Now showing 1 - 3 of 3
  • Publication
    DataExplore: An Application for General Data Analysis in Research and Education
    (Ubiquity Press, 2016-03-22)
    DataExplore is an open source desktop application for data analysis and plotting intended for use in both research and education. It is intended primarily for non-programmers who need to do relatively advanced table manipulation methods. Common tasks that might not be familiar to spreadsheet users such as table pivot, merge and join functionality are included as core elements. Creation of new columns using arithmetic expressions and pre-defined functions is possible. Table filtering may be done with simple boolean queries. The other primary feature is rapid dynamic plot creation from selected data. Multiple plots from various selections and data sources can also be composed using a grid layout. It is thus possible to create publication quality plots. A plugin system allows the addition of features with several plugins already available by default. The program is written in Python and is based on the PyData suite of Python libraries.
  • Publication
    Computational selection of novel antigenic targets in the Mycobacterium bovis proteome
    The discovery of novel antigens is an essential requirement in devising new diagnostics for use in both M. tuberculosis (Mtb) and M. bovis control programmes. Reverse vaccinology is now a feasible method of extracting potential immunogenic epitopes from bacterial genomes to reduce the cost of experimental screening of antigens for anamnestic responses in infected hosts. Since a significant focus has been on the role of CD4+ T cells, the ability to predict peptide binding to MHC-II molecules is seen as a key step in discovery.Previous antigen-mining experiments for identification of novel diagnostic or vaccine candidates for human and bovine TB follow a targeted approach, where specific groups of proteins suspected to contain likely candidates are identified and evaluated for  mmunogenicity. A disadvantage of those approaches is that they are restricted to a relatively small set of proteins biased by the initial selection criteria. Our objective was to computationally select antigens in a less biased manner.
  • Publication
    Protein Dielectric Constants Determined from NMR Chemical Shift Perturbations
    Understanding the connection between protein structure and function requires a quantitative under-standing of electrostatic effects. Structure-based electrostatics calculations are essential for this purpose, but their use has been limited by a long-standing discussion on which value to use for the dielectric constants (εeff and εp) required in Coulombic models and Poisson-Boltzmann models. The currently used values for εeff and εp are essentially empirical parameters calibrated against thermodynamic properties that are indirect measurements of protein electric fields. We determine optimal values for εeff and εp by measuring protein electric fields in solution using direct detection of NMR chemical shift perturbations (CSPs). We measured CSPs in fourteen proteins to get a broad and general characterization of electric fields. Coulomb’s law reproduces the measured CSPs optimally with a protein dielectric constant (εeff) from 3 to 13, with an optimal value across all proteins of 6.5. However, when the water-protein interface is treated with finite difference Poisson-Boltzmann calculations, the optimal protein dielectric constant (εp) rangedsfrom 2-5 with an optimum of 3. It is striking how similar this value is to the dielectric constant of 2-4 measured for protein powders, and how different it is from the εp of 6-20 used in models based on the Poisson-Boltzmann equation when calculating thermodynamic parameters. Because the value of εp = 3 is obtained by analysis of NMR chemical shift perturbations instead of thermodynamic parameters such as pKa values, it is likely to describe only the electric field and thus represent a more general, intrinsic, and transferable εp common to most folded proteins.
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