Huang Liang-Tsung, Saraboji K, Ho Shinn-Ying, Hwang Shiow-Fen, Ponnuswamy M N, Gromiha M Michael
Institute of Information Engineering and Computer Science, Feng-Chia University, Taichung, 407, Taiwan.
Biophys Chem. 2007 Feb;125(2-3):462-70. doi: 10.1016/j.bpc.2006.10.009. Epub 2006 Nov 20.
Prediction of protein stability upon amino acid substitutions is an important problem in molecular biology and the solving of which would help for designing stable mutants. In this work, we have analyzed the stability of protein mutants using two different datasets of 1396 and 2204 mutants obtained from ProTherm database, respectively for free energy change due to thermal (DeltaDeltaG) and denaturant denaturations (DeltaDeltaG(H(2)O)). We have used a set of 48 physical, chemical energetic and conformational properties of amino acid residues and computed the difference of amino acid properties for each mutant in both sets of data. These differences in amino acid properties have been related to protein stability (DeltaDeltaG and DeltaDeltaG(H(2)O)) and are used to train with classification and regression tool for predicting the stability of protein mutants. Further, we have tested the method with 4 fold, 5 fold and 10 fold cross validation procedures. We found that the physical properties, shape and flexibility are important determinants of protein stability. The classification of mutants based on secondary structure (helix, strand, turn and coil) and solvent accessibility (buried, partially buried, partially exposed and exposed) distinguished the stabilizing/destabilizing mutants at an average accuracy of 81% and 80%, respectively for DeltaDeltaG and DeltaDeltaG(H(2)O). The correlation between the experimental and predicted stability change is 0.61 for DeltaDeltaG and 0.44 for DeltaDeltaG(H(2)O). Further, the free energy change due to the replacement of amino acid residue has been predicted within an average error of 1.08 kcal/mol and 1.37 kcal/mol for thermal and chemical denaturation, respectively. The relative importance of secondary structure and solvent accessibility, and the influence of the dataset on prediction of protein mutant stability have been discussed.
预测氨基酸替换后蛋白质的稳定性是分子生物学中的一个重要问题，解决这一问题将有助于设计稳定的突变体。在这项工作中，我们使用了分别从ProTherm数据库获得的1396个和2204个突变体的两个不同数据集，分析了蛋白质突变体的稳定性，分别针对热变性（ΔΔG）和变性剂变性（ΔΔG（H₂O））引起的自由能变化。我们使用了一组48种氨基酸残基的物理、化学能量和构象性质，并计算了两组数据中每个突变体氨基酸性质的差异。这些氨基酸性质的差异与蛋白质稳定性（ΔΔG和ΔΔG（H₂O））相关，并用于训练分类和回归工具以预测蛋白质突变体的稳定性。此外，我们使用4折、5折和10折交叉验证程序对该方法进行了测试。我们发现物理性质、形状和柔韧性是蛋白质稳定性的重要决定因素。基于二级结构（螺旋、链、转角和卷曲）和溶剂可及性（埋藏、部分埋藏、部分暴露和暴露）对突变体进行分类，对于ΔΔG和ΔΔG（H₂O）分别以81%和80%的平均准确率区分稳定/不稳定突变体。实验和预测稳定性变化之间的相关性，对于ΔΔG为0.61，对于ΔΔG（H₂O）为0.44。此外，对于热变性和化学变性，氨基酸残基替换引起的自由能变化预测平均误差分别为1.08千卡/摩尔和1.37千卡/摩尔。讨论了二级结构和溶剂可及性的相对重要性以及数据集对蛋白质突变体稳定性预测的影响。
