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    Identification of putative drug targets and annotation of unknown proteins in Tropheryma whipplei

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    Authors
    Palanisamy, Navaneethan
    Affiliation
    University of Heidelberg
    Publication Date
    2018-06-09
    
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    Abstract
    Tropheryma whipplei (T. whipplei) is the causative agent of Whipple's disease and blood culture-negative endocarditis. Due to the variability of symptoms, the disease is often poorly diagnosed. Treatment for this bacterial infection is often lengthy, and improper uptake of antibiotics has resulted in relapses in many patients. In the present study, using available bioinformatic tools and databases such as the Cluster Database at High Identity with Tolerance (CD-HIT), the Basic Local Alignment Search Tool for proteins (BLASTp), the Database of Essential Genes (DEG), and the DrugBank database, 13 putative drug targets were identified in T. whipplei by subtractive genome analysis that could be targeted with currently available drugs (experimental or approved). Further, a 3D model was generated for one of these putative drug targets, the T. whipplei DNA ligase, and in silico docking was performed with pyridochromanone and adenosine-derived inhibitors using the AutoDock Vina. Additionally, many of the T. whipplei protein sequences in the National Center for Biotechnology Information (NCBI) protein database were unknown/uncurated. Using available web servers e.g. the KEGG Automatic Annotation Server (KAAS), the BLASTp, the Conserved Domain Architecture Retrieval Tool (CDAT) and the Protein families (Pfam), the function/remote/domain homology for nearly 80% of these uncurated protein sequences were annotated. The data obtained in the present study will aid physicians and researchers alike in curbing this bacterial infection.
    Citation
    Palanisamy, N. (2018). Identification of putative drug targets and annotation of unknown proteins in Tropheryma whipplei. Computational Biology and Chemistry, 76, 130-138. https://doi.org/10.1016/j.compbiolchem.2018.05.024
    Publisher
    Elsevier
    Journal
    Computational Biology and Chemistry
    URI
    http://hdl.handle.net/10034/629477
    DOI
    10.1016/j.compbiolchem.2018.05.024
    Additional Links
    https://www.sciencedirect.com/science/article/pii/S1476927117300634
    Type
    Article
    Language
    en
    ISSN
    1476-9271
    EISSN
    1476-928X
    Sponsors
    N/A
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.compbiolchem.2018.05.024
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    Chester Medical School

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