Molecular Networking-Guided Isolation of a Phenolic Constituent from Prunus mume Seed and Its Antioxidant and Anti-Inflammatory Activities

Abstract

Prunus mume (Maesil) is used in health foods and alternative medicine in Korea. In the present study, the anti-inflammatory and antioxidant effects of phenolics from P. mume seed extracts were examined. First, the biological activities of various P. mume extracts were evaluated, and the profiles of their chemical compounds were investigated by Global Natural Products Social (GNPS)-molecular networking. Among these extracts, fermented Maesil seed extract (FMSE) showed potent anti-inflammatory and antioxidant activity, and demonstrated the presence of phenolic clusters in GNPS-based studies. Thus, the chemical constituents of this extract were further investigated. Subsequently, the chemical composition of the active CH2Cl2 fraction of FMSE was explored using an advanced GNPS analysis tool, MolNetEnhancer. In addition, the molecular structure of compound 1 from the CH2Cl2 fraction was similarly predicted with Network Annotation Propagation (NAP). Finally, the anti-inflammatory and antioxidant effects of compound 1 were confirmed by lipopolysaccharide (LPS)-induced nitric oxide production and DPPH assay. Western blot analysis revealed that compound 1 downregulated the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) proteins. The molecular docking simulation additionally confirmed significant interactions of 1 with iNOS and COX-2 proteins. Our findings suggested that an integrated GNPS-based approach could prioritize samples in the early fractionation process and improve the accuracy of target compound prediction.

Charting the Cannabis plant chemical space with computational metabolomics

“…NAP performs in silico fragmentation-based metabolite predictions or annotations of candidate structures through searching several databases including GNPS, ChEBI (Chemical Entities of Biological Interest), SUPER NATURAL (II) and DNP. Therefore, using these two scoring methods, NAP is a beneficial tool when experimental spectra are matched to a few spectral libraries matches as it also allows the propagation of annotations in the absence and presence of library spectral matches (da Silva et al, 2018; Nephali et al, 2022; Kim et al, 2023). The The outputs of the NAP obtained in this study are reported in the supplementary material.…”

Charting the Cannabis plant chemical space with computational metabolomics

“…NAP performs in silico fragmentation-based metabolite predictions or annotations of candidate structures through searching several databases including GNPS, ChEBI (Chemical Entities of Biological Interest), SUPER NATURAL (II) and DNP. Therefore, using these two scoring methods, NAP is a beneficial tool when experimental spectra are matched to a few spectral libraries matches as it also allows the propagation of annotations in the absence and presence of library spectral matches (da Silva et al, 2018 ; Nephali et al, 2022 ; Kim et al, 2023 ). The outputs of NAP obtained in this study are reported in the supplementary material.…”