Automated selection of positions determining functional specificity of proteins by comparative analysis of orthologous groups in protein families

Automated selection of positions determining functional specificity of proteins by comparative analysis of orthologous groups in protein families
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DOI:
10.1110/ps.03191704
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发表时间:
2004-02-01
期刊:
影响因子:
8
通讯作者:
Rakhmaninova, AB
Rakhmaninova, AB
中科院分区:
生物学3区
文献类型:
--
作者:
Kalinina, OV;Mironov, AA;Rakhmaninova, AB

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越来越多的基因组数据为蛋白质功能分析开辟了新的可能性。我们介绍了一种方法,用于自动选择的残基,确定具有共同的一般功能的蛋白质的功能特异性(特异性决定位置[SDP]预测方法)。这些残基被认为在直向同源物组内是保守的(可以被认为具有相同的特异性),并且在旁系同源物之间变化。因此,考虑到被分成邻位组的蛋白质家族的多序列比对,可以选择氨基酸分布与该划分相关的位置。与以前公布的技术不同,引入的方法直接考虑到氨基酸取代频率的不均匀性。此外,它不需要设置任意阈值。相反,一个正式的阈值选择过程中使用的伯努利估计。我们测试了SDP预测方法的LacI家族的细菌转录因子和细菌的水和甘油转运属于主要内在蛋白(MIP)家族的样品。在这两种情况下,与现有的实验和结构数据的比较强烈支持我们的预测。
The increasing volume of genomic data opens new possibilities for analysis of protein function. We introduce a method for automated selection of residues that determine the functional specificity of proteins with a common general function (the specificity-determining positions [SDP] prediction method). Such residues are assumed to be conserved within groups of orthologs (that may be assumed to have the same specificity) and to vary between paralogs. Thus, considering a multiple sequence alignment of a protein family divided into orthologous groups, one can select positions where the distribution of amino acids correlates with this division. Unlike previously published techniques, the introduced method directly takes into account nonuniformity of amino acid substitution frequencies. In addition, it does not require setting arbitrary thresholds. Instead, a formal procedure for threshold selection using the Bernoulli estimator is implemented. We tested the SDP prediction method on the LacI family of bacterial transcription factors and a sample of bacterial water and glycerol transporters belonging to the major intrinsic protein (MIP) family. In both cases, the comparison with available experimental and structural data strongly supported our predictions.