Revving up a Designed Copper Nitrite Reductase Using Noncoded Active Site Ligands

Herein, we report a three-stranded coiled-coil (3SCC) de novo protein containing a type II copper center (CuT2) composed of six-membered ring N-heterocycles. This design yields the most active homogeneous copper nitrite reductase (CuNiR) mimic in water. We achieved this result by controlling three factors. First, previous studies with N-delta- and N-epsilon-methyl histidine had indicated that a ligand providing pyridine-like electronic character to the copper site was superior to the more donating N-delta for nitrite reduction. By substitution of the parent histidine with the noncoded amino acids pyridyl alanine (3 '-pyridine [3 ' Py] vs 4 '-pyridine [4 ' Py]), an authentic pyridine donor was employed without the complications of the coupling of both electronic and tautomeric effects of histidine or methylated histidine. Second, by changing the position of the nitrogen atom within the active site (4 '-pyridine vs 3 '-pyridine) a doubling of the enzyme's catalytic efficiency resulted. This effect was driven by exclusivity by substrate binding to the copper site. Third, we replaced the leucine layer adjacent to the active site with an alanine, and the disparity between the 3 ' Py and 4 ' Py became more apparent. The decreased steric bulk minimally impacted the 3 ' Py derivative; however, the 4 ' Py K-m decreased by an order of magnitude (600 mM to 50 mM), resulting in a 40-fold enhancement in the k(cat)/K-m compared to the analogous histidine site and a 1500-fold improvement compared with the initially reported CuNiR catalyst of this family, TRIW-H. When combined with XANES/EXAFS data, the relaxing of the Cu(I) site to a more two-coordinate Cu(I)-like structure in the resting state increases the overall catalytic efficiency of nitrite reduction via the lowering of K-m. This study illustrates how by combining advanced spectroscopic methods, detailed kinetic analysis, and a broad toolbox of amino acid side chain functionality, one can rationally design systems that optimize biomimetic catalysis.