Identification of GR and TrxR systems in Setaria cervi: Purification and characterization of glutathione reductase

The glutathione reductase (GR) and thioredoxin reductase (TrxR) are important enzymes of the redox system that aid parasites to maintain an adequate intracellular redox environment. In the present study, the enzyme activity of GR and TrxR was investigated in Setaria cervi (S. cervi). Significant activity of both enzymes was detected in the somatic extract of adult and microfilariae stages of S. cervi. Both GR and TrxR were separated by partial purification using ammonium sulfate fractionation and DEAE ion exchange chromatography suggesting the presence of both glutathione and thioredoxin systems in S. cervi. The enzyme glutathione reductase (ScGR) was purified to homogeneity using affinity and ion exchange chromatography that resulted in 90 fold purification with a yield of 11.54%. The specific activity of the ScGR was 643 U/mg that migrated as a single band on SDS-PAGE. The subunit molecular mass was determined to be ~ 50 kDa while the optimum pH and temperature were found to be 7.0 and 35 °C respectively. The activation energy (Ea) was calculated from the slope of Arrhenius plot as 16.29 ± 1.40 kcal/mol. The Km and Vmax were determined to be 0.27 ± 0.045 mM; 30.30 ± 1.30 U/ml with NADPH and 0.59 ± 0.060 mM; 4.16 ± 0.095 U/ml with GSSG respectively. DHBA, a specific inhibitor for GR has completely inhibited the enzyme activity at 1 μM concentration. The inhibition of ScGR activity with NAI (IC₅₀ 0.71 mM), NEM (IC₅₀ 0.50 mM) and DEPC (IC₅₀ 0.27 mM) suggested the presence of tyrosine, cysteine and histidine residues at its active site. Further studies on characterization and understanding of these antioxidant enzymes may lead to designing of an effective drug against lymphatic filariasis.     

Delphinidin Reduces Cell Proliferation and Induces Apoptosis of Non-Small-Cell Lung Cancer Cells by Targeting EGFR/VEGFR2 Signaling Pathways

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor 2 (VEGFR2) have emerged as two effective clinical targets for non-small-cell lung cancer (NSCLC). In the present study, we found that delphinidin, an anthocyanidin, present in pigmented fruits and vegetables, is a potent inhibitor of both EGFR and VEGFR2 in NSCLC cells that overexpress EGFR/VEGFR2. Using these cells, we next determined the effects of delphinidin on cell growth and apoptosis in vitro and on tumor growth and angiogenesis in vivo. Delphinidin (5-60 µM) treatment of NSCLC cells inhibited the activation of PI3K, and phosphorylation of AKT and MAPKs. Additionally, treatment of NSCLC cells with delphinidin resulted in inhibition of cell growth without having significant toxic effects on normal human bronchial epithelial cells. Specifically, treatment of NCI-H441 and SK-MES-1 cells with delphindin (5-60 µM) resulted in (i) cleavage of PARP protein, (ii) activation of caspase-3 and -9, (iii) downregulation of anti-apoptotic proteins (Bcl2, Bcl-xL and Mcl-1), (iv) upregulation of pro-apoptotic proteins (Bax and Bak), and (v) decreased expression of PCNA and cyclin D1. Furthermore, in athymic nude mice subcutaneously implanted with human NSCLC cells, delphinidin treatment caused a (i) significant inhibition of tumor growth, (ii) decrease in the expression of markers for cell proliferation (Ki67 and PCNA) and angiogenesis (CD31 and VEGF), and (iii) induction of apoptosis, when compared with control mice. Based on these observations, we suggest that delphinidin, alone or as an adjuvant to current therapies, could be used for the management of NSCLC, especially those that overexpress EGFR and VEGFR2.     

Modeling the activity of glutathione as a hydroxyl radical scavenger considering its neutral non-zwitterionic form

Glutathione is an immensely important antioxidant, particularly in the central nervous system. The scavenging mechanism of glutathione towards the OH radical was studied theoretically, considering its neutral, non-zwitterionic form relevant to acidic media. Gibbs free barrier and released energies involved in hydrogen abstraction from the different sites of glutathione by an OH radical were studied at the B3LYP/6-31G(d,p), B3LYP/AUG-cc-pVDZ, M06/AUG-cc-pVDZ, M06-2X/AUG-cc-pVDZ levels of density functional theory. Solvation in bulk aqueous media was also studied at all these levels of theory employing the polarizable continuum model. Our study shows that a hydroxyl radical can abstract a hydrogen atom easily from glutathione. Thus, glutathione is shown to be an efficient scavenger of OH radicals, which is in agreement with the results of previous studies.

