Unveiling the antiviral mechanism of Forsythia suspensa: A comprehensive analysis of screening targets and components

doi:10.5246/jcps.2024.06.040

Abstract

Abstract:

Forsythia suspensa, a traditional Chinese medicine, exhibits notable antiviral effects, particularly in the context of treating COVID-19. Despite its efficacy, the specific antiviral compounds within F. suspensa and their respective targets have not been elucidated. In this study, network pharmacology techniques were employed to identify antiviral components and targets in F. suspensa, with subsequent analysis of their interactions via molecular docking. Ultimately, 11 active compounds (1–11) and seven antiviral targets (AKT1, TP53, MYC, PTEN, CASP8, MMP9, and VEGFA) were successfully screened. Gene ontology analysis was then employed to predict potential biological signaling pathways associated with these targets. The structure-activity relationship of the active compounds was discussed based on molecular docking results. Additionally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of the active compounds were predicted and analyzed. This study not only highlighted the synergistic effects of multiple targets and pathways within F. suspensa for treating viral diseases but also underscored the druggability of its active compounds. The findings presented here laid a foundation for the development and design of novel antiviral drugs.

Key words: Forsythia suspensa (Thunb.) Vahl, Antiviral, Traditional Chinese medicine targets, Active compounds

Supporting: /attached/file/20240707/20240707164630_166.pdf

Na Sun, Shuo Ma, Linxuan Jin, Xin Zhang, Miao Zhou, Huanhuan Yang, Wenqian Li, Xinru Wu, Yanyan Hou, Yuhan Yuan, Yu Zhang, Penghua Shu. Unveiling the antiviral mechanism of Forsythia suspensa: A comprehensive analysis of screening targets and components[J]. Journal of Chinese Pharmaceutical Sciences, 2024, 33(6): 543-558.

Figures/Tables 15

Table 1. The compounds screened out in the TCM database.

Table 2. The data of the top 20 KEGG pathways.

Table 3. ADMET prediction results of compounds 1–11.

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