En route for molecular dynamics simulation of a living cell

IF 6.3 3区 综合性期刊 Q1 Multidisciplinary
Yibo Wang , Cong Zhang , Ke Tang , Xiaohui Wang
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引用次数: 0

Abstract

Creating an in silico all-atom whole-cell model for molecular dynamics (MD) simulation is one of the best ways to quantitatively understand the basic structure and function of cells in terms of the laws of physics and chemistry. The heavy use of graphics processing units (GPUs), the exponential growth of supercomputing power, and the emergence of MD simulation-specific supercomputers lay the groundwork for the MD simulation of molecular machinery. Moreover, the involvement of artificial intelligence (AI) will not only improve the accuracy of the simulation but also significantly accelerate the sampling efficiency. However, several underlying critical puzzles prevent in silico all-atom whole-cell modeling, which is the holy grail of MD simulation. From this perspective, we briefly reviewed the accomplishments of present techniques and hardware as well as provided insight to address the challenge of MD simulation of a living cell. With the rapid advancements in computational hardware, AI, and experimental cell biology, it would be possible to achieve this overarching goal.

Abstract Image

活体细胞分子动力学模拟途中
建立分子动力学(MD)模拟的全原子全细胞硅模型是根据物理和化学规律定量了解细胞基本结构和功能的最好方法之一。图形处理单元(gpu)的大量使用、超级计算能力的指数级增长以及专用于分子力学模拟的超级计算机的出现为分子力学的分子力学模拟奠定了基础。此外,人工智能(AI)的参与不仅可以提高模拟的准确性,还可以显着提高采样效率。然而,一些潜在的关键难题阻碍了硅全原子全细胞建模,这是MD模拟的圣杯。从这个角度来看,我们简要回顾了当前技术和硬件的成就,并提供了解决活细胞MD模拟挑战的见解。随着计算硬件、人工智能和实验细胞生物学的快速发展,实现这一总体目标是可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Fundamental Research
Fundamental Research Multidisciplinary-Multidisciplinary
CiteScore
4.00
自引率
1.60%
发文量
294
审稿时长
79 days
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