在线性疏水聚合物中崩过渡的优化集体变量:水化水和端到端距离的重要性
1School of Chemical Sciences, Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032, India.
Journal of chemical theory and computation
|September 10, 2024
概括
研究人员确定了补水是推动聚合物崩过渡的关键因素. 这一发现对于理解聚合物行为和开发生物分子模拟中增强的采样方法至关重要.
科学领域:
- 计算化学和生物物理学
- 聚合物的统计力学.
- 机器学习在分子动力学中的应用.
背景情况:
- 为生物分子过程选择合适的集体变量 (CV) 是一个挑战.
- 机器学习 (ML) 方法提供了新的方法来识别相关的简历.
- 了解聚合物崩过渡是聚合物科学的基础.
研究的目的:
- 用先进的计算技术研究聚合物崩过渡的机制.
- 确定支配这些转变的最关键的集体变量 (CVs).
- 开发和应用基于ML的管道来分析不同订单参数 (OP) 的作用.
主要方法:
- 在适应性采样轨迹上使用时间滞后的独立组件分析 (TICA).
- 构建了马尔科夫状态模型 (MSM),并进行了平均第一通道时间 (MFPT) 分析.
- 用人提交者分析和沙普利添加式扩展 (SHAP) 使用XGBoost回归.
主要成果:
- 旋转半径 (Rg) 和端到端距离被确定为良好顺序参数 (OP).
- 发现水 (Nw) 是崩过渡时间表和屏障的主要决定因素.
- ML分析证实Nw是加强塌过渡采样的关键坐标.
结论:
- 水 (Nw) 在决定线性疏水聚合物的崩过渡机制方面发挥着至关重要的作用.
- 虽然端到端距离有助于解决超稳定状态,但Nw对于探索实际崩过渡至关重要.
- 一个集成的ML管道 (XGBoost-SHAP) 有效地阐明了OP在过渡状态集群 (TSE) 的贡献.
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