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首页> 外文期刊>The journal of physical chemistry, C. Nanomaterials and interfaces >Oligomerization Alters Binding Affinity between Amyloid Beta and a Modulator of Peptide Aggregation
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Oligomerization Alters Binding Affinity between Amyloid Beta and a Modulator of Peptide Aggregation

机译:寡聚化改变淀粉样蛋白β与肽聚集的调节剂之间的结合亲和力

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The soluble oligomeric form of the amyloid beta (A beta) peptide is the major causative agent in the molecular pathogenesis of Alzheimer's disease (AD). We have previously developed a pyrroline-nitroxyl fluorene compound (SLF) that blocks the toxicity of A beta. Here we introduce the multiparametric surface plasmon resonance (MP-SPR) approach to quantify SLF binding and its effect on the self-association of the peptide via a label-free, real-time approach. Kinetic analysis of SLF binding to A beta and measurements of layer thickness alterations inform on the mechanism underlying the ability of SLF to inhibit A beta toxicity and its progression toward larger oligomeric assemblies. Depending on the oligomeric state of A beta, distinct binding affinities for SLF are revealed. The A beta monomer and dimer uniquely possess subnanomolar affinity for SLF via a nonspecific mode of binding. SLF binding is weaker in oligomeric A beta, which displays an affinity for SLF on the order of 100 mu M. To complement these experiments we carried out molecular docking and molecular dynamics simulations to explore how SLF interacts with the A beta peptide. The MP-SPR results together with in silico modeling provide affinity data for the SLF-A beta interaction and allow us to develop a new general method for examining protein aggregation.
机译:淀粉样蛋白β(β)肽的可溶性低聚形式是Alzheimer疾病分子发病机制(AD)中的主要致病剂。我们以前开发过吡咯啉 - 硝基芴化合物(SLF),其阻断β的毒性。在这里,我们介绍了通过可标记的实时方法来量化SLF结合及其对肽自相关的影响的多次表面等离子体共振(MP-SPR)方法。 SLF结合对β的β和测量层厚度改变的动力学分析,介绍了SLF抑制β毒性的能力的机制及其对较大低聚组件的进展。取决于β的低聚状态,揭示了SLF的不同结合亲和力。 β单体和二聚体通过非特异性的结合模式唯一地对SLF具有对SLF的亚甲醛亲和力。 SLF结合在低聚Aβ中较弱,其对SLF的SLF大约为100μm的亲和力。为了补充这些实验,我们进行了分子对接和分子动力学模拟,以探讨SLF如何与β肽相互作用。 MP-SPR结果与Silico建模一起为SLF-Aβ相互作用提供亲和力数据,并允许我们开发一种用于检查蛋白质聚集的新方法。

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