Prediction of sequence signals for lipid post-translational modifications: Insights from case studies
Prediction of sequence signals for lipid post-translational modifications: Insights from case studies
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DOI：
10.1002/pmic.200300781
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发表时间：
2004-06-01
期刊：
影响因子：
3.4
通讯作者：
Neuberger, G
中科院分区：
文献类型：
--
作者：
Eisenhaber, B;Eisenhaber, F;Neuberger, G
翻译后修饰（PTM）的计算机注释技术对于为实验未表征的蛋白质序列生成具有生物学意义的描述是重要的。在先前对脂质PTMs的预测因素做出贡献后，我们总结了我们的方法学经验。而不是只寻找底物序列中的序列模式，一个策略，旨在创建一个通用的模型底物蛋白质/酶相互作用似乎更合适，因为已知的底物序列的数量很少，其中一些没有得到充分的实验验证。这种物理方法（与底物序列的单纯文本分析相反）还可以考虑其他异质生物数据（底物序列的突变、动力学数据、酶序列/结构），在评分函数中具有简单的分析表达式。几种脂质PTM以小序列区（具有明显的氨基酸类型偏好）的形式编码，所述小序列区通过具有许多构象柔性亲水残基的接头区连接至底物蛋白。由惩罚已知与生产性底物蛋白质/酶复合物不相容的序列性质的术语组成的评分函数基本上不选择不适当的查询。此外，我们估计的非冗余序列的数量与统计标准，在大多数情况下的PTM预测是无法达到的强大的配置文件计算所需的。最后，我们讨论了使用进化信息在评估预测的PTM的功能重要性的情况下，序列家族内的基序保守。
In silico annotation techniques for post-translational modifications (PTMs) are important to generate biologically meaningful descriptions for sequences of experimentally uncharacterized proteins. Having previously contributed with predictors for lipid PTMs, we summarize our methodological experience. Rather than only looking for the sequence pattern in substrate sequences, a strategy aimed at creating a generalized model of substrate protein/enzyme interaction appears more appropriate since the number of known substrate sequences is small, and some of them are not sufficiently verified experimentally. Such a physical approach (in contrast to a mere textual analysis of substrate sequences) can also take into account other, heterogeneous biological data (mutations of substrate sequences, kinetic data, enzyme sequences/structures) with simple analytical expressions in the score function. Several lipid PTMs are encoded in the form of a small sequence region (with pronounced amino acid type preferences) that is connected to the substrate protein by a linker region with many conformationally flexible, hydrophilic residues. A score function composed of terms penalizing sequence properties known to be incompatible with productive substrate protein/enzyme complexes essentially unselects inappropriate queries. Also, we estimate the number of nonredundant sequences necessary for robust profile computation with statistical criteria, a number that is not reached in most cases of PTM prediction. Finally, we discuss the usage of evolutionary information in evaluating the functional importance of predicted PTMs in cases of motif conservation within sequence families.