Systems Pharmacology Investigation of Phytochemicals From Scilla peruviana L.: Integrated Gas Chromatography–Mass Spectrometry Profiling, Network Pharmacology, and Molecular Docking Reveal Potential Anti‐Inflammatory Mechanisms
4 affiliations
- 1Department of Microbial Biotechnology Faculty of Natural and Life Science University of Blida 1 Blida Algeria
- 2Laboratory of Biological Engineering, Valorization and Innovation of Agri‐Food Products University of Larbi Ben M’hidi Oum El Bouaghi Algeria
- 3Research Unit of Environmental and Structural Molecular Chemistry University of Constantine (Mentouri) Constantine Algeria
- 4Department of Chemistry and Technologies of Drug Sapienza University Rome Italy
Abstract
This study aimed to characterize the volatile and fatty acid constituents of S. peruviana and investigate their potential anti‐inflammatory mechanisms. Volatile compounds were identified by headspace solid‐phase microextraction coupled with gas chromatography–mass spectrometry (HS‐SPME‐GC–MS), whereas fatty acids were analyzed by GC–MS following derivatization. The identified phytochemicals were subjected to target prediction, followed by protein–protein interaction (PPI), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking. HS‐SPME‐GC–MS analysis identified 11 volatile compounds, predominantly hexahydrofarnesyl acetone (48.4%) and dihydroactinidiolide (23.5%), followed by dehydro‐β‐ionone (5.6%), 2‐methylbutanal (5.5%), and 3‐methylbutanal (5.1%). Fatty acid profiling revealed palmitic acid as the predominant fatty acid (47.7%), followed by α‐linolenic acid (29.9%), linoleic acid (11.6%), and stearic acid (10.8%). Network pharmacology identified 253 overlapping targets between phytochemical‐associated proteins and inflammation‐related genes, with TNF, IL1B, PTGS2, EGFR, STAT3, and PPARG emerging as the principal hub proteins. KEGG enrichment analysis revealed significant enrichment in inflammation‐associated pathways, including NF‐κB, IL‐17, NOD‐like receptor, and advanced glycation end‐products (AGE)‐receptor for advanced glycation end‐products (RAGE) signaling pathways. Molecular docking predicted interactions between the major phytochemicals and the selected targets, with palmitic acid showing the lowest predicted binding energy for COX‐2 (−7.0 kcal/mol), while hexahydrofarnesyl acetone and stearic acid showed the lowest predicted binding energies for PPARγ (−8.3 kcal/mol).
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BibTeX
@article{zatout2026systems,
title = {{Systems Pharmacology Investigation of Phytochemicals From Scilla peruviana L.: Integrated Gas Chromatography–Mass Spectrometry Profiling, Network Pharmacology, and Molecular Docking Reveal Potential Anti‐Inflammatory Mechanisms}},
author = {Roukia Zatout and Ouided Benslama and Stefania Garzoli},
journal = {ChemistryOpen},
year = {2026},
month = oct,
doi = {10.1002/open.70320},
url = {https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/open.70320},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Systems Pharmacology Investigation of Phytochemicals From Scilla peruviana L.: Integrated Gas Chromatography–Mass Spectrometry Profiling, Network Pharmacology, and Molecular Docking Reveal Potential Anti‐Inflammatory Mechanisms
AU - Roukia Zatout
AU - Ouided Benslama
AU - Stefania Garzoli
PY - 2026
DA - 2026/10/21
JO - ChemistryOpen
DO - 10.1002/open.70320
UR - https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/open.70320
AB - This study aimed to characterize the volatile and fatty acid constituents of S. peruviana and investigate their potential anti‐inflammatory mechanisms. Volatile compounds were identified by headspace solid‐phase microextraction coupled with gas chromatography–mass spectrometry (HS‐SPME‐GC–MS), whereas fatty acids were analyzed by GC–MS following derivatization. The identified phytochemicals were subjected to target prediction, followed by protein–protein interaction (PPI), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking. HS‐SPME‐GC–MS analysis identified 11 volatile compounds, predominantly hexahydrofarnesyl acetone (48.4%) and dihydroactinidiolide (23.5%), followed by dehydro‐β‐ionone (5.6%), 2‐methylbutanal (5.5%), and 3‐methylbutanal (5.1%). Fatty acid profiling revealed palmitic acid as the predominant fatty acid (47.7%), followed by α‐linolenic acid (29.9%), linoleic acid (11.6%), and stearic acid (10.8%). Network pharmacology identified 253 overlapping targets between phytochemical‐associated proteins and inflammation‐related genes, with TNF, IL1B, PTGS2, EGFR, STAT3, and PPARG emerging as the principal hub proteins. KEGG enrichment analysis revealed significant enrichment in inflammation‐associated pathways, including NF‐κB, IL‐17, NOD‐like receptor, and advanced glycation end‐products (AGE)‐receptor for advanced glycation end‐products (RAGE) signaling pathways. Molecular docking predicted interactions between the major phytochemicals and the selected targets, with palmitic acid showing the lowest predicted binding energy for COX‐2 (−7.0 kcal/mol), while hexahydrofarnesyl acetone and stearic acid showed the lowest predicted binding energies for PPARγ (−8.3 kcal/mol).
SN - 2191-1363
SN - 2191-1363
ER -