MedicineChemistry

Dan Yang, Dan He, Yiwu Wang, Yuan Shen, Jialing Yu, Ruijia Yang, Lin Yang

2026.1.1Journal of Analytical Methods in Chemistry

DOI: 10.1155/jamc/2885034

tlooto Summary

This study presented an integrated approach combining headspace-gas chromatography-mass spectrometry, chemometrics, and network pharmacology to comprehensively evaluate the volatile components of AF and explore their potential antidepressant mechanisms.

Abstract

Albiziae Flos (AF) is a traditional Chinese medicine with an extensive historical background. This study presented an integrated approach combining headspace-gas chromatography-mass spectrometry (HS-GC-MS), chemometrics, and network pharmacology to comprehensively evaluate the volatile components of AF and explore their potential antidepressant mechanisms. A total of 34 volatile compounds were identified through HS-GC-MS analysis. Fingerprint assessment revealed high consistency among 16 batches (similarity: 0.790-0.998), while chemometric analysis successfully discriminated samples from different geographical origins. Network pharmacology screening identified 15 active components and 131 potential targets, revealing multicomponent, multitarget characteristics of AF's antidepressant effects. Molecular docking simulations demonstrated strong binding affinity between linalool oxide configurations and 12 core targets, primarily through hydrogen bonding and hydrophobic interactions. This work lies in its comprehensive investigation of AF's volatile components using an integrated analytical-pharmacological approach, providing both a methodological framework for quality assessment and mechanistic insights for antidepressant drug development. Our findings established scientific foundations for quality control of AF and revealed its potential antidepressant mechanisms through multiple pathways.

Citation format

YANG, Dan, et al. Exploration of potential antidepressant active ingredients of albiziae flos via HS-GC-MS, chemometrics, and network pharmacology. Journal of Analytical Methods in Chemistry, 2026, 2026(1): 2885034.