Author:
Li Yongming,Yu Songzuo,Li Yu,Liang Xiao,Su Min,Li Rong
Abstract
BackgroundClinically, evidence shows that uterine corpus endometrial carcinoma (UCEC) patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have a higher death-rate. However, current anti-UCEC/coronavirus disease 2019 (COVID-19) treatment is lacking. Plumbagin (PLB), a pharmacologically active alkaloid, is an emerging anti-cancer inhibitor. Accordingly, the current report was designed to identify and characterize the anti-UCEC function and mechanism of PLB in the treatment of patients infected with SARS-CoV-2 via integrated in silico analysis.MethodsThe clinical analyses of UCEC and COVID-19 in patients were conducted using online-accessible tools. Meanwhile, in silico methods including network pharmacology and biological molecular docking aimed to screen and characterize the anti-UCEC/COVID-19 functions, bio targets, and mechanisms of the action of PLB.ResultsThe bioinformatics data uncovered the clinical characteristics of UCEC patients infected with SARS-CoV-2, including specific genes, health risk, survival rate, and prognostic index. Network pharmacology findings disclosed that PLB-exerted anti-UCEC/COVID-19 effects were achieved through anti-proliferation, inducing cytotoxicity and apoptosis, anti-inflammation, immunomodulation, and modulation of some of the key molecular pathways associated with anti-inflammatory and immunomodulating actions. Following molecular docking analysis, in silico investigation helped identify the anti-UCEC/COVID-19 pharmacological bio targets of PLB, including mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and urokinase-type plasminogen activator (PLAU).ConclusionsBased on the present bioinformatic and in silico findings, the clinical characterization of UCEC/COVID-19 patients was revealed. The candidate, core bio targets, and molecular pathways of PLB action in the potential treatment of UCEC/COVID-19 were identified accordingly.
Subject
Endocrinology, Diabetes and Metabolism
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