Calzadiaz-Ramirez Liliana, Calvó-Tusell Carla, Stoffel Gabriele M M, Lindner Steffen N, Osuna Sílvia, Erb Tobias J, Garcia-Borràs Marc, Bar-Even Arren, Acevedo-Rocha Carlos G
Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany.
Institut de Química Computacional i Catàlisi and Departament de Química, Universitat de Girona, Carrer Maria Aurèlia Capmany 69, Girona 17003, Catalonia, Spain.
ACS Catal. 2020 Jul 17;10(14):7512-7525. doi: 10.1021/acscatal.0c01487. Epub 2020 Jun 8.
The efficient regeneration of cofactors is vital for the establishment of biocatalytic processes. Formate is an ideal electron donor for cofactor regeneration due to its general availability, low reduction potential, and benign byproduct (CO). However, formate dehydrogenases (FDHs) are usually specific to NAD, such that NADPH regeneration with formate is challenging. Previous studies reported naturally occurring FDHs or engineered FDHs that accept NADP, but these enzymes show low kinetic efficiencies and specificities. Here, we harness the power of natural selection to engineer FDH variants to simultaneously optimize three properties: kinetic efficiency with NADP, specificity toward NADP, and affinity toward formate. By simultaneously mutating multiple residues of FDH from sp. 101, which exhibits practically no activity toward NADP, we generate a library of >10 variants. We introduce this library into an strain that cannot produce NADPH. By selecting for growth with formate as the sole NADPH source, we isolate several enzyme variants that support efficient NADPH regeneration. We find that the kinetically superior enzyme variant, harboring five mutations, has 5-fold higher efficiency and 14-fold higher specificity in comparison to the best enzyme previously engineered, while retaining high affinity toward formate. By using molecular dynamics simulations, we reveal the contribution of each mutation to the superior kinetics of this variant. We further determine how nonadditive epistatic effects improve multiple parameters simultaneously. Our work demonstrates the capacity of selection to identify highly proficient enzyme variants carrying multiple mutations which would be almost impossible to find using conventional screening methods.
辅因子的高效再生对于生物催化过程的建立至关重要。甲酸因其普遍可得性、低还原电位和良性副产物(CO),是辅因子再生的理想电子供体。然而,甲酸脱氢酶(FDHs)通常对NAD具有特异性,因此利用甲酸进行NADPH再生具有挑战性。先前的研究报道了天然存在的或经过工程改造的可接受NADP的FDHs,但这些酶的动力学效率和特异性较低。在这里,我们利用自然选择的力量对FDH变体进行工程改造,以同时优化三个特性:对NADP的动力学效率、对NADP的特异性以及对甲酸的亲和力。通过同时突变来自sp. 101的FDH的多个残基(该酶对NADP几乎没有活性),我们生成了一个包含超过10个变体的文库。我们将这个文库导入一个不能产生NADPH的菌株中。通过选择以甲酸作为唯一NADPH来源的生长方式,我们分离出了几种支持高效NADPH再生的酶变体。我们发现,具有五个突变的动力学上更优的酶变体,与之前工程改造的最佳酶相比,效率高5倍,特异性高14倍,同时对甲酸保持高亲和力。通过使用分子动力学模拟,我们揭示了每个突变对该变体卓越动力学的贡献。我们进一步确定了非加性上位效应如何同时改善多个参数。我们的工作证明了选择能够识别携带多个突变的高度熟练的酶变体,而使用传统筛选方法几乎不可能找到这些变体。