Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi 530004, People's Republic of China.
Protein Eng Des Sel. 2010 Jan;23(1):35-42. doi: 10.1093/protein/gzp067.
Predicting the pH-activities of residues in proteins is an important problem in enzyme engineering and protein design. A novel predictor called 'Pred-pK(a)' was developed based on the physicochemical properties of amino acids and protein 3D structure. The Pred-pK(a) approach considers the influence of all other residues of the protein to predict the pK(a) value of an ionizable residue. An empirical equation was formulated, in which the pK(a) value was a distance-dependent function of physicochemical parameters of 20 amino acid types, describing their electrostatic and van der Waals interaction, as well as the effects of hydrogen bonds and solvation. Two sets of coefficients, {a(alpha)} and {b(l)}, were used in the predictor: {a(alpha)} is the weight factors of 20 amino acid types and {b(l)} is the weight factors of physicochemical properties of amino acids. An iterative double least square procedure was proposed to solve the two sets of weight factors alternately and iteratively in a training set. The two coefficient sets {a(alpha)} and {b(l)} thus obtained were used to predict the pK(a) values of residues in a protein. The average predictive error is +/-0.6 pH in less than a minute in common personal computer.
预测蛋白质中残基的 pH 值活性是酶工程和蛋白质设计中的一个重要问题。我们开发了一种称为“Pred-pK(a)”的新型预测器，它基于氨基酸的物理化学性质和蛋白质的 3D 结构。Pred-pK(a)方法考虑了蛋白质中所有其他残基的影响，以预测可电离残基的 pK(a)值。我们制定了一个经验公式，其中 pK(a)值是 20 种氨基酸类型物理化学参数的距离相关函数，描述了它们的静电和范德华相互作用，以及氢键和溶剂化的影响。该预测器使用了两组系数{a(alpha)}和{b(l)}：{a(alpha)}是 20 种氨基酸类型的权重因子，{b(l)}是氨基酸物理化学性质的权重因子。我们提出了一种迭代双最小二乘程序，用于在训练集中交替和迭代地求解两组权重因子。得到的这两组系数{a(alpha)}和{b(l)}用于预测蛋白质中残基的 pK(a)值。在普通个人计算机上，平均预测误差在不到一分钟内为 +/-0.6 pH。
