Current Issue : July - September Volume : 2012 Issue Number : 3 Articles : 5 Articles
Identification of regulatory molecules in signaling pathways is critical for understanding cellular behavior. Given the complexity of\r\nthe transcriptional gene network, the relationship between molecular expression and phenotype is difficult to determine using reductionist\r\nexperimental methods. Computational models provide the means to characterize regulatory mechanisms and predict\r\nphenotype in the context of gene networks. Integrating gene expression data with phenotypic data in transcriptional network models\r\nenables systematic identification of critical molecules in a biological network.We developed an approach based on fuzzy logic to\r\nmodel cell budding in Saccharomyces cerevisiae using time series expression microarray data of the cell cycle. Cell budding is a phenotype\r\nof viable cells undergoing division. Predicted interactions between gene expression and phenotype reflected known biological\r\nrelationships. Dynamic simulation analysis reproduced the behavior of the yeast cell cycle and accurately identified genes and\r\ninteractions which are essential for cell viability....
For high-resolution tandem mass spectra, the determination of monoisotopic masses of fragment ions plays a key role in the\r\nsubsequent peptide and protein identification. In this paper, we present a new algorithm for deisotoping the bottom-up spectra.\r\nIsotopic-cluster graphs are constructed to describe the relationship between all possible isotopic clusters. Based on the relationship\r\nin isotopic-cluster graphs, each possible isotopic cluster is assessed with a score function, which is built by combining nonintensity\r\nand intensity features of fragment ions. The non-intensity features are used to prevent fragment ions with low intensity from\r\nbeing removed. Dynamic programming is adopted to find the highest score path with the most reliable isotopic clusters. The\r\nexperimental results have shown that the average Mascot scores and F-scores of identified peptides from spectra processed by our\r\ndeisotoping method are greater than those by YADA and MS-Deconv software....
Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to\r\ncomputational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within\r\ntheir context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying\r\npotential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets,\r\nfunctional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of\r\nthese microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between\r\nMycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced\r\nfor identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of\r\npotential drug targets and to move towards optimal target-based strategies....
Biological functionality arises from the complex interactions of simple components. Emerging behaviour is difficult to recognize\r\nwith verbal models alone, and mathematical approaches are important. Even few interacting components can give rise to a wide\r\nrange of different responses, that is, sustained, transient, oscillatory, switch-like responses, depending on the values of the model\r\nparameters. A quantitative comparison of model predictions and experiments is therefore important to distinguish between\r\ncompeting hypotheses and to judge whether a certain regulatory behaviour is at all possible and plausible given the observed\r\ntype and strengths of interactions and the speed of reactions. Here I will review a detailed model for the transcription factor sF, a\r\nregulator of cell differentiation during sporulation in Bacillus subtilis. I will focus in particular on the type of conclusions that can\r\nbe drawn from detailed, carefully validated models of biological signaling networks. For most systems, such detailed experimental\r\ninformation is currently not available, but accumulating biochemical data through technical advances are likely to enable the\r\ndetailed modelling of an increasing number of pathways. A major challenge will be the linking of such detailed models and their\r\nintegration into a multiscale framework to enable their analysis in a larger biological context....
The first step of HIV-1 infection involves interaction between the viral glycoprotein gp120 and the human cellular receptor CD4.\r\nInhibition of the gp120-CD4 interaction represents an attractive strategy to block HIV-1 infection. In an attempt to explore the\r\nknown lack of affinity of murine CD4 to gp120, we have investigated peptides presenting the putative gp120-binding site of\r\nmurine CD4 (mCD4). Molecular modeling indicates that mCD4 protein cannot bind gp120 due to steric clashes, while the larger\r\nconformational flexibility of mCD4 peptides allows an interaction. This finding is confirmed by experimental binding assays, which\r\nalso evidenced specificity of the peptide-gp120 interaction.Molecular dynamics simulations indicate that the mCD4-peptide stably\r\ninteracts with gp120 via an intermolecular �Ÿ-sheet, while an important salt-bridge formed by a C-terminal lysine is lost. Fixation\r\nof the C-terminus by introducing a disulfide bridge between the N- and C-termini of the peptide significantly enhanced the affinity\r\nto gp120....
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