Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation.

Xiao-Li Chen,Cheng Tang,Qing-Ling Xiao,Ya-Xi Zhao,Jin Xu,Zhong-Hua Pang,Qi-Yong Zhu,Dan-Dan Zhou,Qi Wang,Hongcai Shang

doi:10.1155/2021/6658395

Abstract

Objective This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation. Methods Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets. Results Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis. Conclusions FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

Highlights

Pulmonary fibrosis may take place in a variety of clinical settings and may threaten human life [1, 2]
Mining the Potential Pharmacodynamic Compounds and Related Targets of Fei-Xian formula (FXF). e names of 7 herbs were imported into the BATMAN-Traditional Chinese medicine (TCM), Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the analysis platform successively, to acquire the chemical compounds with corresponding information [23]. ereafter, the drug likeness (DL) ≥ 0.18 and bioavailability (OB) ≥ 30% were used as the thresholds to screen those possible pharmacodynamic compounds in FXF by the method in literature [24, 25]
We applied Cytoscape in constructing the FXF candidate component-target network for the treatment of pulmonary fibrosis, where “component” was set as square, whereas “target” was set as circle. ereafter, the node degree in candidate component-target network was calculated and ranked by CytoHubba plug-in [35], and the value was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network

Summary

Introduction

Pulmonary fibrosis may take place in a variety of clinical settings and may threaten human life [1, 2]. Nintedanib and pirfenidone have been approved to be used to treat pulmonary fibrosis, yet they have serious diverse reactions (such as gastrointestinal symptoms, photosensitivity, and abnormal liver function) [7,8,9,10]. Such phenomenon may be ascribed to the complicated regulatory networks involved in pulmonary fibrosis, which suppress or promote associated target genes or pathway expression [11,12,13]. The networks modulate fibrosis-related gene expression through activating or inactivating the relevant pathways, but not through one single pathway [17]

Methods

Results

Conclusion