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

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.

Computational pharmacology profiling of borapetoside C against melanoma

Melanoma,also known as a 'black tumor', begins in the melanocytes when cells (that produce pigment) grows out of control. Immunological dysregulation, which raises the risk for multiple illnesses, including melanoma, may be influenced by stress tiggered through viral infection, long term effects of ultraviolet radiation, environmental pollutants etc. Borapetoside C is one of the phytoconstituents from Tinospora crispa, and its biological source has been reported for its antistress property. Network pharmacology and KEGG pathway analysis of borapetoside C-regulated proteins were conducted to identify the hub genes involved in melanoma development. Further, a molecular docking was performed between borapetoside C and targets involved in melanoma. Further, the top 3 complexes were selected based on the binding energy to conduct molecular dynamics simulations to evaluate the stability of ligand-protein complex followed by principal component analysis and dynamic cross-correlation matrix. In addition, borapetoside C was also screened for its pharmacokinetics and toxicity profile. Network Pharmacology studies and KEGG pathway analysis revealed 8 targets involved in melanoma. Molecular docking between borapetoside C and targets involved in melanoma identified 3 complexes with minimum binding i.e. borapetoside C- MAP2K1, MMP9, and EGFR. Further, molecular dynamics simulations showed a stable complex of borapetoside C with MMP9 and EGFR. The present study suggested that borapetoside C may target MMP9 and EGFR to possess an anti-melanoma property. This finding can be useful in developing a novel therapeutic agent against melanoma from a natural source.Communicated by Ramaswamy H. Sarma.

Guideline directed medical therapy induced nephrotoxicity in HFrEF patients; an insight to its mechanism

Guideline Directed Medical Therapy (GDMT) has been the standard pharmacotherapy for the treatment of Heart Failure patients with reduced Ejection Fraction (HFrEF) recommended by the European Society of Cardiology (ESC). However, patients on GDMT are likely to possess nephrotoxicity as an adverse effect. We utilized multiple system biology tools like ADVER-Pred, gene enrichment analysis, molecular docking, molecular dynamic simulations, and MMPBSA analysis to predict a possible molecular mechanism of how selected combinations of GDMT may cause nephrotoxicity. As per the ACC/AHA/ESC guidelines, we categorized the drugs as category 1 including β-blockers (BB), angiotensin receptor blockers (ARB), and sodium-glucose cotransporter-2 inhibitors (SGLT2I), category 2 includes BB's, SGLT2I, and angiotensin receptor-neprilysin inhibitors (ARNI), and category 3 includes BB's, SGLT2I, and angiotensin-converting enzyme (ACE) inhibitors. Enrichment analysis predicted category 2 drugs to possess the highest number of proteins to be involved in the development of nephrotoxicity i.e. 79.41%. The targets HBA1, CBR1, ATG5, and SLC6A3 were the top hub genes with an edge count of 7 followed by GPX1 with an edge count of 6. Molecular docking studies revealed candesartan-SLC6A3 to possess the highest binding affinity of -10.2 kcal/mol. In addition, simulation studies displayed empagliflozin-CBR1 to possess the highest stability followed by candesartan-ATG5. A combination of β-blockers, ARBs, and SGLT2I are predicted to likely possess nephrotoxicity which may be due to the modulation of HBA1, CBR1, ATG5, and GPX1. In conclusion, candesartan and empagliflozin are most likely to cause nephrotoxicity via the modulation of HBA1, CBR1, ATG5, and GPX1.Communicated by Ramaswamy H. Sarma.

