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首页> 外文期刊>Journal of chemical theory and computation: JCTC >A Collective Variable for the Efficient Exploration of Protein Beta-Sheet Structures: Application to SH3 and GB1
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A Collective Variable for the Efficient Exploration of Protein Beta-Sheet Structures: Application to SH3 and GB1

机译:有效探索蛋白质β-片层结构的集体变量:在SH3和GB1中的应用

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We introduce a new class of collective variables which allow forming efficiently beta-sheet structures in all-atom explicit-solvent simulations of proteins. By this approach we are able to systematically fold a 16-residue beta hairpin using metadynamics on a single replica. Application to the 56-residue SH3 and GB1 proteins show that, starting from extended states, in ~100 ns tens of structures containing more than 30% beta-sheet are obtained, including parts of the native fold. Using these variables may allow folding moderate size proteins with an accurate explicit solvent description. Moreover, it may allow investigating the presence of misfolded states that are relevant for diseases (e.g., prion and Alzheimer) and studying beta-aggregation (amyloid diseases).
机译:我们引入了一类新的集体变量,这些变量允许在蛋白质的全原子显式溶剂模拟中有效形成β-折叠结构。通过这种方法,我们能够在单个副本上使用元动力学系统地折叠16个残基的β发夹。对具有56个残基的SH3和GB1蛋白的应用表明,从扩展状态开始,在约100 ns内可获得数十个包含超过30%β-sheet的结构,包括部分天然折叠。使用这些变量可以折叠具有准确明确溶剂描述的中等大小的蛋白质。而且,它可以允许调查与疾病(例如病毒和阿尔茨海默氏病)有关的错折叠状态的存在,并研究β-聚集(淀粉样疾病)。

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