改善α-淀粉酶热稳定性的计算机辅助蛋白质表面修饰策略

Starch Pub Date : 2024-07-31 DOI:10.1002/star.202300288
Wenxin Zhai, Mengyu Zhu, Lin Lin, Wei Wei, Dongzhi Wei
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摘要

高温环境下的稳定性对于淀粉酶在以淀粉为基础的工业中发挥作用至关重要。本研究通过将 FoldX、PoPMuSiC、Discovery Studio 和 I-Mutant 2.0 等计算机辅助工具与保守序列分析相结合,开发了一种修饰蛋白质表面的方法。通过这种方法,对来自热葡糖酸副杆状芽孢杆菌(Parageobacillus thermoglucosidasius DSMZ 2542)的截短α-淀粉酶∆AmyPTG进行了合理设计,以提高其热稳定性。共构建了 7 个单位点变体,其中 5 个变体的热稳定性得到了增强。接着,构建了三个双位点变体,其中一个特别成功的双位点变体 N31RT213R 在 80 ℃ 下的半衰期延长了 4.3 倍。值得注意的是,N31RT213R 的比活性达到 10 567.16 U mg-1,高于 ∆AmyPTG(6645.43 U mg-1)。在玉米淀粉液化反应中,突变体 N31RT213R 得到的产物浓度约为 255.70 µg mL-1,高于 ∆AmyPTG 的 190.72 µg mL-1。对分子内作用力和表面静电荷进行了分析,以确定提高产量的可能原因。此外,还利用分子动力学模拟来分析整个蛋白质的柔性变化。事实证明,这种创新的理性工程方法是选择蛋白质热稳定性进化热点的成功策略,并有可能应用于其他酶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer‐Aided Protein Surface Modification Strategy to Improve the Thermostability of α‐Amylase
Stability under high‐temperature environments is crucial for amylase to function in starch‐based industries. This study develops a method of modifying protein surfaces by combining computer‐aided tools including FoldX, PoPMuSiC, Discovery Studio, and I‐Mutant 2.0 with conserved sequence analysis. A truncated α‐amylase ∆AmyPTG from Parageobacillus thermoglucosidasius DSMZ 2542 is rationally designed through this method to improve its thermostability. Seven single‐site variants are constructed and five of them displayed enhanced thermostability. Next, three double‐site variants are constructed with one particularly successful double‐site variant N31RT213R, exhibiting a 4.3‐fold longer half‐life at 80 °C. Notably, the specific activity of N31RT213R reaches 10 567.16 U mg−1, higher than ∆AmyPTG (6645.43 U mg−1). When applied to the corn starch liquefaction reaction, the mutant N31RT213R gets a higher yield of product concentration of about 255.70 µg mL−1, compared to 190.72 µg mL−1 for ∆AmyPTG. Intramolecular forces analysis and surface electrostatic charges analysis are conducted to determine possible causes for the improvement. Also, molecular dynamics simulation is used to analyze the flexibility shifts of the entire protein. This innovative rational engineering approach has proven to be a successful strategy for the selection of hot spots for protein thermostability evolution and has the potential to be applied to other enzymes.
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