Phytochemical composition, anti-microbial, anti-oxidant and anti-diabetic effects of Solanum elaeagnifolium Cav. leaves: in vitro and in silico assessments

The aim of this study was to screen the chemical components of Solanum elaeagnifolium leaves and assess their therapeutic attributes with regard to their antioxidant, antibacterial, and antidiabetic activities. The antidiabetic effects were explored to determine the α-amylase and α-glucosidase inhibitory potential of the leaf extract. To identify the active antidiabetic drugs from the extracts, the GC-MS-screened molecules were docked with diabetes-related proteins using the glide module in the Schrodinger Tool. In addition, molecular dynamics (MD) simulations were performed for 100 ns to evaluate the binding stability of the docked complex using the Desmond module. The ethyl acetate had a significant total phenolic content (TPC), with a value of 79.04 ± 0.98 mg/g GAE. The ethanol extract was tested for its minimum inhibitory concentration (MIC) for its bacteriostatic properties. It suppressed the growth of B. subtilis, E. coli, P. vulgaris, R. equi and S. epidermis at a dosage of 118.75 µg/mL. Moreover, the IC50 values of the ethanol extract were determined to be 17.78 ± 2.38 in the α-amylase and and 27.90 ± 5.02 µg/mL in α-glucosidase. The in-silico investigation revealed that cyclolaudenol achieved docking scores of -7.94 kcal/mol for α-amylase. Likewise, the α-tocopherol achieved the docking scores of -7.41 kcal/mol for glycogen phosphorylase B and -7.21 kcal/mol for phosphorylase kinase. In the MD simulations, the cyclolaudenol and α-tocopherol complexes exhibited consistently stable affinities with diabetic proteins throughout the trajectory. Based on these findings, we conclude that this plant could be a good source for the development of novel antioxidant, antibacterial, and antidiabetic agents.Communicated by Ramaswamy H. Sarma.

System biology mediated assessment of molecular mechanism for sinapic acid against breast cancer: via network pharmacology and molecular dynamic simulation

Sinapic acid is a hydroxycinnamic acid widespread in the plant kingdom, known to be a potent anti-oxidant used for the treatment of cancer, infections, oxidative stress, and inflammation. However, the mode of action for its chemotherapeutic properties has yet not been unleashed. Hence, we aimed to identify potential targets to propose a possible molecular mechanism for sinapic acid against breast cancer. We utilized multiple system biology tools and databases like DisGeNET, DIGEP-Pred, Cytoscape, STRING, AutoDock 4.2, AutoDock vina, Schrodinger, and gromacs to predict a probable molecular mechanism for sinapic acid against breast cancer. Targets for the disease breast cancer, were identified via DisGeNET database which were further matched with proteins predicted to be modulated by sinapic acid. In addition, KEGG pathway analysis was used to identify pathways; a protein-pathway network was constructed via Cytoscape. Molecular docking was performed using three different algorithms followed by molecular dynamic simulations and MMPBSA analysis. Moreover, cluster analysis and gene ontology (GO) analysis were performed. A total of 6776 targets were identified for breast cancer; 95.38% of genes predicted to be modulated by sinapic acid were common with genes of breast cancer. The 'Pathways in cancer' was predicted to be modulated by most umber of proteins. Further, PRKCA, CASP8, and CTNNB1 were predicted to be the top 3 hub genes. In addition, molecular docking studies revealed CYP3A4, CYP1A1, and SIRT1 to be the lead proteins identified from AutoDock 4.2, AutoDock Vina, and Schrodinger suite Glide respectively. Molecular dynamic simulation and MMPBSA were performed for the complex of sinapic acid with above mentioned proteins which revealed a stable complex throughout simulation. The predictions revealed that the mechanism of sinapic acid in breast cancer may be due to regulation of multiple proteins like CTNNB1, PRKCA, CASP8, SIRT1, and cytochrome enzymes (CYP1A1 & CYP3A4); the majorly regulated pathway was predicted to be 'Pathways in cancer'. This indicates the rationale for sinapic acid to be used in the treatment of breast cancer. However, these are predictions and need to be validated and looked upon in-depth to confirm the exact mechanism of sinapic acid in the treatment of breast cancer; this is future scope as well as a drawback of the current study.

