温度复制交换分子动力学的应用:有丝分裂纺锤体相关蛋白SHE1的结构及其与动力蛋白的结合。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-05-20 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.05.024
Laleh Alisaraie, Oliver Stueker, Sayi'Mone Tati
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引用次数: 0

摘要

细胞骨架运动蛋白dynein属于AAA+ 超家族酶,作为一种机械化学atp酶,将化学能转化为力,驱动其沿微管逆行运动。Dynein负责细胞货物运输;然而,病毒颗粒也可以招募动力蛋白。动力蛋白突变在神经退行性和神经发育性疾病中也很重要。SHE1是酵母特异性mt相关蛋白,促进极化动力蛋白介导的纺锤体运动。与动力蛋白的接头蛋白不同,SHE1是唯一已知的抑制动力蛋白运动、独立于动力蛋白起作用并改变动力蛋白活性的蛋白。尽管SHE1具有独特的作用模式,但其结构尚未在实验中得到解决。本文介绍了利用温度复制交换分子动力学模拟获得的SHE1结构。所得到的结构被用来探索由SHE1结合动力蛋白和/或微管形成的复合物的构象。利用无监督机器学习K-means算法对计算蛋白质-蛋白质结合研究获得的复合物的构象进行聚类。这些结果有助于确定潜在的SHE1-动力蛋白相互作用位点和参与的氨基酸,并解释SHE1潜在抑制机制的结构细节。在SHE1-动力蛋白复合物中,SHE1的两个主要结合位点之一,其抑制机制可能是由于其干扰动力蛋白结构域(即杆-柄- mtbd)的远程变构通讯。在这种结合模式下,SHE1可以抑制电机环的AAA1/AAA4模块,影响其“开闭”构象变化。这表明SHE1可以直接干扰动力蛋白运动所必需的atp水解模块。在第二个观察到的结合位点,SHE1与MTBD、α-微管蛋白和β-微管蛋白的c端尾部(E-hook)相互作用,从而抑制MTBD与微管的高结合亲和力模式,阻止其运动,这与最近的体外实验数据一致。表征SHE1结构及其与SHE1-动力蛋白的复合物有助于设计和开发治疗性动力蛋白或其突变体的肽抑制剂,以治疗动力蛋白相关疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of temperature replica exchange molecular dynamics: Structure of mitotic spindle-associated protein SHE1 and its binding to dynein.

Cytoskeletal motor protein dynein belongs to the AAA+ superfamily of enzymes, functioning as a mechanochemical ATPase that converts chemical energy into force to drive its retrograde movements along microtubules. Dynein is responsible for cellular cargo transportation; however, viral particles can also recruit dynein. Dynein's mutation is also critical in neurodegenerative and neurodevelopmental diseases. SHE1 is a yeast-specific MT-associated protein that promotes polarizing dynein-mediated spindle movements. Unlike dynein's adaptor proteins, SHE1 is the only protein known to inhibit dynein motility, act independently from dynactin, and alter dynein activity. Despite SHE1's unique mode of action, its structure has not yet been solved experimentally. This work presents the SHE1 structure obtained using Temperature Replica Exchange Molecular Dynamics simulations. The resulting structure was used to explore the conformations of the complex formed by SHE1 binding to dynein and/or microtubule. The conformations of the complex obtained from the computational protein-protein binding study were clustered using the unsupervised machine learning K-means algorithm. The results helped identify the potential SHE1-dynein interaction sites and the participating amino acids, as well as explaining the structural details underlying SHE1's potential inhibitory mechanisms. In one of the two main recognized binding sites of SHE1 in the SHE1-dynein complexes, its inhibitory mechanism can be due to its interference with the long-range allosteric communications of dynein's domains, namely strut-stalk-MTBD. In that binding mode, SHE1 can restrain the AAA1/AAA4 modules of the motor ring, affecting its "open-closed" conformational changes. That suggests SHE1 could directly interfere with the ATP-hydrolyzing modules necessary for dynein motility. In the second observed binding site, SHE1 interacts with MTBD, α-tubulin, and the C-terminal tail of β-tubulin (E-hook) thereby inhibiting the high binding affinity mode of MTBD to microtubules preventing its motility, which aligns with recent in vitro experimental data. Characterizing the SHE1 structure and its complex with SHE1-dynein can aid in the design and development of therapeutic peptide inhibitors of dynein or its mutants for treating dynein-involved diseases.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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