.png){kind=icon}
返回
Adaptive patch grid strategy for parallel protein folding using atomic burials with NAMD
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2024.104868.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The definition of protein structures is an important research topic in molecular biology currently, since there is a direct relationship between the function of the protein in the organism and the 3D geometric configuration it adopts. The transformations that occur in the protein structure from the 1D configuration to the 3D form are called protein folding. Ab initio protein folding methods use physical forces to model the interactions among the atoms that compose the protein. In order to accelerate those methods, parallel tools such as NAMD were proposed. In this paper, we propose two contributions for parallel protein folding simulations: (a) adaptive patch grid (APG) and (b) the addition of atomic burials (AB) to the traditional forces used in the simulation. With APG, we are able to adapt the simulation box (patch grid) to the current shape of the protein during the folding process. AB forces relate the 3D protein structure to its geometric center and are adequate for modeling globular proteins. Thus, adding AB to the forces used in parallel protein folding potentially increases the quality of the result for this class of proteins. APG and AB were implemented in NAMD and tested in supercomputer environments. Our results show that, with APG, we are able to reduce the execution time of the folding simulation of protein 4LNZ (5,714 atoms, 15 million time steps) from 12 hours and 36 minutes to 11 hours and 8 minutes, using 16 nodes (256 CPU cores). We also show that our APG+AB strategy was successfully used in a realistic protein folding simulation (1.7 billion time steps).
Keyword:
Protein folding
Parallel simulation
Atomic burials
期刊
IF:
4
论文数:
3.8K
被引数:
4.8K
机构
引用论文
Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
OAAI
.png){kind=icon}
OAAI分享收藏分享收藏Day-ahead Optimal Scheduling Strategy of Microgrid with EVs Charging Station含电动汽车充电站的微电网日前优化调度策略
PREAI
分享收藏
查看更多内容