henhaobio
Sign in

bioRxivPharmacology & Toxicology

Active components of commonly prescribed medicines affect influenza A virus-host cell interaction: a pilot study

A. Ianevski, R. Yao, E. Zusinaite, H. Lysvand, V. Oksenych, T. Tenson, M. Bjoras, D. E. Kainov

PDFDOIPreprint

Abstract

BackgroundEvery year, millions of people are hospitalized, and thousands die from influenza A virus (FLUAV) infection. Most cases of hospitalizations and death occur among elderly. Many of these elderly patients are reliant on medical treatment of underlying chronic diseases, such as arthritis, diabetes, and hypertension. We hypothesized that the commonly prescribed medicines for treatment of underlying chronic diseases can affect host responses to FLUAV infection, and thus contribute to morbidity and mortality associated with influenza. Therefore, the aim of this study was to examine whether commonly prescribed medicines could affect host responses to virus infection in vitro. MethodsWe first identified 45 active compounds of commonly prescribed medicines. Then we constructed a drug-target interaction network and identified potential implication of these interactions for FLUAV-host cell interplay. Finally, we tested the effect of 45 drugs on viability, transcription and metabolism of mock- and FLUAV-infected human retinal pigment epithelial (RPE) cells. ResultsIn silico drug-target interaction analysis revealed that many drugs, such as atorvastatin, candesartan, and hydroxocobalam, could target and modulate FLUAV-host cell interaction. In vitro experiments showed that these and other compounds at non-cytotoxic concentrations differently affected transcription and metabolism of mock- and FLUAV-infected cells. ConclusionMany commonly prescribed drugs modulate FLUAV-host cell interactions in silico and in vitro and, therefore, could affect their interplay in vivo, thus, contributing to morbidity and mortality of patients with influenza virus infections.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.