Recent developments in sequencing and growth of bioinformatics resources provide us with vast depositories of protein network and single nucleotide polymorphism data. It allows us to re-examine, on a larger and more comprehensive scale, the relationship between protein-protein interactions and protein variability and evolutionary rates. This relationship has remained far from unambiguously resolved for quite a long time, reflecting shifting analysis approaches in the literature, and growing data availability. In this study, we utilized several public genomic databases to investigate this relationship in human, mouse, pig, chicken, and zebrafish. We observed strong non-linear relationship patterns (tending towards convex decreasing function shapes) between protein variability and the density of corresponding protein-protein interactions across all five species. To investigate further, we carried out stochastic simulations, modeling the interplay between protein connectivity and variability. Our results indicate that a simple negative linear correlation model, often suggested (or tacitly assumed) in the literature, as either a null or an alternative hypothesis, is not a good fit with the observed data. After considering different (but still relatively simple, and not overfitting) simulation models, we found that a convex decreasing protein variability-connectivity function (specifically, exponential decay) led to a much better fit with the real data. We conclude that simple correlation models might be inadequate for describing protein variability-connectivity interplay in vertebrates; they often tend towards false negatives (showing no more than marginal linear or rank correlation where there are in fact strong non-random patterns).

中文翻译：

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蛋白质-蛋白质相互作用与蛋白质变异性和脊椎动物进化速率之间的依赖性：观察到的关系和随机建模。

生物信息学资源测序和增长的最新发展为我们提供了大量蛋白质网络和单核苷酸多态性数据。它使我们能够从更大更全面的角度重新研究蛋白质-蛋白质相互作用与蛋白质变异性和进化速率之间的关系。很长时间以来，这种关系一直没有得到明确解决，这反映了文献中分析方法的变化以及数据可用性的增长。在这项研究中，我们利用了几个公共基因组数据库来研究人，小鼠，猪，鸡和斑马鱼之间的这种关系。我们观察到蛋白质变异性与所有五个物种之间相应的蛋白质-蛋白质相互作用的密度之间的强非线性关系模式（趋向于凸面递减的函数形状）。为了进一步研究，我们进行了随机模拟，对蛋白质连接性和变异性之间的相互作用进行了建模。我们的结果表明，在文献中通常建议（或默认假设）的简单负线性相关模型（作为原假设或替代假设）与观察到的数据不太吻合。在考虑了不同的（但仍然相对简单，并且不过度拟合）的仿真模型之后，我们发现凸的递减的蛋白质变异性-连通性函数（特别是指数衰减）导致与真实数据的拟合度更高。我们得出的结论是，简单的相关模型可能不足以描述脊椎动物中蛋白质变异性-连通性的相互作用。它们往往趋向于假阴性（在实际上存在很强的非随机模式的情况下，仅显示边缘线性或秩相关）。