Revealing the impact of gut microbiota-derived metabolites on depression through network pharmacology

A total of 208 metabolites and 223 targets were initially extracted from the gutMGene v1.0 database. In addition, 1,630 and 1,321 targets were identified using the Similarity Ensemble Approach and Swiss Target Prediction databases, respectively, resulting in 921 overlapping targets. By integrating data from gutMGenev1.0, 13 core targets were finally identified. A microbiota-metabolite-target-signal pathway-disease network was constructed using Cytoscape 3.9.1, revealing 15 metabolites associated with the IL-17, TLR, and PI3K-Akt signalling pathways. Among these, five metabolites exhibited favourable drug similarity and acceptable toxicological profiles. Molecular docking confirmed the stable binding of two key metabolites-succinate and phenylacetylglutamine-to their respective targets. The results showed that succinate and phenylacetylglutamine demonstrated strong binding affinities to IL-1β and GSK3B, both involved in the IL-17, TLR, and PI3K-Akt signalling pathways. IL-17 and TLR4, as important pro-inflammatory cytokines, are closely associated with the development of depression, while the PI3K/AKT signalling pathway plays a key role in its pathogenesis. The present study reveals the potential mechanisms by which gut microbiota influence MDD and provides a scientific basis and a comprehensive research framework for future investigations.

Authors

Institutions

Publication Details

Journal
Artificial Cells Nanomedicine and Biotechnology
Published
2025-07-24
DOI
https://doi.org/10.1080/21691401.2025.2531752
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revealing the impact of gut microbiota-derived metabolites on depression through network pharmacology

Riga Wu, Rilebagen Hu, La Ta, A Ruhan et al.
Artificial Cells Nanomedicine and Biotechnology
Gut microbiota and health
article

Revealing the impact of gut microbiota-derived metabolites on depression through network pharmacology

Riga Wu, Rilebagen Hu, La Ta, A Ruhan, W. J. Huo, Jing Zhang, Lisi Wei, Li Li, Si Su, Lijun Tong, A Tengarile
article en

Abstract

A total of 208 metabolites and 223 targets were initially extracted from the gutMGene v1.0 database. In addition, 1,630 and 1,321 targets were identified using the Similarity Ensemble Approach and Swiss Target Prediction databases, respectively, resulting in 921 overlapping targets. By integrating data from gutMGenev1.0, 13 core targets were finally identified. A microbiota-metabolite-target-signal pathway-disease network was constructed using Cytoscape 3.9.1, revealing 15 metabolites associated with the IL-17, TLR, and PI3K-Akt signalling pathways. Among these, five metabolites exhibited favourable drug similarity and acceptable toxicological profiles. Molecular docking confirmed the stable binding of two key metabolites-succinate and phenylacetylglutamine-to their respective targets. The results showed that succinate and phenylacetylglutamine demonstrated strong binding affinities to IL-1β and GSK3B, both involved in the IL-17, TLR, and PI3K-Akt signalling pathways. IL-17 and TLR4, as important pro-inflammatory cytokines, are closely associated with the development of depression, while the PI3K/AKT signalling pathway plays a key role in its pathogenesis. The present study reveals the potential mechanisms by which gut microbiota influence MDD and provides a scientific basis and a comprehensive research framework for future investigations.

Artificial Cells Nanomedicine and BiotechnologyVol. 53(1)
Mongolian National University (MN), Inner Mongolia Medical University (CN)
Good health and well-being
Openalex Percentile: Top 84%
Gut microbiota and health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.