Department of Physics , Kansas State University , Manhattan , Kansas 66506 , United States.
J Phys Chem B. 2018 May 31;122(21):5567-5578. doi: 10.1021/acs.jpcb.7b11830. Epub 2018 Mar 9.
We present a simple model for the effect of amino acid sequences on amyloid fibril formation. Using the HP model we find the binding lifetimes of four simple sequences by solving the first passage time for the intermolecular H-bond reaction coordinate. We find that sequences with identical binding energies have widely varying binding times depending on where the aggregation prone amino acids are located in the sequence. In general, longer binding times occur when the aggregation prone amino acids are clustered in a single "hot spot". Similarly, binding times are shortened by clustering weakly bound residues. Both of these effects are explained by an increase in the multiplicity of unbinding trajectories that comes from adding weak binding residues. Our model predicts a transition from ordered to disordered fibrils as the concentration of monomers increases. We apply our model to Aβ, IAPP, and apomyoglobin using binding energy estimates derived from bioinformatics. We find that these sequences are highly selective of the in-register state. This selectivity arises from the having strongly bound segments of varying length and separation.
我们提出了一个简单的模型,用于研究氨基酸序列对淀粉样纤维形成的影响。使用 HP 模型,我们通过求解分子间氢键反应坐标的首次通过时间,找到了四个简单序列的结合寿命。我们发现,具有相同结合能的序列具有广泛变化的结合时间,具体取决于易于聚集的氨基酸在序列中的位置。一般来说,当易于聚集的氨基酸聚集在一个“热点”中时,结合时间会变长。类似地,通过聚集弱结合残基,结合时间会缩短。这两种效应都可以通过增加弱结合残基的解结合轨迹的多重性来解释。我们的模型预测,随着单体浓度的增加,从有序纤维到无序纤维的转变。我们使用从生物信息学中得出的结合能估计值,将我们的模型应用于 Aβ、IAPP 和脱辅基肌红蛋白。我们发现这些序列对同型纤维状态具有高度选择性。这种选择性来自于具有不同长度和分离的强烈结合片段。