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Dynamics of binding interactions of TDP‐43 and RNA: An equally weighted multiscale elastic network model study

核糖核酸 RNA结合蛋白 连接器 生物物理学 RNA剪接 分子动力学 结合位点 化学 计算生物学 结晶学 生物 细胞生物学 生物化学 计算机科学 计算化学 基因 操作系统
作者
Xueqing Deng,Shihao Wang,Zhongjie Han,Weikang Gong,Yang Liu,Chunhua Li
出处
期刊:Proteins [Wiley]
卷期号:90 (2): 589-600 被引量:2
标识
DOI:10.1002/prot.26255
摘要

Transactive response DNA binding protein 43 (TDP-43), an alternative-splicing regulator, can specifically bind long UG-rich RNAs, associated with a range of neurodegenerative diseases. Upon binding RNA, TDP-43 undergoes a large conformational change with two RNA recognition motifs (RRMs) connected by a long linker rearranged, strengthening the binding affinity of TDP-43 with RNA. We extend the equally weighted multiscale elastic network model (ewmENM), including its Gaussian network model (ewmGNM) and Anisotropic network model (ewmANM), with the multiscale effect of interactions considered, to the characterization of the dynamics of binding interactions of TDP-43 and RNA. The results reveal upon RNA binding a loss of flexibility occurs to TDP-43's loop3 segments rich in positively charged residues and C-terminal of high flexibility, suggesting their anchoring RNA, induced fit and conformational adjustment roles in recognizing RNA. Additionally, based on movement coupling analyses, it is found that RNA binding strengthens the interactions among intra-RRM β-sheets and between RRMs partially through the linker's mediating role, which stabilizes RNA binding interface, facilitating RNA binding efficiency. In addition, utilizing our proposed thermodynamic cycle method combined with ewmGNM, we identify the key residues for RNA binding whose perturbations induce a large change in binding free energy. We identify not only the residues important for specific binding, but also the ones critical for the conformational rearrangement between RRMs. Furthermore, molecular dynamics simulations are also performed to validate and further interpret the ENM-based results. The study demonstrates a useful avenue to utilize ewmENM to investigate the protein-RNA interaction dynamics characteristics.
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