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Novel Peptide-Mediated Interactions Derived from High-Resolution 3-Dimensional Structures

机译:高分辨率三维结构衍生的新型肽介导的相互作用。

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摘要

Many biological responses to intra- and extracellular stimuli are regulated through complex networks of transient protein interactions where a globular domain in one protein recognizes a linear peptide from another, creating a relatively small contact interface. These peptide stretches are often found in unstructured regions of proteins, and contain a consensus motif complementary to the interaction surface displayed by their binding partners. While most current methods for the de novo discovery of such motifs exploit their tendency to occur in disordered regions, our work here focuses on another observation: upon binding to their partner domain, motifs adopt a well-defined structure. Indeed, through the analysis of all peptide-mediated interactions of known high-resolution three-dimensional (3D) structure, we found that the structure of the peptide may be as characteristic as the consensus motif, and help identify target peptides even though they do not match the established patterns. Our analyses of the structural features of known motifs reveal that they tend to have a particular stretched and elongated structure, unlike most other peptides of the same length. Accordingly, we have implemented a strategy based on a Support Vector Machine that uses this features, along with other structure-encoded information about binding interfaces, to search the set of protein interactions of known 3D structure and to identify unnoticed peptide-mediated interactions among them. We have also derived consensus patterns for these interactions, whenever enough information was available, and compared our results with established linear motif patterns and their binding domains. Finally, to cross-validate our identification strategy, we scanned interactome networks from four model organisms with our newly derived patterns to see if any of them occurred more often than expected. Indeed, we found significant over-representations for 64 domain-motif interactions, 46 of which had not been described before, involving over 6,000 interactions in total for which we could suggest the molecular details determining the binding.
机译:许多对细胞内和细胞外刺激的生物学反应都通过复杂的瞬态蛋白质相互作用网络来调节,其中一种蛋白质的球状结构域可以识别另一种蛋白质的线性肽,从而形成相对较小的接触界面。这些肽段通常在蛋白质的非结构化区域中发现,并包含一个共有基序,该互补基序与其结合伴侣显示的相互作用表面互补。尽管目前大多数从头发现此类基序的方法都利用了它们在无序区域发生的趋势,但我们在这里的工作集中在另一种观察上:结合到其伴侣结构域后,基序采用明确定义的结构。确实,通过分析已知的高分辨率三维(3D)结构的所有肽介导的相互作用,我们发现该肽的结构可能具有与共有基序相同的特征,即使它们确实可以帮助鉴定目标肽与已建立的模式不匹配。我们对已知基序的结构特征的分析表明,与大多数其他相同长度的肽不同,它们倾向于具有特定的拉伸和伸长结构。因此,我们基于支持向量机实施了一种策略,该策略使用此功能以及有关结合界面的其他结构编码信息,以搜索已知3D结构的蛋白质相互作用的集合,并识别其中不被注意的肽介导的相互作用。只要有足够的信息,我们也就得出了这些相互作用的共有模式,并将我们的结果与已建立的线性基序模式及其结合域进行了比较。最后,为了对我们的识别策略进行交叉验证,我们用新近推导的模式扫描了来自四种模式生物的相互作用组网络,以查看它们是否比预期的发生频率更高。确实,我们发现了64个域-基序相互作用的显着过量表达,其中以前没有描述过46个,总共涉及6,000多个相互作用,我们可以建议确定结合的分子细节。

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