Author: Oh, Ki Kwang; Adnan, Md.; Cho, Dong Ha
                    Title: Network pharmacology of bioactives from Sorghum bicolor with targets related to diabetes mellitus  Cord-id: nrloatn6  Document date: 2020_12_31
                    ID: nrloatn6
                    
                    Snippet: BACKGROUND: Sorghum bicolor (SB) is rich in protective phytoconstituents with health benefits and regarded as a promising source of natural anti-diabetic substance. However, its comprehensive bioactive compound(s) and mechanism(s) against type-2 diabetes mellitus (T2DM) have not been exposed. Hence, we implemented network pharmacology to identify its key compounds and mechanism(s) against T2DM. METHODS: Compounds in SB were explored through GC-MS and screened by Lipinski’s rule. Genes associat
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: BACKGROUND: Sorghum bicolor (SB) is rich in protective phytoconstituents with health benefits and regarded as a promising source of natural anti-diabetic substance. However, its comprehensive bioactive compound(s) and mechanism(s) against type-2 diabetes mellitus (T2DM) have not been exposed. Hence, we implemented network pharmacology to identify its key compounds and mechanism(s) against T2DM. METHODS: Compounds in SB were explored through GC-MS and screened by Lipinski’s rule. Genes associated with the selected compounds or T2DM were extracted from public databases, and the overlapping genes between SB-compound related genes and T2DM target genes were identified using Venn diagram. Then, the networking between selected compounds and overlapping genes was constructed, visualized, and analyzed by RStudio. Finally, affinity between compounds and genes was evaluated via molecular docking. RESULTS: GC-MS analysis of SB detected a total of 20 compounds which were accepted by the Lipinski’s rule. A total number of 16 compounds-related genes and T2DM-related genes (4,763) were identified, and 81 overlapping genes between them were selected. Gene set enrichment analysis exhibited that the mechanisms of SB against T2DM were associated with 12 signaling pathways, and the key mechanism might be to control blood glucose level by activating PPAR signaling pathway. Furthermore, the highest affinities were noted between four main compounds and six genes (FABP3-Propyleneglyco monoleate, FABP4-25-Oxo-27-norcholesterol, NR1H3-Campesterol, PPARA-β-sitosterol, PPARD-β-sitosterol, and PPARG-β-sitosterol). CONCLUSION: Our study overall suggests that the four key compounds detected in SB might ameliorate T2DM severity by activating the PPAR signaling pathway.
 
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