Krüger Daniela, Ebenhan Jan, Werner Stefan, Bacia Kirsten
Institut für Chemie, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany.
Institut für Chemie, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany.
Biophys J. 2017 Sep 19;113(6):1311-1320. doi: 10.1016/j.bpj.2017.06.023. Epub 2017 Jul 8.
Fluorescence correlation spectroscopy has been previously used to investigate peptide and protein binding to lipid membranes, as it allows for very low amounts of sample, short measurement times and equilibrium binding conditions. Labeling only one of the binding partners, however, comes with certain drawbacks, as it relies on identifying binding events by a change in diffusion coefficient. Since peptide and protein aggregation can obscure specific binding, and since non-stoichiometric binding necessitates the explicit choice of a statistical distribution for the number of bound ligands, we additionally label the liposomes and perform dual-color fluorescence cross-correlation spectroscopy (dcFCCS). We develop a theoretical framework showing that dcFCCS amplitudes allow calculation of the degree of ligand binding and the concentration of unbound ligand, leading to a model-independent binding curve. As the degree of labeling of the ligands does not factor into the measured quantities, it is permissible to mix labeled and unlabeled ligand, thereby extending the range of usable protein concentrations and accessible dissociation constants, K. The total protein concentration, but not the fraction of labeled protein, needs to be known. In this work, we apply our dcFCCS analysis scheme to Sar1p, a protein of the COPII complex, which binds "major-minor-mix" liposomes. A Langmuir isotherm model yields K=(2.1±1.1)μM as the single-site dissociation constant. The dcFCCS framework presented here is highly versatile for biophysical analysis of binding interactions. It may be applied to many types of fluorescently labeled ligands and small diffusing particles, including nanodiscs and liposomes containing membrane protein receptors.
荧光相关光谱法此前已被用于研究肽和蛋白质与脂质膜的结合,因为它所需样品量极少、测量时间短且能实现平衡结合条件。然而,仅标记其中一个结合伙伴存在一定缺陷,因为它依赖于通过扩散系数的变化来识别结合事件。由于肽和蛋白质聚集会掩盖特异性结合,并且由于非化学计量结合需要明确选择结合配体数量的统计分布,我们额外标记脂质体并进行双色荧光交叉相关光谱法(dcFCCS)。我们建立了一个理论框架,表明dcFCCS振幅可用于计算配体结合程度和未结合配体的浓度,从而得到一个与模型无关的结合曲线。由于配体的标记程度不影响测量量,因此可以混合标记和未标记的配体,从而扩展了可用蛋白质浓度范围和可获得的解离常数K。需要知道的是总蛋白质浓度,而不是标记蛋白质的比例。在这项工作中,我们将dcFCCS分析方案应用于Sar1p,一种COPII复合物的蛋白质,它能结合“主-次-混合”脂质体。朗缪尔等温线模型得出K =(2.1±1.1)μM作为单位点解离常数。本文提出的dcFCCS框架在结合相互作用的生物物理分析方面具有高度通用性。它可应用于多种类型的荧光标记配体和小的扩散颗粒,包括纳米盘和含有膜蛋白受体的脂质体。