A Cooperative Model for Symmetric Ligand Binding to Protein Fibrils

IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Matthew S. Smith*, William F. DeGrado, Michael Grabe and Brian K. Shoichet, 
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引用次数: 0

Abstract

A hallmark of neurodegenerative diseases like Alzheimer’s Disease (AD) and chronic traumatic encephalopathy (CTE) is the presence of toxic protein aggregates in neurons. In AD and CTE specifically, the protein tau forms insoluble fibrils that are hundreds of nanometers in length. Intriguingly, recent experimental structures suggest that tau ligands like the disaggregator EGCG and positron emission tomography (PET) tracers like GTP-1 and MK-6240 bind to tau fibrils in long stacks reflecting the symmetry of the protein across many binding sites. In these stacks, each ligand makes more contact with its symmetry mates than it does with the protein. To interpret the binding of these molecules and new ligands, we must understand the effects of the cooperativity between sites and the entropy coming from the number of sites. Here, we investigate a nearest-neighbors model of cooperativity and use statistical mechanics to derive binding isotherms for saturation and competition experiments. This model allows us to relate measured EC50 and IC50 values to the intrinsic binding affinity to a single site and to cooperativity across sites in ways resembling the Cheng–Prusoff Equation. Depending on the degree of cooperativity between molecular species, this model permits solutions that lack the steep binding curves expected from cooperative systems and even solutions resembling 2-site systems. We finally consider conditions for a fibril’s detection in a PET scan and practical matters of fitting this model’s parameters to data.

Abstract Image

对称配体与蛋白原纤维结合的合作模型。
神经退行性疾病(如阿尔茨海默病(AD)和慢性创伤性脑病(CTE))的一个标志是神经元中存在有毒蛋白聚集体。特别是在AD和CTE中,tau蛋白形成长度为数百纳米的不溶性原纤维。有趣的是,最近的实验结构表明,tau配体(如分解物EGCG)和正电子发射断层扫描(PET)示踪剂(如GTP-1和MK-6240)以长堆叠的方式与tau原纤维结合,反映了蛋白质在许多结合位点上的对称性。在这些堆叠中,每个配体与对称配体的接触比与蛋白质的接触更多。为了解释这些分子和新配体的结合,我们必须了解位点之间的协同作用和来自位点数量的熵的影响。在这里,我们研究了合作的最近邻模型,并使用统计力学推导了饱和和竞争实验的结合等温线。该模型允许我们将测量的EC50和IC50值与单个位点的内在结合亲和力和跨位点的协同性联系起来,类似于Cheng-Prusoff方程。根据分子物种之间的合作程度,该模型允许解决缺乏合作系统所期望的陡峭结合曲线的解决方案,甚至类似于2位点系统的解决方案。最后,我们考虑了在PET扫描中检测纤维的条件以及将该模型的参数拟合到数据中的实际问题。
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来源期刊
Biochemistry Biochemistry
Biochemistry Biochemistry 生物-生化与分子生物学
CiteScore
5.50
自引率
3.40%
发文量
336
审稿时长
1-2 weeks
期刊介绍: Biochemistry provides an international forum for publishing exceptional, rigorous, high-impact research across all of biological chemistry. This broad scope includes studies on the chemical, physical, mechanistic, and/or structural basis of biological or cell function, and encompasses the fields of chemical biology, synthetic biology, disease biology, cell biology, nucleic acid biology, neuroscience, structural biology, and biophysics. In addition to traditional Research Articles, Biochemistry also publishes Communications, Viewpoints, and Perspectives, as well as From the Bench articles that report new methods of particular interest to the biological chemistry community.
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