Knudsen B, Miyamoto M M
Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, Building 090, DK-8000 Arhus C, Denmark.
Proc Natl Acad Sci U S A. 2001 Dec 4;98(25):14512-7. doi: 10.1073/pnas.251526398.
Changes in protein function can lead to changes in the selection acting on specific residues. This can often be detected as evolutionary rate changes at the sites in question. A maximum-likelihood method for detecting evolutionary rate shifts at specific protein positions is presented. The method determines significance values of the rate differences to give a sound statistical foundation for the conclusions drawn from the analyses. A statistical test for detecting slowly evolving sites is also described. The methods are applied to a set of Myc proteins for the identification of both conserved sites and those with changing evolutionary rates. Those positions with conserved and changing rates are related to the structures and functions of their proteins. The results are compared with an earlier Bayesian method, thereby highlighting the advantages of the new likelihood ratio tests.
蛋白质功能的变化会导致作用于特定残基的选择发生变化。这通常可以通过所讨论位点的进化速率变化检测到。本文提出了一种用于检测特定蛋白质位置进化速率变化的最大似然法。该方法确定速率差异的显著性值，为分析得出的结论提供可靠的统计基础。还描述了一种用于检测缓慢进化位点的统计检验。这些方法应用于一组Myc蛋白，以识别保守位点和进化速率发生变化的位点。那些具有保守和变化速率的位置与其蛋白质的结构和功能相关。将结果与早期的贝叶斯方法进行比较，从而突出新似然比检验的优势。
