Li Da-Wei, Xie Mouzhe, Brüschweiler Rafael
Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States.
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.
J Am Chem Soc. 2020 Jun 17;142(24):10730-10738. doi: 10.1021/jacs.0c01885. Epub 2020 Jun 9.
Intrinsically disordered proteins (IDPs) can display a broad spectrum of binding modes and highly variable binding affinities when interacting with both biological and nonbiological materials. A quantitative model of such behavior is important for the better understanding of the function of IDPs when encountering inorganic nanomaterials with the potential to control their behavior and . Depending on their amino acid composition and chain length, binding properties can vary strongly between different IDPs. Moreover, due to differences in the physical chemical properties of clusters of amino acid residues along the IDP primary sequence, individual residues can adopt a wide range of bound state populations. Quantitative experimental binding affinities with synthetic silica nanoparticles (SNPs) at residue-level resolution, which were obtained for a set of IDPs by solution NMR relaxation experiments, are explained here by a first-principle analytical statistical mechanical model termed SILC. SILC quantitatively predicts residue-specific binding affinities to nanoparticles and it expresses binding cooperativity as the cumulative result of pairwise residue effects. The model, which was parametrized for anionic SNPs and applied to experimental data of four IDP systems with distinctive binding behavior, successfully predicts differences in overall binding affinities, fine details of IDP-SNP affinity profiles, and site-directed mutagenesis effects with a spatial resolution at the individual residue level. The SILC model provides an analytical description of such types of fuzzy IDP-SNP complexes and may help advance understanding nanotoxicity and targeting of IDPs by specifically designed nanomaterials.
内在无序蛋白(IDP)在与生物和非生物材料相互作用时,可表现出广泛的结合模式和高度可变的结合亲和力。对于更好地理解IDP在遇到具有控制其行为潜力的无机纳米材料时的功能而言,这种行为的定量模型很重要。根据其氨基酸组成和链长,不同IDP之间的结合特性可能有很大差异。此外,由于沿IDP一级序列的氨基酸残基簇的物理化学性质不同,单个残基可呈现出广泛的结合态群体。通过溶液核磁共振弛豫实验获得的一组IDP与合成二氧化硅纳米颗粒(SNP)在残基水平分辨率下的定量实验结合亲和力,在此由一个称为SILC的第一性原理分析统计力学模型进行解释。SILC定量预测残基对纳米颗粒的特异性结合亲和力,并将结合协同性表示为成对残基效应的累积结果。该模型针对阴离子SNP进行了参数化,并应用于四个具有独特结合行为的IDP系统的实验数据,成功预测了整体结合亲和力的差异、IDP-SNP亲和力图谱的精细细节以及在单个残基水平的空间分辨率下的定点诱变效应。SILC模型为此类模糊的IDP-SNP复合物提供了一种分析描述,并可能有助于推进对纳米毒性以及通过特定设计的纳米材料对IDP进行靶向作用的理解。