A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD These authors contributed equally: Yining Xie, Guangshu Chen, and Weiling Wu

Abstract

The swift transmission rate and unfavorable prognosis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have prompted the pursuit of more effective therapeutic interventions. Azithromycin (AZM) has garnered significant attention for its distinctive pharmacological mechanisms in the treatment of SARS-CoV-2. This study aims to elucidate the biological rationale for employing AZM in patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) who are infected with SARS-CoV-2. Genetic data about COVID-19, COPD, and IPF were independently obtained from the GeneCards database. And 40 drug targets about AZM were retrieved from the STITCH database. The analysis revealed that 311 DEGs were common among COPD, IPF, and COVID-19, and we further found eight genes that interacted with AZM targets. We conducted an analysis of hub genes and their corresponding signaling pathways in these patient cohorts. Additionally, we explored the inhibitory effects of AZM on these hub genes. AZM demonstrated a significant inhibitory effect on eight key genes, except for AR and IL-17 A. These findings suggest that AZM may serve as a promising therapeutic agent for patients with COPD and IPF and SARS-CoV-2 infection.

Keywords: Azithromycin; Bioinformatics; COPD; IPF; SARS-Cov-2.

Fig. 1

The GeneCards database identified 6,550, 3,236, and 1,238 genes associated with COPD, IPF, and COVID-19 after excluding non-functional pseudogenes, respectively. The analysis identified 311 DEGs that were shared among COPD, IPF, and COVID-19 (1 A). Among these, eight genes—IL6, TP53, TGFB1, IL17A, AR, IL6R, SMAD2, and UBC—were found to interact with Azithromycin targets (1B).

Fig. 2

The mutual regulation of eight DEGs in the PPI network. Red represents eight DEGs, and blue represents related genes (2 A). The regulation network of the top 10 hub genes. The redder the color, the more genes are related to each other. There are 13 nodes and 156 edges. The density and heterogeneity of the network made by the top 10 hub genes are 0.216, and 0.756, respectively. The top 10 hub genes are TP53, EP300, IL-6, SMAD2, CREBBP, AR, MDM2, UBC, TGFB1, and IL17A (2B).

Fig. 3

Docked pose of AZM with the top 10 hub genes. In preparation for molecular docking, water molecules, and ligands were removed using PyMOL software. Diagram of the interaction of the top 10 protein molecules with AZM, where the ribbons indicate the backbone structure of the Hub genes protein molecule. The red indicates oxygen atoms, and the blue indicates nitrogen atoms. The molecular docking analysis identified the top 10 hub genes predicted to interact with AZM.

Fig. 4

The qPCR analysis confirmed the inhibitory effect of AZM on the expression of target genes. Expression of all genes was suppressed at specific concentrations of AZM, except for UBC mRNA. The findings demonstrated a consistent pattern of AZM-mediated inhibition across different target gene scenarios. Specifically, SMAD2 mRNA expression was significantly inhibited at AZM concentrations of 40 and 80 µmol/L. CREBBP mRNA expression was significantly reduced at concentrations of 20, 40, and 80 µmol/L. TP53 mRNA expression was significantly inhibited at 20 and 40 µmol/L, while MDM2 mRNA expression was significantly inhibited at 80 µmol/L. Additionally, EP300 mRNA expression was significantly inhibited at concentrations of 20 and 40 µmol/L. In 40 and 80umol/L of the AZM group, IL-6 mRNA is significantly inhibited. In 10 and 20umol/L of the AZM group, TGFB1 mRNA is significantly inhibited.