Amyloid assembly is dominated by misregistered kinetic traps on an unbiased energy landscape
Amyloid assembly is dominated by misregistered kinetic traps on an unbiased energy landscape
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DOI：
10.1073/pnas.1911153117
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发表时间：
2020-05-12
影响因子：
11.1
通讯作者：
Chen, Jianhan
中科院分区：
文献类型：
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作者：
Jia, Zhiguang;Schmit, Jeremy D.;Chen, Jianhan
由于构象搜索的复杂性和长时间尺度，蛋白质原纤维形成的原子描述一直是难以捉摸的。在这里，我们开发了一个多尺度的方法，结合众多的原子模拟显式溶剂，构建马尔可夫状态模型（MSM）的原纤维生长。搜索注册完全绑定的原纤维状态建模为一个崎岖的二维能量景观定义的β-片对齐和氢键状态的随机行走，而涉及没有氢键的状态的转换来自动力学聚类。然后从MSM模拟计算传入肽的可逆缔合/解离和总体生长动力学。这种方法被应用于获得一个无参数的，全面的描述纤维伸长的A β（16-22），以及它是如何调制的苯丙氨酸-环己基丙氨酸（CHA）突变。轨迹显示了一种聚集机制，其中肽的大部分时间被困在由弱结合态t连接的错误记录的β折叠态中，寿命短。我们的研究结果概括了实验观察，突变体CHA 19和CHA 1920加速纤维伸长，但有一个相对较小的影响纤维生长的临界浓度。重要的是，突变的动力学后果来自于扰乱原纤维生长的生产性和非生产性途径网络的累积效应。这与非功能性状态不会进化出有效折叠路径的预期一致，因此需要随机搜索构型空间。这项研究强调了在研究蛋白质原纤维的伸长机制和动力学时描述完整能量景观的重要性。
Atomistic description of protein fibril formation has been elusive due to the complexity and long time scales of the conformational search. Here, we develop a multiscale approach combining numerous atomistic simulations in explicit solvent to construct Markov State Models (MSMs) of fibril growth. The search for the in-register fully bound fibril state is modeled as a random walk on a rugged two-dimensional energy landscape defined by beta-sheet alignment and hydrogen-bonding states, whereas transitions involving states without hydrogen bonds are derived from kinetic clustering. The reversible association/dissociation of an incoming peptide and overall growth kinetics are then computed from MSM simulations. This approach is applied to derive a parameter-free, comprehensive description of fibril elongation of A beta(16-22) and how it is modulated by phenylalanine-to-cyclohexylalanine (CHA) mutations. The trajectories show an aggregation mechanism in which the peptide spends most of its time trapped in misregistered beta-sheet states connected by weakly bound states twith short lifetimes. Our results recapitulate the experimental observation that mutants CHA19 and CHA1920 accelerate fibril elongation but have a relatively minor effect on the critical concentration for fibril growth. Importantly, the kinetic consequences of mutations arise from cumulative effects of perturbing the network of productive and nonproductive pathways of fibril growth. This is consistent with the expectation that nonfunctional states will not have evolved efficient folding pathways and, therefore, will require a random search of configuration space. This study highlights the importance of describing the complete energy landscape when studying the elongation mechanism and kinetics of protein fibrils.