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首页> 外文期刊>BMC Bioinformatics >Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species
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Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species

机译:协同进化分析需要系统发育的深度比对和更好的空模型来准确检测物种内部和物种之间的蛋白质间接触

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摘要

When biomolecules physically interact, natural selection operates on them jointly. Contacting positions in protein and RNA structures exhibit correlated patterns of sequence evolution due to constraints imposed by the interaction, and molecular arms races can develop between interacting proteins in pathogens and their hosts. To evaluate how well methods developed to detect coevolving residues within proteins can be adapted for cross-species, inter-protein analysis, we used statistical criteria to quantify the performance of these methods in detecting inter-protein residues within 8 angstroms of each other in the co-crystal structures of 33 bacterial protein interactions. We also evaluated their performance for detecting known residues at the interface of a host-virus protein complex with a partially solved structure. Our quantitative benchmarking showed that all coevolutionary methods clearly benefit from alignments with many sequences. Methods that aim to detect direct correlations generally outperform other approaches. However, faster mutual information based methods are occasionally competitive in small alignments and with relaxed false positive rates. Two commonly used null distributions are anti-conservative and have high false positive rates in some scenarios, although the empirical distribution of scores performs reasonably well with deep alignments. We conclude that coevolutionary analysis of cross-species protein interactions holds great promise but requires sequencing many more species pairs.
机译:当生物分子发生物理相互作用时,自然选择会共同作用于它们。由于相互作用所施加的限制,蛋白质和RNA结构中的接触位置表现出相关的序列进化模式,并且病原体中的相互作用蛋白质与其宿主之间会发生分子竞争。为了评估开发的检测蛋白质中协同进化残基的方法可用于跨物种,蛋白质间分析的良好程度,我们使用统计学标准量化了这些方法在检测彼此之间8埃以内的蛋白质间残基中的性能。 33种细菌蛋白相互作用的共晶体结构。我们还评估了其检测具有部分解析结构的宿主病毒蛋白复合物界面处已知残基的性能。我们的定量基准测试表明,所有协同进化方法显然都受益于许多序列的比对。旨在检测直接相关性的方法通常优于其他方法。但是,基于快速互信息的方法有时在小规模比对和宽松的假阳性率方面具有竞争力。尽管分数的经验分布在深度比对中表现得相当好,但在某些情况下,两个常用的零值分布是反保守的并且具有较高的假阳性率。我们得出的结论是,跨物种蛋白质相互作用的协同进化分析具有很大的前景,但需要对更多的物种对进行测序。

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