Investigating the Mechanisms of <i>Lycii fructus</i> in Treating Nonalcoholic Fatty Liver Disease and Diabetes Comorbidity Through Network Pharmacology and Molecular Dynamics

Non-alcoholic fatty liver disease (NAFLD) and diabetes mellitus (DM) are prevalent metabolic disorders that frequently coexist, yet their shared molecular mechanisms remain poorly understood, and current therapies often yield suboptimal outcomes. <i>Lycium barbarum</i> L. (<i>Lycii fructus</i>, LF), a traditional medicinal herb, has demonstrated clinical efficacy in treating both conditions, but its mechanism of action in comorbidity management remains unclear. Active LF compounds were identified via the TCMSP database, with potential targets predicted using Swiss Target Prediction and PharmMapper. Disease-associated proteins for NAFLD and DM were curated from OMIM, GeneCards, DisGeNET, UniProt, DrugBank, and TTD. A protein-protein interaction (PPI) network was constructed from these targets, and GO and KEGG pathway analyses were performed using the DAVID platform. Key targets were further refined through network module analysis via Metascape. Drug-likeness of bioactive compounds was assessed using SwissADME and ADMETlab 2.0. Molecular docking and dynamics simulations validated interactions between core targets and LF compounds. Mendelian randomization (MR) analysis tested causal relationships between core genes and disease phenotypes. We identified 58 shared therapeutic targets for NAFLD-DM comorbidity, including HSP90AA1, ESR1, MMP9, EGFR, AKT1, and CASP3. GO analysis implicated LF in blood pressure regulation and glucose-stimulated insulin secretion. KEGG pathways highlighted modulation of MAPK, PI3K-Akt, FoxO, and mTOR signaling. 24-methylenelanost-8-enol and cryptoxanthin monoepoxide emerged as core bioactive compounds with favorable drug-likeness. Molecular docking confirmed strong binding of 24-methylenelanost-8-enol to HSP90AA1 and cryptoxanthin monoepoxide to MMP9, further supported by dynamics simulations. MR analysis revealed a significant causal role for CASP3 in both NAFLD and DM, aligning with network pharmacology predictions. LF's therapeutic effects on NAFLD-DM comorbidity likely arise from terpenoid and cryptoxanthin mediated modulation of apoptosis and inflammation pathway. This study identifies shared molecular networks, proposes candidate mechanisms for LF's efficacy, and provides a framework for targeting multifactorial metabolic diseases.

Authors

Institutions

Publication Details

Journal
Food Science & Nutrition
Published
2025-05-26
DOI
https://doi.org/10.1002/fsn3.70256
Citations
1
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the Mechanisms of Lycii fructus in Treating Nonalcoholic Fatty Liver Disease and Diabetes Comorbidity Through Network Pharmacology and Molecular Dynamics

Xiujing Li, Yiming Zhang, Jiahui Song, Peng Sun et al.
1 citations
Food Science & Nutrition
Liver Disease Diagnosis and Treatment
1.35
article

Investigating the Mechanisms of Lycii fructus in Treating Nonalcoholic Fatty Liver Disease and Diabetes Comorbidity Through Network Pharmacology and Molecular Dynamics

Xiujing Li, Yiming Zhang, Jiahui Song, Peng Sun, Yuxing Zhou, Wei Gong, Yang Liu
article en
1 citations

Abstract

Non-alcoholic fatty liver disease (NAFLD) and diabetes mellitus (DM) are prevalent metabolic disorders that frequently coexist, yet their shared molecular mechanisms remain poorly understood, and current therapies often yield suboptimal outcomes. <i>Lycium barbarum</i> L. (<i>Lycii fructus</i>, LF), a traditional medicinal herb, has demonstrated clinical efficacy in treating both conditions, but its mechanism of action in comorbidity management remains unclear. Active LF compounds were identified via the TCMSP database, with potential targets predicted using Swiss Target Prediction and PharmMapper. Disease-associated proteins for NAFLD and DM were curated from OMIM, GeneCards, DisGeNET, UniProt, DrugBank, and TTD. A protein-protein interaction (PPI) network was constructed from these targets, and GO and KEGG pathway analyses were performed using the DAVID platform. Key targets were further refined through network module analysis via Metascape. Drug-likeness of bioactive compounds was assessed using SwissADME and ADMETlab 2.0. Molecular docking and dynamics simulations validated interactions between core targets and LF compounds. Mendelian randomization (MR) analysis tested causal relationships between core genes and disease phenotypes. We identified 58 shared therapeutic targets for NAFLD-DM comorbidity, including HSP90AA1, ESR1, MMP9, EGFR, AKT1, and CASP3. GO analysis implicated LF in blood pressure regulation and glucose-stimulated insulin secretion. KEGG pathways highlighted modulation of MAPK, PI3K-Akt, FoxO, and mTOR signaling. 24-methylenelanost-8-enol and cryptoxanthin monoepoxide emerged as core bioactive compounds with favorable drug-likeness. Molecular docking confirmed strong binding of 24-methylenelanost-8-enol to HSP90AA1 and cryptoxanthin monoepoxide to MMP9, further supported by dynamics simulations. MR analysis revealed a significant causal role for CASP3 in both NAFLD and DM, aligning with network pharmacology predictions. LF's therapeutic effects on NAFLD-DM comorbidity likely arise from terpenoid and cryptoxanthin mediated modulation of apoptosis and inflammation pathway. This study identifies shared molecular networks, proposes candidate mechanisms for LF's efficacy, and provides a framework for targeting multifactorial metabolic diseases.

Food Science & NutritionVol. 13(6)
Ningxia Seismological Bureau (CN), Ningxia Medical University (CN), The Fourth People's Hospital of Ningxia Hui Autonomous Region (CN)
Ningxia Medical University
Good health and well-being
Openalex Percentile: Top 19%
Liver Disease Diagnosis and Treatment
1.35
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.