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用于高效探索蛋白质β-折叠结构的集体变量:在SH3和GB1中的应用。

A Collective Variable for the Efficient Exploration of Protein Beta-Sheet Structures: Application to SH3 and GB1.

作者信息

Pietrucci Fabio, Laio Alessandro

机构信息

International School for Advanced Studies (SISSA-ISAS), via Beirut 2-4, I-34014 Trieste, Italy.

出版信息

J Chem Theory Comput. 2009 Sep 8;5(9):2197-201. doi: 10.1021/ct900202f. Epub 2009 Aug 4.

DOI:10.1021/ct900202f
PMID:26616604
Abstract

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).

摘要

我们引入了一类新的集体变量,其能够在蛋白质的全原子显式溶剂模拟中高效地形成β-折叠结构。通过这种方法,我们能够在单个复制品上使用元动力学系统地折叠一个16个残基的β-发夹。应用于56个残基的SH3和GB1蛋白表明,从伸展状态开始,在约100纳秒内可获得数十个包含超过30%β-折叠的结构,包括部分天然折叠结构。使用这些变量可能允许对中等大小的蛋白质进行具有精确显式溶剂描述的折叠。此外,它可能允许研究与疾病(如朊病毒和阿尔茨海默病)相关的错误折叠状态的存在,并研究β-聚集(淀粉样疾病)。

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