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Abstract：
Exponentially increasing protein sequence data enables artificial enzyme design using sequence-based protein design methods, including full-consensus protein design (FCD). The success of artificial enzyme design is strongly dependent on the nature of the sequences used. Hence, sequences must be selected from databases and curated libraries prepared to enable a successful design by FCD. In this study, we proposed a selection approach regarding several key residues as sequence motifs. We used l-threonine 3-dehydrogenase (TDH) as a model to test the validity of this approach. In the classification, four residues (143, 174, 188, and 214) were used as key residues. We classified thousands of TDH homologous sequences into five groups containing hundreds of sequences. Utilizing sequences in the libraries, we designed five artificial TDHs by FCD. Among the five, we successfully expressed four in soluble form. Biochemical analysis of artificial TDHs indicated that their enzymatic properties vary; half of the maximum measured enzyme activity (t1/2) and activation energies were distributed from 53 to 65 °C and from 38 to 125 kJ/mol, respectively. The artificial TDHs had unique kinetic parameters, distinct from one another. Structural analysis indicates that consensus mutations are mainly introduced in the secondary or outer shell. The functional diversity of the artificial TDHs is due to the accumulation of mutations that affect their physicochemical properties. Taken together, our findings indicate that our proposed approach can help generate artificial enzymes with unique enzymatic properties.
摘要：
指数增加的蛋白质序列数据使得能够使用基于序列的蛋白质设计方法进行人工酶设计,包括全共识蛋白设计（FCD）。人工酶设计的成功在很大程度上取决于所用序列的性质。因此，必须从数据库中选择序列，并准备好精选的文库，以使FCD能够成功设计。在这项研究中,我们提出了一种将几个关键残基作为序列基序的选择方法。我们使用1-苏氨酸3-脱氢酶（TDH）作为模型来测试这种方法的有效性。在分类中,四个残基(143,174,188和214)用作关键残基.我们将数千个TDH同源序列分类为包含数百个序列的五组。利用文库中的序列，我们由FCD设计了五个人造TDHs。在这五个人中,我们成功表达了四种可溶形式。人工TDHs的生化分析表明其酶学性质不同；最大测量酶活性的一半（t1/2）和活化能分布在53至65°C和38至125kJ/mol之间，分别。人工TDHs具有独特的动力学参数，彼此不同。结构分析表明，共有突变主要在二级或外壳中引入。人工TDHs的功能多样性是由于影响其物理化学性质的突变的积累。一起来看,我们的研究结果表明，我们提出的方法可以帮助产生具有独特酶学性质的人工酶。
