Browsing Publications of the research group Chemical Biology (CBIO) by Authors
Generation of novel-substrate-accepting biphenyl dioxygenases through segmental random mutagenesis and identification of residues involved in enzyme specificity.Zielinski, Marco; Kahl, Silke; Standfuss-Gabisch, Christine; Cámara, Beatriz; Seeger, Michael; Hofer, Bernd; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2006-03)Aryl-hydroxylating dioxygenases are of interest for the degradation of persistant aromatic pollutants, such as polychlorobiphenyls (PCBs), or as catalysts for the functionalization of aromatic scaffolds. In order to achieve dioxygenation of technical mixtures of PCBs, enzymes with broadened or altered substrate ranges are essential. To alter the substrate specificity of the biphenyl dioxygenase (BphA) of Burkholderia xenovorans LB400, we applied a directed evolution approach that used structure-function relationship data to target random mutageneses to specific segments of the enzyme. The limitation of random amino acid (AA) substitutions to regions that are critical for substrate binding and the exclusion of AA exchanges from positions that are essential for catalytic activity yielded enzyme variants of interest at comparatively high frequencies. After only a single mutagenic cycle, 10 beneficial variants were detected in a library of fewer than 1,000 active enzymes. Compared to the parental BphA, they showed between 5- and 200-fold increased turnover of chlorinated biphenyls, with substituent patterns that rendered them largely recalcitrant to attack by BphA-LB400. Determination of their sequences identified AAs that prevent the acceptance of specific PCBs by the wild-type enzyme, such as Pro334 and Phe384. The results suggest prime targets for subsequent cycles of BphA modification. Correlations with a three-dimensional model of the enzyme indicated that most of the exchanges with major influence on substrate turnover do not involve pocket-lining residues and had not been predictable through structural modeling.