Evaluating the in vitro anti-diabetic activity of Bryonia dioica root extracts supported by molecular docking analysis

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Evaluating the in vitro anti-diabetic activity of Bryonia dioica root extracts supported by molecular docking analysis

ReferencesShowing 10 of 42 papers
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Ethnobotanical study of medicinal plants used by traditional healers in Mascara (North West of Algeria)
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The Synergistic Influence of Polyflavonoids from Citrus aurantifolia on Diabetes Treatment and Their Modulation of the PI3K/AKT/FOXO1 Signaling Pathways: Molecular Docking Analyses and In Vivo Investigations
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Experimental and computational approaches to reveal the potential of Ficus deltoidea leaves extract as α-amylase inhibitor
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Vitexin isolated from Acanthus ilicifolius L. leaf enhances GLUT-4 translocation in experimental diabetic rats
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Novel α-amylase and α-glucosidase inhibitors from selected Nigerian antidiabetic plants: an in silico approach
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Molecular Docking and Pharmacokinetic Prediction of Potential Compounds from Luffa acutangula as Antidiabetic Candidates
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Cucurbitane-type compounds from Momordica charantia: Isolation, in vitro antidiabetic, anti-inflammatory activities and in silico modeling approaches
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COVID-19 has caused a severe impact on global health. Several studies have reported the use of Vitamin D in the management of COVID-19 illness; however, the molecular basis of its action is not clear. This draws an interest to understand the molecular insights of binding of vitamin D and its analogues with ACE2 (angiotensin-converting enzyme 2) and VDR (vitamin D receptor) using molecular docking analysis. Here, we have documented the molecular docking and simulation analysis of the binding interactions of seocalcitol with ACE2 and VDR for further consideration in managing COVID-19.

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Antidiarrheal Activity of the Ethanolic Extract of Operculina turpethum Stem and in silico Molecular Docking and ADMET Analysis of Its Isolated Compounds
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Background: Operculina turpethum (OT) is widely known for its use in traditional treatment practices to heal several diseases, such as bronchitis, pectoralgia, arthralgia, diarrhea, obesity, helminthiasis, gastropathy, ascites, sporadic fever, leucoderma, inflammation, pruritis, ulcers, erysipelas, tumors, jaundice, hemorrhoids, ophthalmia, etc. In this report, the antidiarrheal potential of the O. turpethum (EEOT) stem was assessed in an animal model along with a molecular docking study of previously isolated compounds to determine the mechanism involved in identifying prospective phytocompounds against diarrhea. Methods: Ethanolic stem extract was used in a mouse model of castor oil-induced in vivo antidiarrheal syndrome. In silico molecular docking analysis was performed using the ‘Vina Wizard’ program in PyRx – Python Prescription 0.8. Results: At 250 and 500 mg/kg, the EEOT stem dose-dependently demonstrated significant differences in antidiarrheal potential. During molecular docking analysis, out of four previously isolated compounds from O. turpethum stem, three (22,23-dihydro-α-spinosterol-ß-D-glucoside, 3-(4-hydroxy-phenyl)-N-[2-(4-hydroxy phenyl)-ethyl]-acrylamide and β-sitosterol-β-D-glucoside) have shown satisfactory binding affinity against the target M3 muscarinic acetylcholine receptor compared with the reference standard drug loperamide. Conclusion: The EEOT stem has significant potential to prevent diarrhea, which can be rationalized by molecular docking analysis, in which secondary plant metabolites were found to bind promisingly to their target receptor.

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Molecular Docking Analysis for Screening of Cyclooxygenase-2 Inhibitors from Secondary Metabolite Compounds of Lactococcus lactis subsp. lactis (Lac3)
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Inflammatory response plays important roles in both tumorigenesis and carcinogenesis. In this study, secondary metabolite compounds from Lactococcus lactis subsp. lactis (Lac3) were analyzed by LC-MS and the potential inhibition activity against the COX-2 receptor was screened through molecular docking and molecular dynamics (MD) analysis. Anti-inflammatory agents, mofezolac and ibuprofen, were used as positive control ligands. The result indicates a potential COX-2 inhibitor of 5-[(4-Amino-6-morpholin-4-yl-1,3,5-triazin-2-yl)amino]-2- methylbenzenesulfonate, which has a hydrogen bond on the active site Tyr385 of COX-2 with affinity energy of –9.0 kcal/mol. Moreover, another candidate of COX-2 inhibitor, designated as 3-Indolepropionic acid binds hydrogen on the important residue Ser530 of COX-2, with an affinity energy of –6.9 kcal/mol. To confirm the binding specificity, molecular docking analysis was also performed against COX-1. The binding stability and flexibility were confirmed using MD simulations. In addition, the toxicity and solubility of the potential ligands were predicted according to Lipinski’s rules and BOILED-Egg modeling. The 5-[(4-Amino-6-morpholin-4-yl- 1,3,5-triazin-2-yl)amino]-2-methylbenzenesulfonate shows the propensity for passive absorption through the gastrointestinal tract, whereas 3-Indolepropionic acid shows a high probability of blood-brain barrier penetration. In conclusion, this study identified potential compounds through molecular docking analysis which can be developed as COX-2 inhibitors.

