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  • 1.
    Musumeci, Matías A
    et al.
    Centro para el Estudio de Sistemas Marinos, CONICET, Puerto Madryn, Argentina.
    Lozada, Mariana
    Centro para el Estudio de Sistemas Marinos, CONICET, Puerto Madryn, Argentina.
    Rial, Daniela V
    Universidad Nacional de Rosario, CONICET, Rosario, Argentina.
    Mac Cormack, Walter P
    Instituto Antártico Argentino, Ciudad Autónoma de Buenos Aires, Argentina / CONICET—Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina.
    Jansson, Janet K.
    Pacific Northwest National Laboratory, Richland, USA.
    Sjöling, Sara
    Södertörn University, School of Natural Sciences, Technology and Environmental Studies, Environmental Science.
    Carroll, JoLynn
    Fram—High North Research Centre for Climate and the Environment, Tromsø, Norway / UiT The Arctic University of Norway, Tromsø, Norway.
    Dionisi, Hebe M
    Centro para el Estudio de Sistemas Marinos, CONICET, Puerto Madryn, Argentina.
    Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach2017In: Marine Drugs, ISSN 1660-3397, E-ISSN 1660-3397, Vol. 15, no 4, article id 114Article in journal (Refereed)
    Abstract [en]

    The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

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