Metabolic profiling of milk thistle different organs using UPLC-TQD-MS/MS coupled to multivariate analysis in relation to their selective antiviral potential

Introduction: Silybum marianum commonly known as milk thistle is one of the most imperative medicinal plants due to its remarkable pharmacological activities. Lately, the antiviral activities of S. marianum extract have been studied and it showed effectiveness against many viruses.

Objective: Although most previous studies were concerned mainly with silymarin content of the fruit, the present study provides comprehensive comparative evaluation of S. marianum different organs' chemical profiles using UPLC-MS/MS coupled to chemometrics to unravel potentially selective antiviral compounds against human coronavirus (HCoV-229E).

Methodology: UPLC-ESI-TQD-MS/MS analysis was utilized to establish metabolic fingerprints for S. marianum organs namely fruits, roots, stems and seeds. Multivariate analysis, using OPLS-DA and HCA-heat map was applied to explore the main discriminatory phytoconstituents between organs. Selective virucidal activity of organs extracts against coronavirus (HCoV-229E) was evaluated for the first time using cytopathic effect (CPE) inhibition assay. Correlation coefficient analysis was implemented for detection of potential constituents having virucidal activity.

Results: UPLC-MS/MS analysis resulted in 87 identified metabolites belonging to different classes. OPLS-DA revealed in-between class discrimination between milk thistle organs proving their significantly different metabolic profiles. The results of CPE assay showed that all tested organ samples exhibited dose dependent inhibitory activity in nanomolar range. Correlation analysis disclosed that caffeic acid-O-hexoside, gadoleic and linolenic acids were the most potentially selective antiviral phytoconstituents.

Conclusion: This study valorizes the importance of different S. marianum organs as wealthy sources of selective and effective antiviral candidates. This approach can be extended to unravel potentially active constituents from complex plant matrices.