# Exploration of Potential Antidepressant Active Ingredients of Albiziae Flos via HS–GC–MS, Chemometrics, and Network Pharmacology

## TL;DR

This study explores the antidepressant properties of Albiziae Flos using advanced analytical and pharmacological methods to identify active compounds and their mechanisms.

## Contribution

The study introduces a novel integrated approach combining HS–GC–MS, chemometrics, and network pharmacology to evaluate AF's volatile components and antidepressant mechanisms.

## Key findings

- Identified 34 volatile compounds in Albiziae Flos with high consistency across 16 batches.
- Network pharmacology revealed 15 active components and 131 potential targets linked to antidepressant effects.
- Molecular docking showed strong binding affinity between linalool oxide and core targets via hydrogen and hydrophobic interactions.

## 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.