Reused Protein Segments Linked to Functional Dynamics.

IF 11 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Molecular biology and evolution Pub Date : 2024-09-04 DOI:10.1093/molbev/msae184
Yiğit Kutlu, Gabriel Axel, Rachel Kolodny, Nir Ben-Tal, Turkan Haliloglu
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Abstract

Protein space is characterized by extensive recurrence, or "reuse," of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.

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与功能动态相关的重复使用蛋白质片段
蛋白质空间的特点是部件的大量重复出现或 "重复使用",这表明新的蛋白质和结构域可以通过现有片段的混合和匹配而进化。从进化的角度来看,要使特定的组合持续存在,蛋白质片段不仅要在几何上匹配,还要在动态上相互沟通,以实现对功能至关重要的协同运动。来自蛋白质空间的证据支持这样一个前提,即结构域确实是以这种方式结合在一起的。为此,我们使用高斯网络模型(GNM)来计算所谓的软模式,即 150 个蛋白质结构域数据集的低频运动模式。运动模式可用于将一个结构域分解为连续的氨基酸片段,我们称之为 "动态元素",每个动态元素都属于以相反方式运动的两个部分之一。我们发现,在许多情况下,根据 GNM 分析检测到的动态元素与已确立的 "主题 "相对应:已被证明在蛋白质空间中重复出现的子域级片段,这些片段在以前的研究中仅使用序列相似性就能检测到(即完全独立于 GNM 分析)。这种统计学上的显著相关性暗示了动态进化的重要性。总体而言,研究结果与蛋白质的进化情景是一致的,即蛋白质从需要在几何和动力学上相互匹配的主题中产生,例如,为了促进异位调节。
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来源期刊
Molecular biology and evolution
Molecular biology and evolution 生物-进化生物学
CiteScore
19.70
自引率
3.70%
发文量
257
审稿时长
1 months
期刊介绍: Molecular Biology and Evolution Journal Overview: Publishes research at the interface of molecular (including genomics) and evolutionary biology Considers manuscripts containing patterns, processes, and predictions at all levels of organization: population, taxonomic, functional, and phenotypic Interested in fundamental discoveries, new and improved methods, resources, technologies, and theories advancing evolutionary research Publishes balanced reviews of recent developments in genome evolution and forward-looking perspectives suggesting future directions in molecular evolution applications.
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