Doctoral Program in Biology, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan.
Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.
J Chem Inf Model. 2024 Aug 26;64(16):6610-6622. doi: 10.1021/acs.jcim.4c00901. Epub 2024 Aug 16.
Protein conformations in cells are not solely determined by amino acid sequences; they also depend on cellular environments. For instance, the ribosome tunnel induces its specific α-helix formation during cotranslational folding. Owing to the link between these temporally α-helix and biological functions, the mechanism of α-helix formation inside the ribosome tunnel has been previously explored. Consequently, the conformational restrictions of the tunnel were considered one of the driving forces of α-helix formation. Conversely, the ribosomal tunnel environment, including its chemical properties, appears to influence the α-helix formation. However, a comprehensive analysis of the ribosome tunnel environment's impact on the α-helix formation has not been conducted yet due to challenges in experimentally controlling it. Therefore, as a new computational approach, we proposed a ribosome environment-mimicking model (REMM) based on the radius and components of the experimentally determined ribosome tunnel structures. Using REMM, we assessed the impact of the ribosome tunnel environment on α-helix formation. Herein, we employed carbon nanotubes (CNT) as a reference model alongside REMM because CNT reproduce conformational restrictions rather than the ribosome tunnel environment. Quantitatively, the ability to reproduce the α-helix of nascent peptides in the experimental structure was compared between the CNT and REMM using enhanced all-atom molecular dynamics simulations. Consequently, the REMM more accurately reproduced the α-helix of the nascent peptides than the CNT, highlighting the significance of the ribosome tunnel environment in α-helix formation. Additionally, we analyzed the properties of the peptide inside each model to reveal the mechanism of ribosome tunnel-specific α-helix formation. Consequently, we revealed that the chemical diversities of the tunnel are essential for the formation of backbone-to-backbone hydrogen bonds in the peptides. In conclusion, the ribosome tunnel environment, with the diverse chemical properties, drives its specific α-helix formation. By proposing REMM, we newly provide the technical basis for investigating the protein conformations in various cellular environments.
细胞中的蛋白质构象不仅取决于氨基酸序列，还取决于细胞环境。例如，核糖体隧道在共翻译折叠过程中诱导其特定的α-螺旋形成。由于这种暂时的α-螺旋与生物功能之间的联系，核糖体隧道内α-螺旋形成的机制已被前人探索过。因此，隧道的构象限制被认为是α-螺旋形成的驱动力之一。相反，核糖体隧道环境，包括其化学性质，似乎会影响α-螺旋的形成。然而，由于实验控制的挑战，尚未对核糖体隧道环境对α-螺旋形成的影响进行全面分析。因此，作为一种新的计算方法，我们提出了基于实验确定的核糖体隧道结构的半径和组成的核糖体环境模拟模型（REMM）。我们使用 REMM 评估了核糖体隧道环境对α-螺旋形成的影响。在这里，我们使用碳纳米管（CNT）作为参考模型和 REMM 一起，因为 CNT 再现构象限制而不是核糖体隧道环境。通过增强全原子分子动力学模拟，我们比较了 CNT 和 REMM 对实验结构中新生肽α-螺旋的重现能力。结果表明，REMM 比 CNT 更准确地重现了新生肽的α-螺旋，突出了核糖体隧道环境在α-螺旋形成中的重要性。此外，我们分析了每个模型中肽的性质，以揭示核糖体隧道特异性α-螺旋形成的机制。结果表明，隧道的化学多样性对于肽中骨干到骨干氢键的形成是必不可少的。总之，具有多样化化学性质的核糖体隧道环境驱动其特定的α-螺旋形成。通过提出 REMM，我们为研究各种细胞环境中的蛋白质构象提供了新的技术基础。
