College of Physical Science and Technology, Central China Normal University, Hubei, China; Computational Science Program, University of Texas at El Paso, El Paso, Texas.
Computational Science Program, University of Texas at El Paso, El Paso, Texas.
Biophys J. 2024 Sep 3;123(17):2740-2748. doi: 10.1016/j.bpj.2023.12.024. Epub 2023 Dec 30.
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions that are bound or restricted at the Ncd-tubulin dimer binding interfaces. To consider the ion effects, widely used implicit solvent models treat ions implicitly in the continuous solvent environment without focusing on the individual ions' effects. But highly charged biomolecules such as the Ncd and tubulin dimer may capture some ions at highly charged regions as bound ions. Such bound ions are restricted to their binding sites; thus, they can be treated as part of the biomolecules. By applying multiscale computational methods, including the machine-learning-based Hybridizing Ions Treatment-2 program, molecular dynamics simulations, DelPhi, and DelPhiForce, we studied the interaction between the Ncd motor domain and the tubulin dimer using a hybrid solvent model, which considers the bound ions explicitly and the other ions implicitly in the solvent environment. To identify the importance of treating bound ions explicitly, we also performed calculations using the implicit solvent model without considering the individual bound ions. We found that the calculations of the electrostatic features differ significantly between those of the hybrid solvent model and the pure implicit solvent model. The analyses show that treating bound ions at highly charged regions explicitly is crucial for electrostatic calculations. This work proposes a machine-learning-based approach to handle the bound ions using the hybrid solvent model. Such an approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules, such as DNA/RNA, viral capsid proteins, etc.
果蝇 Ncd 蛋白是在纺锤体组织中发挥重要作用的马达蛋白。Ncd 和微管二聚体带高电荷。因此，研究 Ncd-微管二聚体相互作用在离子存在下的情况至关重要，特别是那些结合或限制在 Ncd-微管二聚体结合界面上的离子。为了考虑离子的影响，广泛使用的隐式溶剂模型在连续溶剂环境中隐式处理离子，而不关注单个离子的影响。但是，像 Ncd 和微管二聚体这样的带高电荷的生物分子可能会在带高电荷的区域捕获一些结合离子。这些结合离子被限制在它们的结合位点；因此，它们可以被视为生物分子的一部分。通过应用多尺度计算方法，包括基于机器学习的混合离子处理 2 程序、分子动力学模拟、DelPhi 和 DelPhiForce，我们使用混合溶剂模型研究了 Ncd 运动域与微管二聚体之间的相互作用，该模型明确考虑了结合离子，并在溶剂环境中隐式考虑了其他离子。为了确定明确处理结合离子的重要性，我们还使用不考虑单个结合离子的隐式溶剂模型进行了计算。我们发现，混合溶剂模型和纯隐式溶剂模型的静电特征计算结果差异显著。分析表明，在带高电荷的区域明确处理结合离子对于静电计算至关重要。这项工作提出了一种基于机器学习的方法，使用混合溶剂模型处理结合离子。这种方法不仅能够处理驱动蛋白-微管复合物，还适用于其他带高电荷的生物分子，如 DNA/RNA、病毒衣壳蛋白等。
