Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California.
Artie McFerrin Department of Chemical Engineering, Texas A&M College of Engineering, College Station, Texas.
Biophys J. 2023 Nov 21;122(22):4370-4381. doi: 10.1016/j.bpj.2023.10.016. Epub 2023 Oct 17.
The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent C⍺ model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.
TDP-43 是一种 RNA 结合蛋白,与 mRNA 从细胞核到细胞质的加工和运输有关。TDP-43 在细胞核中定位,同时在细胞质凝聚物(如应激颗粒)中积累。细胞质 TDP-43 的聚集和形成类似淀粉样纤维是许多神经退行性疾病的标志,在 >90%的肌萎缩侧索硬化症(ALS)患者中最为明显。目前尚不清楚细胞质 TDP-43 的过度积累是导致神经退行性变的原因,还是由其引起的。在这项工作中,我们使用多种分辨率的分子动力学模拟来探索 TDP-43 自我和交叉相互作用的动力学。我们从该蛋白功能域(N 端结构域和两个 RNA 识别结构域 RRM1 和 RRM2)的选择结构以及无序连接环和低复杂度甘氨酸丰富的 C 端结构域的建模构建了全长 TDP-43 的全原子 CHARMM36m 分子模型。单个 TDP-43 蛋白的全原子 CHARMM36m 模拟被用来构建 TDP-43 的粗粒化 Martini3 模型。Martini 模型和优化用于无序蛋白的更粗糙的隐溶剂 Cα 模型随后被用于探测 TDP-43 相互作用;来自单链全长 TDP-43 模拟的自相互作用、来自两个蛋白模拟的交叉相互作用以及来自数十个到数百个蛋白的组装模拟的交叉相互作用。我们的研究结果说明了不同建模尺度在获取 TDP-43 分子水平相互作用方面的实用性,并表明 TDP-43 具有多种相互作用偏好或模式,表现出整体较强但动态的关联,并驱动生物分子凝聚物的形成。