Integrative bioinformatics analysis of biomarkers and pathways for exploring the mechanisms and molecular targets associated with pyroptosis in type 2 diabetes mellitus

Introduction

Research has shown that pyroptosis contributes greatly to the progression of diabetes and its complications. However, the exact relationship between this particular cell death process and the pathology of type 2 diabetes mellitus (T2DM) remains unclear. In this study, we used bioinformatic tools to identify the pyroptosis-related genes (PRGs) associated with T2DM and to analyze their roles in the disease pathology.

Methods

Two microarray datasets, GSE7014 and GSE25724, were obtained from the GEO database and assessed for differentially expressed genes (DEGs). The T2DM-associated DEGs that overlapped with differentially expressed PRGs were noted as T2DM-PRGs. Subsequently, 25 T2DM-PRGs were validated and subjected to functional enrichment analysis through Gene Ontology annotation analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and gene set enrichment analysis (GSEA). The diagnostic and predictive value of the T2DM-PRGs was evaluated using receiver operating characteristic curves (ROC). Additionally, a single-sample GSEA algorithm was applied to study immune infiltration in T2DM and assess immune infiltration levels.

Results

We identified 25 T2DM-PRGs that were significantly enriched in the nuclear factor-kappa B signaling and prostate cancer pathways. The top five differentially expressed prognostic T2DM-PRGs targeted by miRNAs were PTEN, BRD4, HSP90AB1, VIM, and PKN2. The top five differentially expressed T2DM-PRGs associated with transcription factors were HSP90AB1, VIM, PLCG1, SCAF11, and PTEN. The genes PLCG1, PTEN, TP63, CHI3L1, SDHB, DPP8, BCL2, SERPINB1, ACE2, DRD2, DDX58, and BTK showed excellent diagnostic performance. The immune infiltration analysis revealed notable differences in immune cells between T2DM and normal tissues in both datasets. These findings suggest that T2DM-PRGs play a crucial role in the development and progression of T2DM and could be used as potential diagnostic biomarkers and therapeutic targets.

Discussion

Investigating the mechanisms and biomarkers associated with pyroptosis may offer valuable insights into the pathophysiology of T2DM and lead to novel therapeutic approaches to treat the disease.

Selection of potential natural compounds for poly-ADP-ribose polymerase (PARP) inhibition in glioblastoma therapy by in silico screening methods

Glioblastoma (GBM), the most prevalent brain tumor, is one of the least treatable malignancies due to its propensity for intracranial spread, high proliferative potential, and innate resistance to radiation and chemotherapy. Current GBM therapy is limited due to unfavorable, non-specific therapeutic effects in healthy cells and the difficulty of small molecules to penetrate the blood brain barrier (BBB) and reach the tumor microenvironment. Adding PARP-1 inhibitors inhibit DNA repair enzymes thereby increasing the cytotoxicity of anticancer agents. Hence, we aimed to discover potential naturally occurring PARP-1 inhibitors that can be utilized in the treatment of glioma by using multiple in silico tools like molecular docking, absorption, distribution, metabolism, and excretion (ADME) profile, pharmacophore modeling, and molecular dynamic (MD) simulations. Among 43 phytocompounds we screened, two of them (Ellagic acid and Naringin) were discovered to be bound to the catalytic site of PARP-1 with an affinity more remarkable than commercially available PARP-1 inhibitors (Talazoparib, Niraparib, and Rucaparib) except Olaparib. The molecular interactions were analyzed, and data shows that bound entity attained a conserved domain via hydrogen bond interactions, polar interactions, and π-π stacking. Pharmacophore modeling studies showed electronic and steric features of ligands responsible for supramolecular interaction with PARP-1. ADME properties were studied, to assess drug-likeness, hydrophilic nature, hydrophobicity, brain permeability, and oral bioavailability of the natural PARP-1 inhibitors. The simulation study demonstrated the development of a stable complex between Naringin, Ellagic acid, and PARP-1 protein. Moreover, cell culture studies and animal investigations are essential to determine pharmacokinetics and pharmacodynamics.

