Polizzi Karen M, Chaparro-Riggers Javier F, Vazquez-Figueroa Eduardo, Bommarius Andreas S
School of Chemical & Biomolecular Engineering, Parker H. Petit Institute of Bioengineering and Bioscience, Atlanta, GA 30332-0363, USA.
Biotechnol J. 2006 May;1(5):531-6. doi: 10.1002/biot.200600029.
The thermostabilization of penicillin G acylase (PGA) is a difficult problem due to the large size of the protein and its complex maturation process. We developed a data-driven protein design method that requires fewer homologous sequences than the traditional consensus approach and utilizes structural information to limit the number of variants created. Approximately 50% of our 21 single-point mutants were found experimentally to be more thermostable than the wild-type PGA, two had almost threefold longer half-life at 50 degrees C, with very little effect on activity. An analysis of four programs that predict the thermostability conferred by point mutations shows little agreement between the programs and with the experimental data, emphasizing that the chosen stabilizing mutations are very difficult to predict, but that our data-driven design method should prove useful.
由于青霉素G酰化酶（PGA）蛋白质体积大且成熟过程复杂，其热稳定性是一个难题。我们开发了一种数据驱动的蛋白质设计方法，该方法比传统的共识方法所需的同源序列更少，并利用结构信息来限制产生的变体数量。实验发现，我们的21个单点突变体中约50%比野生型PGA更耐热，其中两个在50摄氏度下的半衰期几乎延长了两倍，而对活性的影响很小。对四个预测点突变赋予热稳定性的程序的分析表明，这些程序之间以及与实验数据之间几乎没有一致性，这强调了所选的稳定突变很难预测，但我们的数据驱动设计方法应该会被证明是有用的。
