Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Paper Count: 6

6
10007347
Investigation of Possible Behavioural and Molecular Effects of Mobile Phone Exposure on Rats
Abstract:

The N-methyl-D-aspartate (NMDA)-dependent pathway is the major intracellular signaling pathway implemented in both short- and long-term memory formation in the hippocampus which is the most studied brain structure because of its well documented role in learning and memory. However, little is known about the effects of RF-EMR exposure on NMDA receptor signaling pathway including activation of protein kinases, notably Ca2+/calmodulin-dependent protein kinase II alpha (CaMKIIα). The aim of the present study was to investigate the effects of acute and chronic 900 MHz RF-EMR exposure on both passive avoidance behaviour and hippocampal levels of CaMKIIα and its phosphorylated form (pCaMKIIα). Rats were divided into the following groups: Sham rats, and rats exposed to 900 MHz RF-EMR for 2 h/day for 1 week (acute group) or 10 weeks (chronic group), respectively. Passive avoidance task was used as a behavioural method. The hippocampal levels of selected kinases were measured using Western Blotting technique. The results of passive avoidance task showed that both acute and chronic exposure to 900 MHz RF-EMR can impair passive avoidance behaviour with minor effects on chronic group of rats. The analysis of western blot data of selected protein kinases demonstrated that hippocampal levels of CaMKIIα and pCaMKIIα were significantly higher in chronic group of rats as compared to acute groups. Taken together, these findings demonstrated that different duration times (1 week vs 10 weeks) of 900 MHz RF-EMR exposure have different effects on both passive avoidance behaviour of rats and hippocampal levels of selected protein kinases.

5
10001695
Bioinformatics and Molecular Biological Characterization of a Hypothetical Protein SAV1226 as a Potential Drug Target for Methicillin/Vancomycin- Staphylococcus aureus Infections
Abstract:
Methicillin/multiple-resistant Staphylococcus aureus (MRSA) are infectious bacteria that are resistant to common antibiotics. A previous in silico study in our group has identified a hypothetical protein SAV1226 as one of the potential drug targets. In this study, we reported the bioinformatics characterization, as well as cloning, expression, purification and kinetic assays of hypothetical protein SAV1226 from methicillin/vancomycin-resistant Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis revealed a low degree of structural similarity with known proteins. Kinetic assays demonstrated that hypothetical protein SAV1226 is neither a domain of an ATP dependent dihydroxyacetone kinase nor of a phosphotransferase system (PTS) dihydroxyacetone kinase, suggesting that the function of hypothetical protein SAV1226 might be misannotated on public databases such as UniProt and InterProScan 5.
4
9998537
Systematic Identification and Quantification of Substrate Specificity Determinants in Human Protein Kinases
Abstract:

Protein kinases participate in a myriad of cellular processes of major biomedical interest. The in vivo substrate specificity of these enzymes is a process determined by several factors, and despite several years of research on the topic, is still far from being totally understood. In the present work, we have quantified the contributions to the kinase substrate specificity of i) the phosphorylation sites and their surrounding residues in the sequence and of ii) the association of kinases to adaptor or scaffold proteins. We have used position-specific scoring matrices (PSSMs), to represent the stretches of sequences phosphorylated by 93 families of kinases. We have found negative correlations between the number of sequences from which a PSSM is generated and the statistical significance and the performance of that PSSM. Using a subset of 22 statistically significant PSSMs, we have identified specificity determinant residues (SDRs) for 86% of the corresponding kinase families. Our results suggest that different SDRs can function as positive or negative elements of substrate recognition by the different families of kinases. Additionally, we have found that human proteins with known function as adaptors or scaffolds (kAS) tend to interact with a significantly large fraction of the substrates of the kinases to which they associate. Based on this characteristic we have identified a set of 279 potential adaptors/scaffolds (pAS) for human kinases, which is enriched in Pfam domains and functional terms tightly related to the proposed function. Moreover, our results show that for 74.6% of the kinase–pAS association found, the pAS colocalize with the substrates of the kinases they are associated to. Finally, we have found evidence suggesting that the association of kinases to adaptors and scaffolds, may contribute significantly to diminish the in vivo substrate crossed-specificity of protein kinases. In general, our results indicate the relevance of several SDRs for both the positive and negative selection of phosphorylation sites by kinase families and also suggest that the association of kinases to pAS proteins may be an important factor for the localization of the enzymes with their set of substrates.

3
17118
Tumor Necrosis Factor-α Regulates Heme Oxygenase-1 Expression in Endothelial Cells via the Phosphorylation of JNK/p38
Abstract:

Heme oxygenase-1 (HO-1), an enzyme degrading heme to carbon monoxide, iron, and biliverdin, has been recognized as playing a crucial role in cellular defense against stressful conditions, not only related to heme release. In the present study, the effects of TNF-a on the expression of heme oxygenase-1 (HO-1) in human aortic endothelial cells (HAECs) as well as the related mechanisms were investigated. 10 ng/mL TNF-α treatment significantly increased HO-1 expression after 6h, then a further increase at 12h and declined at 24h. Treatment with 2 ng/mL of TNF-a after 12 h resulted in a significant increase in HO-1 expression, which peaked at 10 ng/mL, then declined at 20 ng/mL. TNF-α induced HO-1 expression and then HO-1 expression reduced  vascular cell adhesion molecule-1 (VCAM-1) expression. Phosphorylation studies of ERK1/2, JNK, and p38, three subgroups of mitogen-activated protein kinases (MAPKs) demonstrated TNF-α-induced ERK1/2, JNK, and p38 phosphorylation. The increase in HO-1 expression in response to TNF-α treatment was affected by pretreatment with SP600125 (a JNK inhibitor) and SB203580 (a p38 inhibitor), not with PD98059 (an ERK1/2 inhibitor). The expression of HO-1 was stronger in aortas of TNF-α-treated apo-E deficient mice when compared with control mice. These results suggest that low dose of TNF-α treatment notably induced HO-1 expression was mediated through JNK/p38 phosphorylation and may have a protective potential in cardiovascular diseases and inflammatory response through the regulation of HO-1 expression.

2
15192
In Silico Analysis of Quinoxaline Ligand Conformations on 1ZIP: Adenylate Kinase
Abstract:
Adenylate kinase (AK) catalyse the phosphotransferase reaction plays an important role in cellular energy homeostasis. The inhibitors of bacterial AK are useful in the treatment of several bacterial infections. To the novel inhibitors of AK, docking studies performed by using the 3D structure of Bacillus stearothermophilus adenylate kinase from protein data bank (IZIP). 46 Quinoxaline analogues were docked in 1ZIP and selected the highly interacting compounds based on their binding energies, for further studies
1
11829
Parameters Identification of Mathematical Model of the Fission Yeast Cell Cycle Control Using Evolutionary Strategy
Abstract:
Complex assemblies of interacting proteins carry out most of the interesting jobs in a cell, such as metabolism, DNA synthesis, mitosis and cell division. These physiological properties play out as a subtle molecular dance, choreographed by underlying regulatory networks that control the activities of cyclin-dependent kinases (CDK). The network can be modeled by a set of nonlinear differential equations and its behavior predicted by numerical simulation. In this paper, an innovative approach has been proposed that uses genetic algorithms to mine a set of behavior data output by a biological system in order to determine the kinetic parameters of the system. In our approach, the machine learning method is integrated with the framework of existent biological information in a wiring diagram so that its findings are expressed in a form of system dynamic behavior. By numerical simulations it has been illustrated that the model is consistent with experiments and successfully shown that such application of genetic algorithms will highly improve the performance of mathematical model of the cell division cycle to simulate such a complicated bio-system.
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