Nuciferine improves random skin flap survival via TFEB-mediated activation of autophagy-lysosomal pathway

Due to their simplicity and reliability, random-pattern skin flaps are commonly utilized in surgical reconstruction to repair cutaneous wounds. However, the post-operative necrosis frequently happens because of the ischemia and high-level of oxidative stress of random skin flaps, which can severely affect the healing outcomes. Earlier evidence has shown promising effect of Nuciferine (NF) on preventing hydrogen peroxide (H₂O₂)-induced fibroblast senescence and ischemic injury, however, whether it can function on promoting ischemic flap survival remains unknown. In this work, using network pharmacology analysis, it was possible to anticipate the prospective targets of NF in the context of ischemia. The results revealed that NF treatment minimized H₂O₂-induced cellular dysfunction of human umbilical vein endothelial cells (HUVECs), and also improved flap survival through strengthening angiogenesis and alleviating oxidative stress, inflammation and apoptosis in vivo. These outcomes should be attributed to TFEB-mediated enhancement of autophagy-lysosomal degradation via the AMPK-mTOR signaling pathway, whilst the restriction of autophagy stimulation with 3MA effectively diminished the above advantages of NF treatment. The increased nuclear translocation of TFEB not only restored lysosome function, but also promoted autophagosome-lysosome fusion, eventually restoring the inhibited autophagic flux and filling the high energy levels. The outcomes of our research can provide potent proof for the application of NF in the therapy of vascular insufficiency associated disorders, including random flaps.

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

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.

In Silico Molecular Docking of Phytochemicals for Type 2 Diabetes Mellitus Therapy: A Network Pharmacology Approach

Identification of potential lead molecules in herbal medicines is crucial not only for validation but also for drug discovery. This study was focused on identifying the therapeutic mechanisms of 10 common herbs used to treat type 2 diabetes mellitus (T2DM) using network pharmacology and docking studies. Details pertaining to medicinal plants and their phytoconstituents were obtained from Indian Medicinal Plants, Phytochemistry, and Therapeutics and Dr. Duke's database, respectively. MolSoft was used to assess their drug likeness. Prediction of protein targets for the screened phytochemicals and the list of target genes involved in T2DM were obtained using Swiss TargetPrediction and GeneCards respectively. STRING; Cytoscape; Database for Annotation, Visualization, and Integrated Discovery; and PyRx were used for network construction, network analysis, gene ontology analysis, and molecular docking, respectively. The protein targets MAPK1, AKT1, PI3K, and EGFR were identified to play a crucial role in the progression of T2DM. Furthermore, molecular docking indicated that nimbaflavone exhibited high binding affinities for MAPK1 (-8.7 kcal/mole) and PI3K (-9.6 kcal/mole), whereas rutin and 10-hydroxyaloin-B showed high binding affinities for AKT1 (-7.4 kcal/mole) and EGFR (-8.1 kcal/mole), respectively. The findings from this study suggest that flavonoids are the major phytoconstituents that display antidiabetic activity by interacting with key protein molecules related to the MAPK and PI3K-AKT signaling pathways, thereby aiding in the treatment of T2DM. The activation of these pathways alters Ras-GTPase activity and enhances the expression of GLUT4, a glucose transporter, resulting in the uptake of glucose from the bloodstream.

Network Pharmacology- and Molecular Dynamics Simulation-Based Bioprospection of Aspalathus linearis for Type-2 Diabetes Care