Plasmon-Enhanced Light Trapping to Improve Efficiency of TiO2 Nanorod-Based Dye-Sensitized Solar Cell

Localized surface plasmon resonance incurred by silver nanoparticles is used to enhance the photoelectric conversion efficiency of a TiO₂ nanorod-based dye-sensitized solar cell (DSSC). Improved light transmission is observed experimentally in silver nanoparticle-coated FTO glass. The transmission data are used to explore the effect on electrical parameters of DSSC using theoretical model. Current density increased from 11.7 to 12.34 mA/cm² and open-circuit voltage increased from 704 to 709.5 mV. Overall efficiency enhancement of 6.67 % is observed in TiO₂ nanorod-based DSSC due to plasmon-induced light trapping.     

Resveratrol depletes mitochondrial DNA and inhibition of autophagy enhances resveratrol-induced caspase activation

We recently demonstrated that resveratrol induces caspase-dependent apoptosis in multiple cancer cell types. Whether apoptosis is also regulated by other cell death mechanisms such as autophagy is not clearly defined. Here we show that inhibition of autophagy enhanced resveratrol-induced caspase activation and apoptosis. Resveratrol inhibited colony formation and cell proliferation in multiple cancer cell types. Resveratrol treatment induced accumulation of LC3-II, which is a key marker for autophagy. Pretreatment with 3-methyladenine (3-MA), an autophagy inhibitor, increased resveratrol-mediated caspase activation and cell death in breast and colon cancer cells. Inhibition of autophagy by silencing key autophagy regulators such as ATG5 and Beclin-1 enhanced resveratrol-induced caspase activation. Mechanistic analysis revealed that Beclin-1 did not interact with proapoptotic proteins Bax and Bak; however, Beclin-1 was found to interact with p53 in the cytosol and mitochondria upon resveratrol treatment. Importantly, resveratrol depleted ATPase 8 gene, and thus, reduced mitochondrial DNA (mtDNA) content, suggesting that resveratrol induces damage to mtDNA causing accumulation of dysfunctional mitochondria triggering autophagy induction. Together, our findings indicate that induction of autophagy during resveratrol-induced apoptosis is an adaptive response.     

In silico Platform for Prediction of N-, O- and C-Glycosites in Eukaryotic Protein Sequences

Glycosylation is one of the most abundant and an important post-translational modification of proteins. Glycosylated proteins (glycoproteins) are involved in various cellular biological functions like protein folding, cell-cell interactions, cell recognition and host-pathogen interactions. A large number of eukaryotic glycoproteins also have therapeutic and potential technology applications. Therefore, characterization and analysis of glycosites (glycosylated residues) in these proteins is of great interest to biologists. In order to cater these needs a number of in silico tools have been developed over the years, however, a need to get even better prediction tools remains. Therefore, in this study we have developed a new webserver GlycoEP for more accurate prediction of N-linked, O-linked and C-linked glycosites in eukaryotic glycoproteins using two larger datasets, namely, standard and advanced datasets. In case of standard datasets no two glycosylated proteins are more similar than 40%; advanced datasets are highly non-redundant where no two glycosites’ patterns (as defined in methods) have more than 60% similarity. Further, based on our results with several algorihtms developed using different machine-learning techniques, we found Support Vector Machine (SVM) as optimum tool to develop glycosite prediction models. Accordingly, using our more stringent and non-redundant advanced datasets, the SVM based models developed in this study achieved a prediction accuracy of 84.26%, 86.87% and 91.43% with corresponding MCC of 0.54, 0.20 and 0.78, for N-, O- and C-linked glycosites, respectively. The best performing models trained on advanced datasets were then implemented as a user-friendly web server GlycoEP (http://www.imtech.res.in/raghava/glycoep/). Additionally, this server provides prediction models developed on standard datasets and allows users to scan sequons in input protein sequences.