Nakai K, Kidera A, Kanehisa M
Institute for Chemical Research, Kyoto University, Japan.
Protein Eng. 1988 Jul;2(2):93-100. doi: 10.1093/protein/2.2.93.
The relationship among 222 published indices representing various physicochemical and biochemical properties of amino acid residues has been investigated by hierarchical cluster analysis. The clustering result is illustrated by the minimum spanning tree, which is conveniently divided into four regions: alpha and turn propensities, beta propensity, hydrophobicity and other physicochemical properties including, among others, bulkiness of amino acid residues. In addition, several subclasses of hydrophobicity scales have been identified: preference of inside and outside, accessible surface area, surrounding hydrophobicity and other mostly experimental scales including transfer free energy, partition coefficients, HPLC parameters and polarity. Representative amino acid indices are identified in each of these groups. The collection of amino acid indices is a useful resource for empirical analyses correlating sequence information with structural and functional properties of proteins. As an example, the indices that best reproduce the amino acid mutation data matrix are searched against this collection.
通过层次聚类分析研究了代表氨基酸残基各种物理化学和生化特性的222个已发表指数之间的关系。聚类结果由最小生成树表示，它可方便地分为四个区域：α螺旋和转角倾向、β折叠倾向、疏水性以及包括氨基酸残基体积等在内的其他物理化学特性。此外，还确定了疏水性标度的几个子类：内外偏好、可及表面积、周围疏水性以及其他主要是实验性的标度，包括转移自由能、分配系数、高效液相色谱参数和极性。在这些组中的每一组中都确定了代表性的氨基酸指数。氨基酸指数的集合是将序列信息与蛋白质的结构和功能特性相关联的实证分析的有用资源。例如，在此集合中搜索最能重现氨基酸突变数据矩阵的指数。
