Protein Sequence Selection Method That Enables Full Consensus Design of Artificial L-Threonine 3-Dehydrogenases with Unique Enzymatic Properties
Protein Sequence Selection Method That Enables Full Consensus Design of Artificial L-Threonine 3-Dehydrogenases with Unique Enzymatic Properties
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DOI：
10.1021/acs.biochem.0c00570
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发表时间：
2020-10-13
期刊：
影响因子：
2.9
通讯作者：
Ito, Sohei
中科院分区：
文献类型：
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作者：
Motoyama, Tomoharu;Hiramatsu, Nozomi;Ito, Sohei
指数级增长的蛋白质序列数据使得使用基于序列的蛋白质设计方法（包括全共识蛋白质设计（FCD））进行人工酶设计成为可能。人工酶设计的成功很大程度上取决于所使用序列的性质。因此，序列必须从数据库和精心准备的库中选择，以使FCD设计成功。在这项研究中，我们提出了一种选择方法，以几个关键残基作为序列基序。我们以l -苏氨酸3-脱氢酶（TDH）为模型来检验该方法的有效性。在分类中，4个残基（143、174、188和214）作为关键残基。我们将数千个TDH同源序列分为五组，其中包含数百个序列。利用文库中的序列，利用FCD设计了5个人工TDHs。其中，我们成功地以可溶性形式表达了四种。对人工TDHs的生化分析表明，其酶学性质存在差异；最大酶活性（t(1/2)）和活化能的一半分别分布在53 ~ 65℃和38 ~ 125 kJ/mol之间。人工TDHs具有不同的动力学参数。结构分析表明，一致突变主要发生在次级或外壳。人工TDHs的功能多样性是由于突变的积累影响了其物理化学性质。综上所述，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性质的人工酶。
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 (t(1/2)) and activation energies were distributed from 53 to 65 degrees 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.