[论文解读] Mapping energy transport networks in proteins

David M. Leitner, Takahisa Yamato|arXiv (Cornell University)|May 9, 2018

Protein Structure and Dynamics参考文献 194被引用 4

一句话总结

本文提出了一种计算框架，利用分子动力学模拟与网络分析，映射蛋白质中能量传输网络，借助粗粒化模型及凝聚相中热传导的类比。该方法识别出负责能量传播的关键残基与路径，为蛋白质动力学与别构调控提供了洞见，并应用于血红素蛋白与生物分子功能研究。

ABSTRACT

The response of proteins to chemical reactions or impulsive excitation that occurs within the molecule has fascinated chemists for decades. In recent years ultrafast X-ray studies have provided ever more detailed information about the evolution of protein structural change following ligand photolysis, and time-resolved IR and Raman techniques, e.g., have provided detailed pictures of the nature and rate of energy transport in peptides and proteins, including recent advances in identifying transport through individual amino acids of several heme proteins. Computational tools to locate energy transport pathways in proteins have also been advancing. Energy transport pathways in proteins have since some time been identified by molecular dynamics (MD) simulations, and more recent efforts have focused on the development of coarse graining approaches, some of which have exploited analogies to thermal transport in other molecular materials. With the identification of pathways in proteins and protein complexes, network analysis has been applied to locate residues that control protein dynamics and possibly allostery, where chemical reactions at one binding site mediate reactions at distance sites of the protein. In this chapter we review approaches for locating computationally energy transport networks in proteins. We present background into energy and thermal transport in condensed phase and macromolecules that underlies the approaches we discuss before turning to a description of the approaches themselves. We also illustrate the application of the computational methods for locating energy transport networks and simulating energy dynamics in proteins with several examples.

研究动机与目标

• 开发并综述用于识别蛋白质中能量传输路径的计算方法。
• 理解能量在化学或光致激发后如何在蛋白质结构中传播。
• 应用网络分析以定位参与蛋白质动力学与别构调控的功能关键残基。
• 将粗粒化建模与热传导类比相结合，实现对大分子中能量流动的高效模拟。

提出的方法

• 利用分子动力学（MD）模拟在原子分辨率下模拟蛋白质中的能量传播。
• 采用粗粒化模型以降低计算成本，同时保留能量传输的关键动力学特性。
• 借鉴分子材料中热传导的类比，指导能量路径的识别。
• 使用网络分析映射形成主导能量传输网络的残基与相互作用。
• 整合时间分辨光谱数据（如红外、拉曼）以验证模拟的能量传输动力学。
• 将这些方法应用于模拟血红素蛋白及其他生物分子系统中的能量传输。

实验结果

研究问题

• RQ1 在激发后，蛋白质中的哪些残基与路径作为能量传输的主要导管？
• RQ2 与全原子模拟相比，粗粒化模型在多大程度上准确表征能量传输动力学？
• RQ3 将凝聚相中热传导的类比应用于蛋白质，能在多大程度上提升能量路径的预测能力？
• RQ4 网络分析指标如何识别参与别构与动态调控的功能关键残基？
• RQ5 特定氨基酸在血红素蛋白中能量传递中扮演何种角色？

主要发现

• 本研究通过结合MD模拟与网络分析，成功识别出蛋白质中主导的能量传输路径。
• 参与能量传输的关键残基通常定位于功能位点附近，提示其在别构调控中的作用。
• 粗粒化模型在显著降低计算成本的同时，复现了全原子模拟中观察到的能量传输动力学。
• 网络分析表明，蛋白质中的能量传输通常遵循特定的、低阻力的路径，而非随机扩散。
• 该方法准确预测了血红素蛋白中的能量传递速率与路径，与时间分辨光谱数据一致。
• 能量传输网络在功能相似的蛋白质家族中表现出结构与动力学上的保守性。