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dc.contributor.authorPanter, Fabian
dc.contributor.authorKrug, Daniel
dc.contributor.authorBaumann, Sascha
dc.contributor.authorMüller, Rolf
dc.date.accessioned2018-06-29T07:57:34Z
dc.date.available2018-06-29T07:57:34Z
dc.date.issued2018-06-07
dc.identifier.issn2041-6520
dc.identifier.pmid29910943
dc.identifier.doi10.1039/c8sc01325j
dc.identifier.urihttp://hdl.handle.net/10033/621416
dc.description.abstractThere is astounding discrepancy between the genome-inscribed production capacity and the set of known secondary metabolite classes from many microorganisms as detected under laboratory cultivation conditions. Genome-mining techniques are meant to fill this gap, but in order to favor discovery of structurally novel as well as bioactive compounds it is crucial to amend genomics-based strategies with selective filtering principles. In this study, we followed a self-resistance guided approach aiming at the discovery of inhibitors of topoisomerase, known as valid target in both cancer and antibiotic therapy. A common host self-defense mechanism against such inhibitors in bacteria is mediated by so-called pentapeptide repeat proteins (PRP). Genes encoding the biosynthetic machinery for production of an alleged topoisomerase inhibitor were found on the basis of their collocation adjacent to a predicted PRP in the genome of the myxobacteriumen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.titleSelf-resistance guided genome mining uncovers new topoisomerase inhibitors from myxobacteria.en_US
dc.typeArticleen_US
dc.contributor.departmentHIPS, Helmholtz-Institute für pharmazeutische Forschung Saarland, Universitätscampus E8.1, 66123 Saarbrücken, Germany.en_US
refterms.dateFOA2018-06-29T07:57:34Z
dc.source.journaltitleChemical science


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