 DEGs to construct a risk score. Next, LUAD/COVID-19 DEGs were uploaded on Connectivity Map to obtain drugs for anti-LUAD/COVID-19. Finally, we used network pharmacology, molecular docking, and molecular dynamics (MD) simulation to explore the drug’s therapeutic targets and potential mechanisms for anti-LUAD/COVID-19. Results: We identified 230 LUAD/COVID-19 DEGs and constructed a risk score containing 7 genes (BTK, CCL20, FURIN, LDHA, TRPA1, ZIC5, and SDK1) that could classify LUAD patients into two risk groups. Then, we screened emetine as an effective drug for anti-LUAD/COVID-19. Network pharmacology analyses identified 6 potential targets (IL6, DPP4, MIF, PRF1, SERPING1, and SLC6A4) for emetine in anti-LUAD/COVID-19. Molecular docking and MD simulation analyses showed that emetine exhibited excellent binding capacities to DDP4 and the main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Conclusions: This study found that emetine may inhibit the entry and replication of SARS-CoV-2 and enhance tumor immunity by bounding to DDP4 and Mpro.

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Zhang, K., Wang, K., Zhang, C., Teng, X., Li, D., & Chen, M. (2022). Exploring the potential mechanism of emetine against coronavirus disease 2019 combined with lung adenocarcinoma: bioinformatics and molecular simulation analyses. BMC Cancer, 22(1). https://doi.org/10.1186/s12885-022-09763-2

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