The medicinal herb Aspalathus linearis (rooibos) is globally recognized in type-2 diabetes mellitus (T2DM) treatment due to its known and distinctive compounds. This work utilized network pharmacology (NP) coupled with molecular dynamics simulation in gaining new insight into the anti-diabetic molecular mechanism of action of rooibos teas. It looked at the interactions between rooibos constituents with various relevant protein receptors and signaling routes associated with T2DM progression. The initial analysis revealed 197 intersecting gene targets and 13 bioactive rooibos constituents linked to T2DM. The interactions between proteins and compounds to the target matrix were generated with the Cystoscope platform and STRING database. These analyses revealed intersecting nodes active in T2DM and hypoxia-inducible factor 1 (HIF-1) as an integral receptors target. In addition, KEGG analysis identified 11 other pathways besides the hub HIF-1 signaling route which may also be targeted in T2DM progression. In final molecular docking and dynamics simulation analysis, a significant binding affinity was confirmed for key compound-protein matrices. As such, the identified rooibos moieties could serve as putative drug candidates for T2DM control and therapy. This study shows rooibos constituents' interaction with T2DM-linked signaling pathways and target receptors and proposes vitexin, esculin and isovitexin as well as apigenin and kaempferol as respective pharmacologically active rooibos compounds for the modulation of EGFR and IGF1R in the HIF-1 signaling pathway to maintain normal homeostasis and function of the pancreas and pancreatic β-cells in diabetics.

Synthesis and antibacterial activity evaluation of N (7) position-modified balofloxacins

A series of small-molecule fluoroquinolones were synthesized, characterized by HRMS and NMR spectroscopy, and screened for their antibacterial activity against MRSA, P. aeruginosa, and E. coli as model G+/G− pathogens. Compounds 2-e, 3-e, and 4-e were more potent than the reference drug balofloxacin against MRSA and P. aeruginosa (MIC values of 0.0195 and 0.039 μg/ml for 2-e, 0.039 and 0.078 μg/ml for each of 3-e and 4-e, respectively). Analysis of the time-dependent antibacterial effect of compound 2-e toward MRSA showed that in the early logarithmic growth phase, bactericidal effects occurred, while in the late logarithmic growth phase, bacterial inhibition occurred because of concentration effects and possibly the development of drug resistance. Compound 2-e exhibited low toxicity toward normal mammalian cell lines 3T3 and L-02 and tumor cell lines A549, H520, BEL-7402, and MCF-7. The compound was not hemolytic. Atomic force microscopy (AFM) revealed that compound 2-e could effectively destroy the membrane and wall of MRSA cells, resulting in the outflow of the cellular contents. Docking studies indicated the good binding profile of these compounds toward DNA gyrase and topoisomerase IV. ADMET’s prediction showed that most of the synthesized compounds followed Lipinski’s “rule of five” and possessed good drug-like properties. Our data suggested that compound 2-e exhibited potent anti-MRSA activity and is worthy of further investigation.

Ficus benghalensis promotes the glucose uptake- Evidence with in silico and in vitro

Background

Ficus benghalensis L. is traditionally used to manage diabetes; also used in various herbal formulations, and is indicated as an insulin sensitizer. Hence, present work attempted in identifying the probable lead hits to promote glucose uptake via computational approach followed by experimental evaluation of hydroalcoholic extract of Ficus benghalensis L. bark in yeast cells.

Methods

The in vitro assay for glucose uptake was performed in the baker yeast whereas in-silico study involved retrieving the phytoconstituents from open sources, and predicting for probable targets of diabetes followed by drug-likeness score, probable side effects, and ADMET profile. Homology modeling was performed to construct the target protein glucose transporter-2. In addition, the binding affinity of each ligand with glucose transporter was predicted using AutoDock 4.2.

Results

A total of 17 phytoconstituents from F. benghalensis were identified to possess the anti-diabetic effects. Among them, 4-methoxybenzoic acid scored the highest drug-likeness score and lupeol acetate had the maximum binding affinity of -8.02 kcal/mol with 9 pi-interactions via Tyr324, Phe323, Ile319, Ile200, Ile28, Phe24, and Ala451. Similarly, the extract showed the highest glucose uptake efficacy in yeast cells at 500 µg/mL.

Conclusion

Herein the present study reflected the probable activity of the phytoconstituents from F. benghalensis in promoting the glucose uptake via the in silico and in vitro approaches.