In the indigenous system of medicine in India, the plant Sesbania grandiflora is claimed to be useful for various ailments, and one such use is for the treatment of renal calculi. The major purpose of this study is to investigate the potential of S. grandiflora in the treatment of renal calculi. The leaf juice of S. grandiflora was evaluated for median lethal dose, gross behavioral changes, antiurolithiatic and antioxidant activities. The antiurolithiatic activity was evaluated by a calculi-producing diet model, using gentamicin (subcutaneously) and 5% ammonium oxalate in rat feed to induce calcium oxalate-type stones. The parameters monitored in the present study are calcium and oxalate deposition in the kidney, kidney weights, urinary excretion of calcium and oxalate. The in vivo antioxidant parameters lipid peroxidation, glutathione reductase and catalase were monitored. The plant juice was also evaluated for scavenging of nitric oxide and 2-diphenyl-2-picryl hydrazyl free radicals. The leaf juice of S. grandiflora was safe orally and exhibited no gross behavioral changes except for an increase in urination. The leaf juice of S. grandiflora showed significant antiurolithiatic activity against calcium oxalate-type stones and also exhibited antioxidant properties. The results obtained in this study provide evidence for the efficacy of the leaf juice of S. grandiflora as antiurolithiatic agent.
A simple, sensitive, precise, accurate and robust high performance liquid chromatographic method has been developed for simultaneous estimation of saxagliptin (SAXA) and dapagliflozin (DAPA) in pharmaceutical formulation. Design of experiments (DoE) was applied for multivariate optimization of the experimental conditions of RP-HPLC method. Risk assessment was performed to identify the critical method parameters. Three independent factors; mobile phase composition, flow rate and column temperature were used to design mathematical models. Central composite design (CCD) was used to study the response surface methodology and to study in depth the effects of these independent factors. Desirability function was used to simultaneously optimize the retention time and resolution of SAXA and DAPA. The optimized and predicted data from contour diagram consisted of acetonitrile and ortho phosphoric acid (0.1%) in the ratio of 50:50 respectively, at a flow rate of 0.98 ml/min and column temperature 31.4 °C. Using these optimum conditions baseline separation of both drugs with good resolution and run time of less than 6 min were achieved. The optimized assay conditions were validated according to ICH guidelines. Hence, the results clearly showed that Quality by design approach could be successfully applied to optimize RP-HPLC method for simultaneous estimation of SAXA and DAPA.
The coronavirus disease-19 (COVID-19) outbreak that is caused by a highly contagious severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a zoonotic pandemic, with approximately 24.5 million positive cases and 8.3 lakhs deaths globally. The lack of effective drugs or vaccine provoked the research for drug candidates that can disrupt the spread and progression of the virus. The identification of drug molecules through experimental studies is time-consuming and expensive, so there is a need for developing alternative strategies like
in silico
approaches which can yield better outcomes in less time. Herein, we selected transmembrane protease serine 2 (TMPRSS2) enzyme, a potential pharmacological target against SARS-CoV-2, involved in the spread and pathogenesis of the virus. Since 3D structure is not available for this protein, the present study aims at homology modelling and validation of TMPRSS2 using Swiss-model server. Validation of the modelled TMPRSS2 using various online tools confirmed model accuracy, topology and stereochemical plausibility. The catalytic triad consisting of Serine-441, Histidine-296 and Aspartic acid-345 was identified as active binding site of TMPRSS2 using existing ligands. Molecular docking studies of various drugs and phytochemicals against the modelled TMPRSS2 were performed using camostat as a standard drug. The results revealed eight potential drug candidates, namely nafamostat, meloxicam, ganodermanontriol, columbin, myricetin, proanthocyanidin A2, jatrorrhizine and baicalein, which were further studied for ADME/T properties. In conclusion, the study unravelled eight high affinity binding compounds, which may serve as potent antagonists against TMPRSS2 to impact COVID-19 drug therapy.
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