BACKGROUND Persea americana fruit (PAF) is a favorable nutraceutical resource that comprises diverse unsaturated fatty acids. Unsaturated fatty acids are of significance in dietary supplementation, as they relieve metabolic disorders, including obesity (OB). Unquestionably, a plethora of natural plants contain fatty acids like those found in PAF. This study focused on the anti-OB efficacy of the non-fatty acids in PAF using a network pharmacology approach. METHODS The chemical constituents of PAF were retrieved from the NPASS database and literature sources. The OB-related targets obtained by DisGeNET and the overlapping targets from the SEA and STP databases were analyzed with a Venn diagram to discover the crucial targets in OB. The crucial targets were analyzed via PPI and PSTC networks, the constructed bubble chart and molecular docking studies. Finally, the toxicities of the key compounds were identified by ProTox-II. RESULTS A total of 41 chemical compounds in PAF were identified by NPASS and other reports. The 31 overlapping targets were selected from the 52 intersecting targets and OB-related targets (3028) and were considered to be key protein encoding genes in OB, with AKT1 being the most significant among them. On the bubble chart, the PPAR signaling pathway had the highest rich factor and its modulation was determined to be the key mechanism, suggesting that this pathway may have an agonistic function for the treatment of OB. Likewise, the PSTC network showed that AKT1 had the greatest degree value. The MDA results showed that AKT1-γ-tocopherol, PPARA-fucosterol, PPARD-stigmasterol, PPARG-fucosterol, NR1H3-campesterol, and ILK-α-tocopherol formed the most stable complexes. These five key compounds were nontoxic, and could be developed as new antagonists to alleviate OB. CONCLUSION In summary, alpha-tocopherol, gamma-tocopherol, fucosterol, stigmasterol, and campesterol might be key players in the activation of the PPAR signaling pathway.
Background: Cornus kousa fruit (CKF) has been utilized as anti-obesity (AOB) supplementation in East Asia, including Korea, and gut microbiota (GM) might have positive effects on obesity (OB) via its interplay. We aimed to decode molecule(s), mechanism(s), and target(s) on interactive association between CKF and GM via network pharmacology (NP) analysis. The chemical constituents from ethanolic CKF (ECKF) were detected by Gas Chromatography-Mass Spectrometry (GC-MS). Results: The 31 compounds in ECKF were accepted by Lipinski’s rule and the overlapping targets (45) were identified by SEA and STP. The final targets (22) were selected on OB-responded targets, indicating that IL6 was the most crucial protein-coding target on PPI networks. A bubble plot and CKF, GM, signaling pathways, targets, and metabolites (CGSTM) networks suggested that AGE-RAGE signaling pathway in diabetic complications inhibited by CKF, and PPAR signaling pathway activated by GM. As the most stable conformers, the IL6-equol complex was attributed to GM, and PPARA-linoleic acid, PPARD-stearic acid, and FABP4-dimethyl 2,3-bis(1,3-dimethylindol-2-yl) fumarate complex were attributed to CKF. Noticeably, stearic acid was removed by Density Functional Theory (DFT) analysis, all other three molecules were proposed as good electron donators with the higher electronegativity, compared with a standard drug (Orlistat). Conclusion: This study shows that integrated pharmacological analysis can enable to decode the unknown relationships between CKF and GM. For the extensive viewpoints, our approach can obtain scientific evidence to verify the food-GM-host interactions by introducing several fields: bioinformatics, cheminformatics, pharmacology, microbiology, natural products chemistry, and quantum chemistry. Overall, this study reveals that the combination of CKF and favorable GM might exert dual therapeutic effects on OB.
Background: Persea americana fruit (PAF) is a favorable nutraceutical resource that comprises diverse unsaturated fatty acids. Unsaturated fatty acids are significant in dietary supplementation, as they relieve metabolic disorders, including obesity (OB). Unquestionably, a plethora of natural plants contain fatty acids found in PAF. This study focused on the anti-OB efficacy of the non-fatty acids in PAF using a network pharmacology approach. Results: A total of 41 chemical compounds in PAF were identified by NPASS and other reports. All 41 compounds conformed to Lipinski’s rule, and 52 intersecting targets were selected from the SEA and STP databases. Finally, 31 overlapping targets were selected from the 52 intersecting targets and OB-related targets (3028), which were considered as key proteins against OB, including AKT1 as the uppermost key target. On the bubble chart, the PPAR signaling pathway had the highest rich factor and its modulation was determined as the key mechanism, suggesting that this pathway may have an agonistic function in treating OB. The PFA-signaling pathways-targets-compounds (PSTC) network showed that AKT1 had the greatest degree value. The MDA results showed that AKT1-γ-tocopherol, PPARA-fucosterol, PPARD-stigmasterol, PPARG-fucosterol, NR1H3-campesterol, and ILK-α-tocopherol formed the most stable complexes. These five key compounds were nontoxic, and could be developed as new antagonists to alleviate OB. Conclusions: In summary, this study suggests that the non-fatty acids in PAF might play central roles in OB. Notably, alpha-tocopherol, gamma-tocopherol, fucosterol, stigmasterol, and campesterol might be key players in the activation on PPAR signaling pathway. However, the results of this study should be further investigated to determine the therapeutic value of these compounds.
Gleditsia sinensis Lam. (GSL) is a medicinal herb and a noticeable resource of possessing hepatic protective agents such as alcoholic liver disease (ALD). At present, it has been documented that gut microbiota (GM) is related directly to etiology of ALD. Nevertheless, the bioactive molecules in GSL, favorable GM, targets, and key mechanism(s) against ALD are yet to be revealed. Hence, we integrated the significant four components to clarify the nuanced pathogenesis with help of network pharmacology (NP) concept. We retrieved significant metabolites via gutMGene and constructed GSL or GM-Signaling pathways-Targets-Metabolites (GGSTM) networks. Finally, molecular docking test (MDT) was performed to verify the key findings. The gutMGene suggested that 16 GM and 6 metabolites were related to the two signaling pathways through GGSTM networks. Both MDT and frontier molecular orbitals (FMO) theory revealed the most stable conformers: equol from Lactobacillus paracasei JS1 on IL6, Bauer-7-en-3-one, and Urs-12-en-3-one from GSL on PPARA, PPARD, and PPARG, respectively. In conclusion, this study sheds light on the combinatorial effects of GM, and GSL in treating ALD via systems biology concept.
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