scholarly journals Comparative in silico analysis identifies bona fide MyoD binding sites within the Myocyte Stress 1 gene promoter

2008 ◽  
Vol 9 (1) ◽  
pp. 50 ◽  
Author(s):  
Samir Ounzain ◽  
Caroline S Dacwag ◽  
Nilesh J Samani ◽  
Anthony N Imbalzano ◽  
Nelson W Chong
2010 ◽  
Vol 68 ◽  
pp. e354
Author(s):  
Mana Igarashi ◽  
Shingo Nakamura ◽  
Mika Kinoshita ◽  
Hirotaka J. Okano ◽  
Hideyuki Okano

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5704
Author(s):  
Zuzana Janíčková ◽  
Štefan Janeček

This study brings a detailed bioinformatics analysis of fungal and chloride-dependent α-amylases from the family GH13. Overall, 268 α-amylase sequences were retrieved from subfamilies GH13_1 (39 sequences), GH13_5 (35 sequences), GH13_15 (28 sequences), GH13_24 (23 sequences), GH13_32 (140 sequences) and GH13_42 (3 sequences). Eight conserved sequence regions (CSRs) characteristic for the family GH13 were identified in all sequences and respective sequence logos were analysed in an effort to identify unique sequence features of each subfamily. The main emphasis was given on the subfamily GH13_32 since it contains both fungal α-amylases and their bacterial chloride-activated counterparts. In addition to in silico analysis focused on eventual ability to bind the chloride anion, the property typical mainly for animal α-amylases from subfamilies GH13_15 and GH13_24, attention has been paid also to the potential presence of the so-called secondary surface-binding sites (SBSs) identified in complexed crystal structures of some particular α-amylases from the studied subfamilies. As template enzymes with already experimentally determined SBSs, the α-amylases from Aspergillus niger (GH13_1), Bacillus halmapalus, Bacillus paralicheniformis and Halothermothrix orenii (all from GH13_5) and Homo sapiens (saliva; GH13_24) were used. Evolutionary relationships between GH13 fungal and chloride-dependent α-amylases were demonstrated by two evolutionary trees—one based on the alignment of the segment of sequences spanning almost the entire catalytic TIM-barrel domain and the other one based on the alignment of eight extracted CSRs. Although both trees demonstrated similar results in terms of a closer evolutionary relatedness of subfamilies GH13_1 with GH13_42 including in a wider sense also the subfamily GH13_5 as well as for subfamilies GH13_32, GH13_15 and GH13_24, some subtle differences in clustering of particular α-amylases may nevertheless be observed.


2018 ◽  
Vol 46 (1) ◽  
pp. 1413-1424 ◽  
Author(s):  
Mónica De Nova-Ocampo ◽  
Mayra Cristina Soliman ◽  
Wendy Espinosa-Hernández ◽  
Cristina Velez-del Valle ◽  
Juan Salas-Benito ◽  
...  

Glutathione (g-glutamylcysteinylglycine) redox homeostasis in human erythrocytes is dependent on the activities of glutathione peroxidase (GPX1, EC 1.11.1.9), glutathione reductase (GSR, EC 1.8.1.7), glutaredoxin 1 (GRX1) and NADPH-generating enzymes of pentose phosphate pathway, glucose-6-phosphate dehydrogenase (G6PD, EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (PGD, EC 1.1.1.44). Free heme accumulation under hemolysis can affect proteins activity thereby in silico analysis of glutathione redox cycle enzymes structure was performed in order to reveal putative heme-binding sites and oxidizable cysteine residues. Protein annotations were taken from UniProt. Heme docking was performed by PatchDock with clustering RMSD 1,5 Å using PDB structures of proteins and heme. Cysteines oxidation potential was estimated by Cy-Preds. Heme binding GSR monomers (1DNC, 3DJJ, 3DK9, 2GRT) and dimers (3SQP, 2GH5) was predicted through His81 close to interchain disulfide bond and through Cys59 near FAD and GSSG binding sites. Heme-binding areas in GPX1 (2F8A) and GPX3 (2R37) also were revealed in the interchain region and in active centre (His80). GLRX1 (4RQR) was predicted to bind heme almost exclusively near the N-end in spite of accessibility of all cysteines including CPYC motif in active centre. G6PD monomer (2BH9, 5UKW) revealed heme-docking areas in NADP+ binding region and a-helix 437–447 located in dimer 2BHL at the interchain surface. Heme docking to PGD (4GWG, 4GWK) was in substrate binding region near His187. So enzymes active centres and chain interaction regions were revealed in the most of heme docking variants. From one (in PGD) to three (GSR) cysteines susceptible to oxidation were found in each protein including cysteines that were predicted to bind heme. Heme-mediated oxidative effect on glutathione redox cycle enzymes in erythrocytes and blood plasma could be an important mechanism of hemolysis progression under stress and pathologies.


2013 ◽  
Vol 113 (suppl_1) ◽  
Author(s):  
Marina Bayeva ◽  
Konrad Sawicki ◽  
Hossein Ardehali

Introduction: Heart disease and stroke are the primary causes of death in adults with type-2 diabetes thus strict metabolic control is essential in these patients. Here, we show that tristetraprolin (TTP), a protein involved in regulation of inflammation and iron homeostasis via mRNA degradation, may alleviate diabetic phenotype through modulation of key enzymes involved in gluconeogenesis and fatty acid (FA) metabolism in insulin-sensitive tissues. Results: TTP protein content was significantly reduced in livers of diabetic mice fed high-fat diet compared to control, suggesting that mRNA targets of TTP may be stabilized in diabetes. We then assessed the effects of TTP knockdown using siRNA in HepG2 liver cells on the expression of enzymes in four major metabolic pathways: glycolysis, gluconeogenesis, FA oxidation and synthesis. Consistent with reduced TTP, we found increased expression of a key gluconeogenic regulator - pyruvate dehydrogenase kinase 4 (PDK4). In silico analysis of the 3’ untranslated region (UTR) of PDK4 revealed five putative TTP binding sites. Importantly, elevated PDK4 levels were previously reported in diabetic patients, and are thought to exacerbate the disease by increasing hepatic glucose output. Assessment of FA metabolism revealed increased levels of PPARα and two of its targets, carnitine palmitoyltransferase I (CPT1) and fatty acid translocase (FAT). Consistent with increased FA flux, triglyceride levels were elevated with TTP siRNA in hepatocytes. In silico analysis revealed multiple well-conserved putative TTP-binding sites in the 3’UTR of PPARα, consistent with regulation by TTP. We also observed significant upregulation of PPARα and its targets in HL-1 cardiac cell line, indicating an overlapping function for TTP in insulin-sensitive tissues. Notably, cardiac-specific overexpression of PPARα was previously shown to cause a phenotype resembling diabetic cardiomyopathy, further suggesting that reduction of TTP in diabetes may exacerbate this disease. Conclusions: Our studies show that TTP is downregulated in diabetic mouse livers, and knockdown of this protein in hepatic and cardiac cells increases the levels of key metabolic enzymes, PDK4 and PPARα, both of which are implicated in diabetes and heart disease.


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