蛋白质解折叠的拉伸分子动力学模拟效率优化

许超; 郑斌; 李森淼; 郑鹏

doi:10.11777/j.issn1000-3304.2024.24123

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蛋白质解折叠的拉伸分子动力学模拟效率优化

研究论文 | 更新时间：2024-12-24

- 蛋白质解折叠的拉伸分子动力学模拟效率优化
- Optimizing Efficiency for Steered Molecular Dynamics Simulations of Protein Unfolding
- 高分子学报 2024年55卷第11期页码：1608-1616
- 作者机构：
  
  南京大学化学与化工学院化学与生物医学创新中心配位化学国家重点实验室南京 210023
- 作者简介：
  
  E-mail: pengz@nju.edu.cn
- 基金信息：
  
  国家自然科学基金(基金号 22222703)
- DOI：10.11777/j.issn1000-3304.2024.24123
  中图分类号：
- CSTR：32057.14.GFZXB.2024.7266
- 收稿日期：2024-04-24，
  
  录用日期：2024-05-23，
  
  网络出版日期：2024-09-19，
  
  纸质出版日期：2024-11-20
- 稿件说明：
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许超, 郑斌, 李森淼, 郑鹏. 蛋白质解折叠的拉伸分子动力学模拟效率优化. 高分子学报, 2024, 55(11), 1608-1616

Xu, C.; Zheng, B.; Li, S. M.; Zheng, P. Optimizing efficiency for steered molecular dynamics simulations of protein unfolding. Acta Polymerica Sinica, 2024, 55(11), 1608-1616
许超, 郑斌, 李森淼, 郑鹏. 蛋白质解折叠的拉伸分子动力学模拟效率优化. 高分子学报, 2024, 55(11), 1608-1616 DOI： 10.11777/j.issn1000-3304.2024.24123. CSTR： 32057.14.GFZXB.2024.7266.

Xu, C.; Zheng, B.; Li, S. M.; Zheng, P. Optimizing efficiency for steered molecular dynamics simulations of protein unfolding. Acta Polymerica Sinica, 2024, 55(11), 1608-1616 DOI： 10.11777/j.issn1000-3304.2024.24123. CSTR： 32057.14.GFZXB.2024.7266.

摘要

拉伸分子动力学(SMD)模拟是揭示生物大分子在机械力作用下行为的一种重要计算方法，与蛋白质展开的单分子力谱实验技术相似. 尽管SMD模拟已经广泛应用，但由于模拟大分子系统的计算需求，研究范围受到限制. 最近计算机硬件的技术进步使得更广泛且经济的模拟成为可能. 本研究基于白细胞介素-6(IL-6)的解折叠过程，寻找使用GROMACS进行SMD模拟的最佳硬件配置. 研究表明，目前八核中央处理器(CPU)与一块图形处理器(GPU)的配置能提供最高效的性能. 此外，具有更高频率的CPU和更强FP32计算能力的GPU可以显著提升模拟效果. 此外，模拟体系原子数与模拟效率呈负相关，体系原子数小于1.2×10

时这种相关性较为明显. 本研究不仅明确了进行蛋白质展开的SMD模拟的最佳硬件设置，还将这种详细分子研究的可行性扩展到更广泛的研究中，为分子水平理解力学机制提供了一条更高效的途径，也为未来理解和研究更复杂的高分子在力学作用下的行为提供了重要基础.

Abstract

Steered Molecular Dynamics (SMD) simulations represent an important computational approach for uncovering the mechanistic behaviors of bio-macromolecules under mechanical forces

closely resembling experimental techniques such as single-molecule force spectroscopy for protein unfolding. Despite its widespread application

the computational intensity of simulating large molecular systems has traditionally constrained the scope of such studies. Recent technological advancements in computer hardware have now enabled more extensive and economically viable simulations. This study investigates the unfolding of Interleukin-6 (IL-6) to determine the optimal hardware configurations for SMD simulations using GROMACS. Our findings highlight that a configuration of eight CPU cores to one GPU yields the most efficient performance. Moreover

CPUs with higher clock speeds and GPUs with greater full precise float 32 calculation ability directly enhance simulation outcomes. We also examined the impact of atom count on simulation efficiency. Additionally

we identified the most suitable hardware for SMD simulation by analyzing the cost-effectiveness of the hardware involved in this article. Our research not only elucidates the optimal hardware setup for SMD simulations of protein unfolding but also extends the feasibility of such detailed molecular investigations to a broader research community

offering a pathway to more accessible and insightful mechanistic studies at the molecular level. This also provided an important foundation for understanding and studying the mechanical mechanisms of more complex polymer unfolding in the future.

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