Identification of serum predictors of n-acetyl-l-cysteine and isoproterenol induced remodelling in cardiac hypertrophy.

Cardiac hypertrophy (CH), leading to cardiac failure is due to chronic metabolic alterations occurring during cellular stress. Besides the already known relationship between oxidative stress and CH, there are implications of reductive stress leading to CH. This study attempted to develop reductive stress-based CH rat model using n-acetyl-L-cysteine (NAC), a glutathione agonist that was compared with typical isoproterenol (ISO) induced CH model. The main objective was to identify serum metabolites that can serve as potent predictors for seven routine clinical and diagnostic parameters in CH: 3-hydroxybutyrate (3-HB), lactic acid (LA), urea, and ECG-CH parameters (QRS complex, R-amplitude, R-R interval, heart rate) that were hypothesized to underlie metabolic remodelling in this study. CH was assessed using electrocardiography, hypertrophic index and histopathological analysis (H&E stain) in both ventricles after 2 weeks. Gas chromatography mass spectroscopy analysis (GC-MS) identified unique metabolite finger-prints. Correlation and pattern analysis revealed strong relationships between specific metabolites and parameters (Pearson's score > 0.7) of this study. Multiple regression analysis (MRA) for the strongly related metabolites (independent variables) with each of the seven parameters (dependent variables) identified significant predictors for the latter namely fructose, valine, butanoic acid in NAC and cholesterol, erythrose, isoleucine in ISO models, with proline and succinic acid as common for both models. Metabolite set enrichment analysis (MSEA) of those significant predictors (p < 0.05) mapped butyrate metabolism as highly influential pathway in NAC, with arginine-proline metabolism and branched chain amino acid (BCAA) degradation as common pathways in both models, thus providing new insights towards initial metabolic remodeling in the pathogenesis of CH.

Pharmacological analysis of hydroethanolic extract of Senna alata (L.) for in vitro free radical scavenging and cytotoxic activities against HepG2 cancer cell line.

The main objective of this study was to evaluate the hydroethanolic extract of Senna alata for the possible free radical scavenging and cytotoxic properties. Using such hydroethanolic extract, various in vitro antioxidant assays at different concentrations were performed and analyzed. In all the assays, plant extract has good inhibitory effect. Ethanolic extract of Senna alata was further subjected into cytotoxicity against HepG2 cell line. Accordingly, it was also found that the plant extract has appreciable potency against cancer cell lines.

Development of MLR and SVM Aided QSAR Models to Identify Common SAR of GABA Uptake Herbal Inhibitors used in the Treatment of Schizophrenia.

BACKGROUND: Alterations in GABAnergic system are implicated in the pathophysiology of schizophrenia. Available antipsychotics that target GABA receptor form a desirable therapeutic strategy in the treatment regimen of schizophrenia, unfortunately, suffer serious setback due to their prolonged side effects. The present investigation focuses on developing QSAR models from the biological activity of herbal compounds and their derivatives that promise to be alternative candidates to GABA uptake inhibitors. METHODS: Three sets of compounds were undertaken in the study to develop QSAR models. The first set consisted of nine compounds which included Magnolol, Honokiol and other GABA acting established compounds. The second set consisted of 16 derivatives of N-diarylalkenylpiperidinecarboxylic acid. The third QSAR dataset was made up of thirty two compounds which were Magnolol and Honokiol derivatives. Multiple linear regressions (MLR) and support vector machine (SVM) supervised quantitative structure-activity relationship (QSAR) models were developed to predict the biological activity of these three sets. The purpose of taking three QSAR sets of diverse chemical structures but identical in their GABA targeting and pharmacological action was to identify common chemical structure features responsible for structure-activity relationship (SAR). RESULTS: Linear and non-linear QSAR models confirmed that the three sets shared common structural descriptors derived from WHIM (Weighted Holistic Invariant Molecular descriptors), 3D-MoRSE and Eigenvalue classes. CONCLUSION: It was concluded that properties like electro negativity and polarizability play a crucial role in controlling the activity of herbal compounds against GABA receptor.

Molecular docking based screening of GABA (A) receptor inhibitors from plant derivatives.

UNLABELLED: The present antipsychotic drugs have known to show serious concerns like extra pyramidal side effects therefore, pursuit for novel antipsychotic GABAnergic drugs has lately focused on the folkloric medicine from plant derivatives as better treatment option of schizophrenia. The present study centers to identify potential inhibitors of plant origin for GABA receptor through in silico approaches. Three compound datasets were undertaken in the study. The first set consisted of seven compounds which included Magnolol, Honokiol and other plant derivatives. The second set consisted of 16 derivatives of N-diarylalkenyl-piperidinecarboxylic acid synthesized by Zheng et al., 2006. The third dataset had thirty two compounds which were Magnolol and Honokiol analogues synthesized by Fuchs et al., 2014. All the compounds were docked at the allosteric site of the GABA (A) receptor. The compounds were further tested for ADMET and biological activity. We observed Honokiol and its derivatives demonstrated superior druglike properties than any compound undertaken in the study. Further, compound 61 [2-(4-methoxyphenyl)-4-propylphenol] of dataset three - a synthetic derivative of honokiol had better profile than its parent compound. In a possible attempt to identify compound with even better efficacious compound than 61, virtual screening was performed, 135 compounds akin to compound 61 were retrieved. Interestingly none of the 135 compounds showed better druggable properties than compound 61. Our in silico pharmacological profiling of compounds is in coherence and is complemented by the findings of Fuchs et al, which also revealed compound 61 to be the good potentiator of GABA receptor. ABBREVIATIONS: GABA (A) R - Gamma Amino Butyric Acid Receptor, subtype A, GPCR - G Protein Coupled Receptor, OPLS - Optimized Potentials for Liquid Simulations, PDB - Protein Data Bank, PLP - Piece wise Linear Potential, T.E.S.T - Toxicity Estimation Software Tool, TCM - Traditional Chinese Medicine.

Effect of 50% hydro-ethanolic leaf extracts of ruellia tuberosa L. And dipteracanthus patulus (jacq.) on lipid profile in alloxan induced diabetic rats.

BACKGROUND: The study was undertaken to investigate the effect of 50% hydro -ethanolic leaf extracts of Ruellia tuberosa L. and Dipteracanthus patulus (Jacq.) on lipid profile in alloxan induced diabetic rats. METHOD: In lipid profile the parameters studied were serum total cholesterol, phospholipids, triglycerides, HDL-c, LDL-c and VLDL-c level. Extracts were orally administered daily for 30 days at a dosage of 250 and 500 mg/kg bodyweight to alloxan induced diabetic rats. RESULTS: The levels of phospholipids, triglycerides, LDL-c and VLDL-c were significantly (P < 0.05) reduced. The HDL-c level was found to be increased in the treatment groups. Total cholesterol level was found to be significantly (P < 0.05) decreased at 500 mg/kg bodyweight of both the plant extracts treated groups. CONCLUSION: The results further suggests that the effect of plant extract treated groups was found to be lower in reducing the lipid levels in serum when compared to the drug (Glibenclamide 600 µg/kg body weight) treated group.