【摘要】 α-淀粉酶在许多工业领域中均有广泛应用,但大多数α-淀粉酶必须改造才能满足苛刻的温度条件,因此α-淀粉酶温度改造的蛋白质工程已经开始。通过对酶的理性设计可以创造新的酶。这一技术实现,依赖于两大技术的发明,即基因工程中的定点诱变技术和生物信息学。在本文中,构建了α-淀粉酶序列库和α-淀粉酶温度序列库。通过对α-淀粉酶温度序列库进行多元回归分析,得到预测α-淀粉酶的最适温度的方程。预测了α-淀粉酶的最适温度,相关系数为0．959 71。分析方程中各种氨基酸系数,发现:半胱氨酸对α-淀粉酶最适温度影响最大。极性氨基酸影响强;大多数氨基酸会降低α-淀粉酶的最适温度。这些信息将有助于α-淀粉酶的温度改造工程。更多还原

【Abstract】 Alpha-amylases have found widespread use in industrial processes. But most alpha-araylase must be improved for temperature conditions. Protein engineering studies of temperature-activity profiles have been initiated. Rational design of enzyme will create a new enzyme for use. The way depended on two inventions: one is site-directed mutagenesis; another is bioinformatics. In this paper, built the alpha-amylase’s bank and alpha-amylase’s temperature -sequence bank. The multiple linear regression models were used to al-pha-amylase’s temperature a-sequence bank with method of least squares. Got the predicting equation. Predicted alpha-amylase optimal temperature. Its correlation coefficient is 0. 959 71. So it is feasible to predict optimal temperature of alpha-amylase by percent of amino acid. Analyze amino acid coefficient in equation, found that result. Ammo acid of the greatest influence coefficient is cysteine. Polar amino acid has great influence to alpha-amylase optimal temperature. Most amino acids decrease alpha-amylase optimal temperature. These will help alpha-amylase protein engineering of temperature a-activity.更多还原