Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.
Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.
复制标题
DOI：
10.1146/annurev-biophys-070816-033834
复制
发表时间：
2017-05-22
影响因子：
12.4
通讯作者：
Chong LT
中科院分区：
文献类型：
--
作者：
Zuckerman DM;Chong LT
加权集成(WE)方法协调了具有间歇性通信的准独立并行模拟运行，可以增强对罕见事件的采样，例如蛋白质构象变化、折叠和结合。WE策略可以实现超线性缩放--对诸如速率常数和平衡态布居等关键观测数据的无偏估计，其精度比普通并行模拟更高。我们的软件可用于控制任何动力学引擎，如标准分子动力学和细胞建模程序包。这篇文章回顾了WE的理论基础，并继续描述了它在一些复杂的生物学过程中的成功应用--蛋白质构象转变、(解)结合、组装过程以及系统生物学中的细胞尺度过程。我们进一步讨论了在我们方法学发展的下一阶段需要克服的挑战。总体而言，WE方法和软件的综合进步使得能够模拟长时间尺度的过程，否则在使用标准模拟的典型计算资源上是不实用的。
The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling—the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes—protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation.
登录
查看更多内容
影响因子：
3.4
作者：
Adelman, Joshua L.;Dale, Amy L.;Grabe, Michael
通讯作者：
Grabe, Michael
影响因子：
2.6
作者：
Au, SK;Beck, JL
通讯作者：
Beck, JL
影响因子：
4.4
作者：
Donovan, Rory M.;Sedgewick, Andrew J.;Zuckerman, Daniel M.
通讯作者：
Zuckerman, Daniel M.
影响因子：
4.4
作者：
Bhatt, Divesh;Bahar, Ivet
通讯作者：
Bahar, Ivet
影响因子：
4.4
作者：
Bhatt, Divesh;Zhang, Bin W.;Zuckerman, Daniel M.
通讯作者：
Zuckerman, Daniel M.