Background: Diabetes mellitus is one of the most common endocrine metabolic disorder-
related diseases. The application of herbal medicine to control glucose levels and improve insulin
action might be a useful approach in the treatment of diabetes. Mulberry leaves (ML) have
been reported to exert important activities of anti-diabetic.
Objective: In this work, we aimed to explore the multi-targets and multi-pathways regulatory
molecular mechanism of Mulberry leaves (ML, Morus alba Linne) acting on diabetes.
Methods: Identification of active compounds of Mulberry leaves using Traditional Chinese
Medicine Systems Pharmacology (TCMSP) database was carried out. Bioactive components were
screened by FAF-Drugs4 website (Free ADME-Tox Filtering Tool). The targets of bioactive components
were predicted from SwissTargetPrediction website, and the diabetes related targets were
screened from GeneCards database. The common targets of ML and diabetes were used for Gene
Ontology (GO) and pathway enrichment analysis. The visualization networks were constructed by
Cytoscape 3.7.1 software. The biological networks were constructed to analyze the mechanisms as
follows: (1) compound-target network; (2) common target-compound network; (3) common targets
protein interaction network; (4) compound-diabetes protein-protein interactions (ppi) network; (5)
target-pathway network; and (6) compound-target-pathway network. At last, the prediction results
of network pharmacology were verified by molecular docking method.
Results: 17 active components were obtained by TCMSP database and FAF-Drugs4 website. 51 potential
targets (11 common targets and 40 associated indirect targets) were obtained and used to
build the PPI network by the String database. Furthermore, the potential targets were used for GO
and pathway enrichment analysis. Eight key active compounds (quercetin, Iristectorigenin A, 4-
Prenylresveratrol, Moracin H, Moracin C, Isoramanone, Moracin E and Moracin D) and 8 key targets
(AKT1, IGF1R, EIF2AK3, PPARG, AGTR1, PPARA, PTPN1 and PIK3R1) were obtained to
play major roles in Mulberry leaf acting on diabetes. And the signal pathways involved in the mechanisms
mainly include AMPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling
pathway, insulin signaling pathway and insulin resistance. The molecular docking results show that
the 8 key active compounds have good affinity with the key target of AKT1, and the 5 key targets
(IGF1R, EIF2AK3, PPARG, PPARA and PTPN1) have better affinity than AKT1 with the key
compound of quercetin.
Conclusion: Based on network pharmacology and molecular docking, this study provided an important
systematic and visualized basis for further understanding of the synergy mechanism of ML
acting on diabetes.