Identification of Volatile Components in Leaves of Sapindus saponaria from Different Altitudes and Their Anti-inflammatory Mechanism Using Headspace-Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) and Network Pharmacology

Abstract

This research seeks to investigate how varying altitudes influence the volatile compounds present in the leaves of Sapindus saponaria, optimize the resource utilization of Sapindus saponaria leaves, and explore the anti-inflammatory properties and medicinal value of Sapindus saponaria leaves. A detailed investigation of the volatile compounds in Sapindus saponaria leaves across three different altitudes ranges led to the identification of 50 distinct compounds. Specifically, 29 were detected at low altitude (0-500 m), 43 at medium altitude (500-1000 m), and 28 at high altitude (1000-1500 m). The volatile components of the Sapindus saponaria leaves from different altitudes were clustered by Principal Coordinates Analyses (PCoA) and Orthogonal Partial Least Squares-Discriminant Analyses (OPLS-DA), and the components from three altitudes were successfully distinguished. The findings of the network pharmacology analysis indicated that, based on the common and differential volatile components of Sapindus saponaria leaves at low, medium, and high altitudes, 192, 39, 170, and 110 core targets were screened, respectively. Targets identified with great success via the PPI network included IL6, TNF, GAPDH, PTGS2, HSP90AA1, CASP1, STAT3, CASP3, MMP9, AKT1, EGFR, and MMP9. Molecular docking preliminarily validated these results from network pharmacology analysis. In this research, preliminary screening of the anti-inflammatory effects of shared and differential volatile constituents of Sapindus saponaria leaves at three altitudes showed that the best anti-inflammatory effect was observed at altitudes of 500 to 1,000 meters. Additionally, this work provides a theoretical foundation for further exploration of S. saponaria resources, helping to prevent resource wastage.