Exploring the therapeutic mechanisms of Cassia glauca in diabetes mellitus through network pharmacology, molecular docking and molecular dynamics

Cassia glauca is reported as anti-diabetic medicinal plant and is also used as an ethnomedicine. However, its mode of action as an anti-diabetic agent has not been clearly elucidated. Hence, the present study investigated the probable mechanism of action of C. glauca to manage diabetes mellitus via network pharmacology and molecular docking and simulations studies. The reported bioactives from C. glauca were retrieved from an open-source database, i.e. ChEBI, and their targets were predicted using SwissTargetPrediction. The proteins involved in the pathogenesis of diabetes were identified from the therapeutic target database. The targets involved in diabetes were enriched in STRING, and the pathways involved in diabetes were identified concerning the KEGG. Cytoscape was used to construct the network among bioactives, proteins, and probably regulated pathways, which were analyzed based on edge count. Similarly, molecular docking was performed using the Glide module of the Schrodinger suite against majorly targeted proteins with their respective ligands. Additionally, the drug-likeness score and ADMET profile of the individual bioactives were predicted using MolSoft and admetSAR2.0 respectively. The stability of these complexes were further studied via molecular dynamics simulations and binding energy calculations. Twenty-three bio-actives were retrieved from the ChEBI database in which cassiarin B was predicted to modulate the highest number of proteins involved in diabetes mellitus. Similarly, GO analysis identified the PI3K-Akt signaling pathway to be primarily regulated by modulating the highest number of gene. Likewise, aldose reductase (AKR1B1) was majorly targeted via the bioactives of C. glauca. Similarly, docking study revealed methyl-3,5-di-O-caffeoylquinate (docking score −9.209) to possess the highest binding affinity with AKR1B1. Additionally, drug-likeness prediction identified cassiaoccidentalin B to possess the highest drug-likeness score, i.e. 0.84. The molecular dynamics simulations and the MMGBSA indicate high stability and greater binding energy for the methyl-3,5-di-O-caffeoylquinate (ΔGbind = −40.33 ± 6.69 kcal mol−1) with AKR1B1, thus complementing results from other experiments. The study identified cassiarin B, cassiaoccidentalin B, and cinnamtannin A2 as lead hits for the anti-diabetic activity of C. glauca. Further, the PI3K-Akt and AKR1B1 were traced as majorly modulated pathway and target, respectively

Barosmin against postprandial hyperglycemia: outputs from computational prediction to functional responses in vitro

Previously, barosmin has been demonstrated to possess anti-diabetic action. However, its effect to inhibit α-amylase and α-glucosidase, including glucose utilization efficacy, has yet to be revealed. Hence, the current study attempted to assess the efficiency of barosmin in inhibiting the α-amylase, α -glucosidase, and dipeptidyl peptidase 4 enzymes, including glucose uptake efficacy. Molecular docking and simulation were performed using AutoDock Vina and Gromacs respectively followed by gene ontology analysis using the database for annotation, visualization, and integrated discovery. Further, in vitro enzyme inhibitory activities and glucose uptake assay were performed in L6 cell lines. Density functional theory analysis detailed mechanistic insights into the crucial interaction sites of barosmin of which the electron-dense region was prone to nucleophilic attack (O-atoms) whereas hydroxyl groups (-OH) showed affinity for electrophilic attacks. Barosmin showed good binding affinity with α-amylase (-9.2 kcal/mol), α-glucosidase (-10.7 kcal/mol), and dipeptidyl peptidase 4 (-10.0 kcal/mol). Barosmin formed stable nonbonded contacts with active site residues of aforementioned enzymes throughout 200 ns molecular dynamics simulation. Further, it regulated pathway concerned with glucose homeostasis i.e. tumor necrosis factor signaling pathway. In addition, barosmin showed α-amylase (IC50= 95.77 ± 23.33 µg/mL), α-glucosidase (IC50= 68.13 ± 2.95 µg/mL), and dipeptidyl peptidase 4 (IC50= 13.27 ± 1.99 µg/mL) inhibitory activities including glucose uptake efficacy in L6 cell lines (EC50= 12.46 ± 0.90 µg/mL) in the presence of insulin. This study presents the efficacy of the barosmin to inhibit α-amylase and α-glucosidase and glucose uptake efficacy in L6 cell lines via the use of multiple system biology tools and in vitro techniques. Communicated by Ramaswamy H. Sarma</p

DataSheet1_Systems and in vitro pharmacology profiling of diosgenin against breast cancer.ZIP

Aim: The purpose of this study was to establish a mode of action for diosgenin against breast cancer employing a range of system biology tools and to corroborate its results with experimental facts.Methodology: The diosgenin-regulated domains implicated in breast cancer were enriched in the Kyoto Encyclopedia of Genes and Genomes database to establish diosgenin-protein(s)-pathway(s) associations. Later, molecular docking and the lead complexes were considered for molecular dynamics simulations, MMPBSA, principal component, and dynamics cross-correlation matrix analysis using GROMACS v2021. Furthermore, survival analysis was carried out for the diosgenin-regulated proteins that were anticipated to be involved in breast cancer. For gene expression analyses, the top three targets with the highest binding affinity for diosgenin and tumor expression were examined. Furthermore, the effect of diosgenin on cell proliferation, cytotoxicity, and the partial Warburg effect was tested to validate the computational findings using functional outputs of the lead targets.Results: The protein-protein interaction had 57 edges, an average node degree of 5.43, and a p-value of 3.83e-14. Furthermore, enrichment analysis showed 36 KEGG pathways, 12 cellular components, 27 molecular functions, and 307 biological processes. In network analysis, three hub proteins were notably modulated: IGF1R, MDM2, and SRC, diosgenin with the highest binding affinity with IGF1R (binding energy −8.6 kcal/mol). Furthermore, during the 150 ns molecular dynamics (MD) projection run, diosgenin exhibited robust intermolecular interactions and had the least free binding energy with IGF1R (−35.143 kcal/mol) compared to MDM2 (−34.619 kcal/mol), and SRC (-17.944 kcal/mol). Diosgenin exhibited the highest cytotoxicity against MCF7 cell lines (IC50 12.05 ± 1.33) µg/ml. Furthermore, in H2O2-induced oxidative stress, the inhibitory constant (IC50 7.68 ± 0.51) µg/ml of diosgenin was lowest in MCF7 cell lines. However, the reversal of the Warburg effect by diosgenin seemed to be maximum in non-cancer Vero cell lines (EC50 15.27 ± 0.95) µg/ml compared to the rest. Furthermore, diosgenin inhibited cell proliferation in SKBR3 cell lines more though.Conclusion: The current study demonstrated that diosgenin impacts a series of signaling pathways, involved in the advancement of breast cancer, including FoxO, PI3K-Akt, p53, Ras, and MAPK signaling. Additionally, diosgenin established a persistent diosgenin-protein complex and had a significant binding affinity towards IGF1R, MDM2, and SRC. It is possible that this slowed down cell growth, countered the Warburg phenomenon, and showed the cytotoxicity towards breast cancer cells.</p