Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester School of Medicine & Dentistry, 601 Elmwood Avenue, Rochester, New York 14642, United States.
J Am Chem Soc. 2020 Nov 25;142(47):19835-19839. doi: 10.1021/jacs.0c09689. Epub 2020 Nov 10.
RNA recognition by proteins is central to biology. Here we demonstrate the existence of a recurrent structural motif, the "arginine fork", that codifies arginine readout of cognate backbone and guanine nucleobase interactions in a variety of protein-RNA complexes derived from viruses, metabolic enzymes, and ribosomes. Nearly 30 years ago, a theoretical arginine fork model was posited to account for the specificity between the HIV-1 Tat protein and TAR RNA. This model predicted that a single arginine should form four complementary contacts with nearby phosphates, yielding a two-pronged backbone readout. Recent high-resolution structures of TAR-protein complexes have unveiled new details, including () arginine interactions with the phosphate backbone and the major-groove edge of guanine and () simultaneous cation-π contacts between the guanidinium group and flanking nucleobases. These findings prompted us to search for arginine forks within experimental protein-RNA structures retrieved from the Protein Data Bank. The results revealed four distinct classes of arginine forks that we have defined using a rigorous but flexible nomenclature. Examples are presented in the context of ribosomal and nonribosomal interfaces with analysis of arginine dihedral angles and structural (suite) classification of RNA targets. When arginine fork chemical recognition principles were applied to existing structures with unusual arginine-guanine recognition, we found that the arginine fork geometry was more consistent with the experimental data, suggesting the utility of fork classifications to improve structural models. Software to analyze arginine-RNA interactions has been made available to the community.
蛋白质与 RNA 的相互作用在生物学中至关重要。在这里，我们展示了一种反复出现的结构基序，即“精氨酸叉”，它编码了各种蛋白质-RNA 复合物中精氨酸对同源骨架和鸟嘌呤核苷酸碱基相互作用的读取，这些复合物来自病毒、代谢酶和核糖体。大约 30 年前，提出了一个理论上的精氨酸叉模型，以解释 HIV-1 Tat 蛋白和 TAR RNA 之间的特异性。该模型预测，单个精氨酸应该与附近的磷酸基形成四个互补的接触，产生两个分叉的骨架读取。最近 TAR-蛋白复合物的高分辨率结构揭示了新的细节，包括 () 精氨酸与磷酸骨架和鸟嘌呤大沟边缘的相互作用，以及 () 胍基和相邻核苷酸碱基之间的同时阳离子-π 相互作用。这些发现促使我们在从蛋白质数据库中检索到的实验蛋白质-RNA 结构中搜索精氨酸叉。结果显示了四种不同类型的精氨酸叉，我们使用严格但灵活的命名法对其进行了定义。在核糖体和非核糖体界面的背景下，我们展示了这些结构的示例，并对精氨酸二面角和 RNA 靶标的结构（套件）分类进行了分析。当精氨酸叉的化学识别原理应用于具有异常精氨酸-鸟嘌呤识别的现有结构时，我们发现精氨酸叉的几何形状与实验数据更一致，这表明叉分类法可用于改进结构模型。用于分析精氨酸-RNA 相互作用的软件已提供给社区。
