Abstract:

This study systematically investigated the bioactive components and established a quality control strategy for olive leaf extract in cosmetics by integrating network pharmacology with high-performance liquid chromatography （HPLC） analysis. Through a comprehensive literature review, 23 major chemical components were identified. Using the SwissTargetPrediction and TCMSP databases, 443 potential targets were predicted, while 543 targets related to soothing, redness reduction, and acne elimination efficacies were screened from databases such as Genecards. A Venn diagram analysis reveals 109 overlapping targets. Based on these data, a compound-target network and a protein-protein interaction （PPI） network were constructed, followed by GO functional and KEGG pathway enrichment analyses. Network topology analysis identifies 16 core targets, which are primarily involved in biological processes such as the cellular response to lipopolysaccharide and the TNF signaling pathway. By correlating component concentrations with target activities, five active components with high abundance and significant modulation of core targets were selected as candidate quality control markers: oleuropein, hydroxytyrosol, luteolin-7-O-glucoside, apigenin-7-O-glucoside, and verbascoside. An HPLC method was subsequently developed and applied to analyze commercial cosmetics. The results show that these five components generally exhibit stable co-occurrence characteristics （either all detected or all undetected）, indicating their reliability as quality control markers for determining the presence of olive leaf extract in cosmetics. Based on these findings, this study proposes a classification and evaluation standard according to the addition level of olive leaf extract: standard addition products require the detection of all five components, while trace addition products use oleuropein as the single evaluation indicator.

Key words: network pharmacology, olive leaf extract, cosmetics, quality control