88 research outputs found

    Cloning, purification and characterisation of a recombinant purine nucleoside phosphorylase from Bacillus halodurans Alk36

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    A purine nucleoside phosphorylase from the alkaliphile Bacillus halodurans Alk36 was cloned and overexpressed in Escherichia coli. The enzyme was purified fivefold by membrane filtration and ion exchange. The purified enzyme had a Vmax of 2.03 × 10−9 s −1 and a Km of 206 μM on guanosine. The optimal pH range was between 5.7 and 8.4 with a maximum at pH 7.0. The optimal temperature for activity was 70°C and the enzyme had a half life at 60°C of 20.8 h

    Hijacking of the Pleiotropic Cytokine Interferon-γ by the Type III Secretion System of Yersinia pestis

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    Yersinia pestis, the causative agent of bubonic plague, employs its type III secretion system to inject toxins into target cells, a crucial step in infection establishment. LcrV is an essential component of the T3SS of Yersinia spp, and is able to associate at the tip of the secretion needle and take part in the translocation of anti-host effector proteins into the eukaryotic cell cytoplasm. Upon cell contact, LcrV is also released into the surrounding medium where it has been shown to block the normal inflammatory response, although details of this mechanism have remained elusive. In this work, we reveal a key aspect of the immunomodulatory function of LcrV by showing that it interacts directly and with nanomolar affinity with the inflammatory cytokine IFNγ. In addition, we generate specific IFNγ mutants that show decreased interaction capabilities towards LcrV, enabling us to map the interaction region to two basic C-terminal clusters of IFNγ. Lastly, we show that the LcrV-IFNγ interaction can be disrupted by a number of inhibitors, some of which display nanomolar affinity. This study thus not only identifies novel potential inhibitors that could be developed for the control of Yersinia-induced infection, but also highlights the diversity of the strategies used by Y. pestis to evade the immune system, with the hijacking of pleiotropic cytokines being a long-range mechanism that potentially plays a key role in the severity of plague

    Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock

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    <p>Abstract</p> <p>Background</p> <p>Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.</p> <p>Results</p> <p>The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.</p> <p>Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.</p> <p>Conclusion</p> <p>Our results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.</p

    The use of biodiversity as source of new chemical entities against defined molecular targets for treatment of malaria, tuberculosis, and T-cell mediated diseases: a review

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    Structural biology of the purine biosynthetic pathway

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    Direct-method-aided phasing of MAD data

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    A localized specific interaction alters the unfolding pathways of structural homologues

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    Reductive unfolding studies of proteins are designed to provide information about intramolecular interactions that govern the formation (and stabilization) of the native state and about folding/unfolding pathways. By mutating Tyr92 to G, A, or L in the model protein, bovine pancreatic ribonuclease A, and through analysis of temperature factors and molecular dynamics simulations of the crystal structures of these mutants, it is demonstrated that the markedly different reductive unfolding rates and pathways of ribonuclease A and its structural homologue onconase can be attributed to a single, localized, ring-stacking interaction between Tyr92 and Pro93 in the bovine variant. The fortuitous location of this specific stabilizing interaction in a disulfide-bond-containing loop region of ribonuclease A results in the localized modulation of protein dynamics that, in turn, enhances the susceptibility of the disulfide bond to reduction leading to an alteration in the reductive unfolding behavior of the homologues. These results have important implications for folding studies involving topological determinants to obtain folding/unfolding rates and pathways, for protein structure-function prediction through fold recognition, and for predicting proteolytic cleavage sites
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