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CytochromeP450 isoenzyme specificity in the metabolism of anti-malarial biguanides: molecular docking and molecular dynamics analyses
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Anti-malarial proguanil (1) and phenoxypropoxy biguanide derivatives (2–9) are prodrugs. Their efficacy is directly proportional to the quantity of active triazine metabolites produced from these prodrugs. Detailed molecular docking analyses for all nine drug candidates in the active site of CYP3A4, CYP2D6, and CYP2C19 were carried out under the influence of induced-fit effect of ligand during molecular dynamic simulations. We have developed a strategy based on docking pose clusters to quantify the production of active metabolites for this class of molecules. For all drugs, site of metabolism based clusters of docking poses were prepared in both phases of the molecular docking analyses and correlated with the percentage of metabolites generated in the pooled human liver microsomes study. The total numbers of docking poses representing active metabolite formation were found to be well correlated with the experimental results in post-induced fit docking analyses. This strategy was first validated using proguanil, PS-15 and JPC-2056. Further, this methodology was employed to correlate the theoretically predicted metabolite formation of 4–9 to the experimentally estimated values which further led to clues on isoenzyme specificity in producing the metabolites. Binding requirements of these leads in the active sites of CYPs were also explored in this study.

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In Silico exploration for potent phytochemicals targeting Helicobacter pylori: assessment of ADMET profiles and molecular docking analysis
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Treatment of Helicobacter pylori (H. pylori) infections faces challenges such as drug adherence, drug resistance, and re-infection. Surface antigens like BabA and SabA cause the disease, while phytochemicals like glycyrrhizin and cinnamaldehyde in liquorice and cinnamon are highly absorbed by H. pylori. Other molecules like coumarin can disrupt H. pylori adherence. Optimizing pharmacokinetics of certain drugs remain a challenge. Plant-derived chemical compounds can overcome treatment restrictions using molecular docking research, drug compatibility, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) examinations. These tools help to determine the appropriate usage of phytochemicals in bacteria. Our work aims to explore the potential of phytochemicals (glycyrrhizin, cinnamaldehyde, coumarin) as a treatment for H. pylori disease using molecular docking (BabA, SabA, CagA, VacA and urease) and ADMET analysis by in silico approaches. Glycyrrhizin has the most favorable binding energies with both CagA (− 8.9 kcal/mol) and VacA (− 8.4 kcal/mol), indicating stable interactions. Cinnamaldehyde and coumarin show weaker binding energies, suggesting less stability. Amoxicillin and clarithromycin showed moderate binding energy. Glycyrrhizin, cinnamaldehyde, and coumarin showed non-toxicity in assays, while amoxicillin and clarithromycin displayed toxicity, underscoring the importance of thorough safety assessments in drug development by ADMET study. Compounds meeting Lipinski's Rule of Five criteria, including cinnamaldehyde and coumarin, demonstrate potential for good oral bioavailability. Despite these difficulties, substances like coumarin, glycyrrhizin, and cinnamondehyde can be useful in the treatment of H. pylori. In-depth safety evaluations and continuous research are essential for improving medication development and promoting more effective H. pylori treatment.Graphical

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Multiple machine learning, molecular docking, and ADMET screening approach for identification of selective inhibitors of CYP1B1
  • Mar 22, 2021
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Cytochrome P4501B1 is a ubiquitous family protein that is majorly overexpressed in tumors and is responsible for biotransformation-based inactivation of anti-cancer drugs. This inactivation marks the cause of resistance to chemotherapeutics. In the present study, integrated in-silico approaches were utilized to identify selective CYP1B1 inhibitors. To achieve this objective, we initially developed different machine learning models corresponding to two isoforms of the CYP1 family i.e. CYP1A1 and CYP1B1. Subsequently, small molecule databases including ChemBridge, Maybridge, and natural compound library were screened from the selected models of CYP1B1 and CYP1A1. The obtained CYP1B1 inhibitors were further subjected to molecular docking and ADMET analysis. The selectivity of the obtained hits for CYP1B1 over the other isoforms was also judged with molecular docking analysis. Finally, two hits were found to be the most stable which retained key interactions within the active site of CYP1B1 after the molecular dynamics simulations. Novel compound with CYP-D9 and CYP-14 IDs were found to be the most selective CYP1B1 inhibitors which may address the issue of resistance. Moreover, these compounds can be considered as safe agents for further cell-based and animal model studies. Communicated by Ramaswamy H. Sarma

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