计算机科学
构象异构
采样(信号处理)
可视化
聚类分析
子空间拓扑
算法
数据挖掘
计算科学
人工智能
化学
计算机视觉
分子
滤波器(信号处理)
有机化学
作者
Burak Kaynak,She Zhang,İvet Bahar,Pemra Doruker
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2021-07-03
卷期号:37 (21): 3956-3958
被引量:17
标识
DOI:10.1093/bioinformatics/btab496
摘要
Abstract Summary Efficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace. Availability and implementation ClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy. Supplementary information Supplementary data are available at Bioinformatics online.
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