Correlated substitution analysis and the prediction of amino acid structural contacts
Correlated substitution analysis and the prediction of amino acid structural contacts
复制标题
DOI：
10.1093/bib/bbm052
复制
发表时间：
2008-01-01
影响因子：
9.5
通讯作者：
Pesole, Graziano
中科院分区：
文献类型：
--
作者：
Horner, David S.;Pirovano, Walter;Pesole, Graziano
长期以来，人们一直怀疑相关氨基酸取代的分析应该揭示成熟蛋白质结构中空间上邻近的位点对或簇。因此，基于不同的数学原理，如信息论，相关系数和最大似然的方法已被开发，以确定共同进化的氨基酸从多个序列比对。其行为通过这些方法鉴定为相关的成对位点的集合通常显著富集在空间上接近的残基对中。然而，相对高水平的假阳性预测通常使这些方法孤立地在蛋白质结构的从头预测中几乎没有用处。误导性信号（或显著性水平估计的问题）可能由同源序列之间的系统发育相关性和由于空间接近性以外的因素（例如，空间上不接近但涉及蛋白质共同功能特性的位点的相关性）引起。近年来，一些工作者建议，相关取代的信息应该与其他信息来源（二级结构，溶剂可及性，进化速率）相结合，以减少假阳性预测的比例。我们回顾了相关氨基酸取代的检测方法，比较了它们在接触预测中的相对性能，并预测了该领域的未来发展方向。
It has long been suspected that analysis of correlated amino acid substitutions should uncover pairs or clusters of sites that are spatially proximal in mature protein structures. Accordingly, methods based on different mathematical principles such as information theory, correlation coefficients and maximum likelihood have been developed to identify co-evolving amino acids from multiple sequence alignments. Sets of pairs of sites whose behaviour is identified by these methods as correlated are often significantly enriched in pairs of spatially proximal residues. However, relatively high levels of false-positive predictions typically render such methods, in isolation, of little use in the ab initio prediction of protein structure. Misleading signal (or problems with the estimation of significance levels) can be caused by phylogenetic correlations between homologous sequences and from correlation due to factors other than spatial proximity (for example, correlation of sites which are not spatially close but which are involved in common functional properties of the protein). In recent years, several workers have suggested that information from correlated substitutions should be combined with other sources of information (secondary structure, solvent accessibility, evolutionary rates) in an attempt to reduce the proportion of false-positive predictions. We review methods for the detection of correlated amino acid substitutions, compare their relative performance in contact prediction and predict future directions in the field.