ArticlePloS one2020
Network pharmacology of bioactives from Sorghum bicolor with targets related to diabetes mellitus.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 48 citations in OpenAlex.
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- Metabolomics-based profiling of 4 avocado varieties using HPLC-MS/MS and GC/MS and evaluation of their antidiabetic activity.Scientific reports · 2022Article
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- Integrating experimental model, LC-MS/MS chemical analysis, and systems biology approach to investigate the possible antidiabetic effect and mechanisms ofFrontiers in pharmacology · 2022Article
- Antidiabetic Effect ofFrontiers in pharmacology · 2022Article
- Mechanisms of Rhizoma Coptidis against type 2 diabetes mellitus explored by network pharmacology combined with molecular docking and experimental validation.Scientific reports · 2021Article
- Network Pharmacology-Based Study to Uncover Potential Pharmacological Mechanisms of Korean Thistle (Molecules (Basel, Switzerland) · 2021Article
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- Network pharmacology approach to decipher signaling pathways associated with target proteins of NSAIDs against COVID-19.Scientific reports · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSorghum 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.
methodsCompounds 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.
resultsGC-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).
conclusionOur 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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