Predicting the folding pathway of engrailed homeodomain with a probabilistic roadmap enhanced reaction-path algorithm.
Predicting the folding pathway of engrailed homeodomain with a probabilistic roadmap enhanced reaction-path algorithm.
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DOI：
10.1529/biophysj.107.119214
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发表时间：
2008-03
影响因子：
3.4
通讯作者：
Da-Wei Li;Haijun Yang;Li Han;Shuanghong Huo
中科院分区：
文献类型：
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作者：
Da-Wei Li;Haijun Yang;Li Han;Shuanghong Huo
为了预测蛋白质折叠途径，我们提出了一种替代耗时的原子模型的动态模拟。我们取代了实际的动态模拟与变分优化的反应路径连接已知的初始和最终的蛋白质构象的方式，以最大限度地提高估计的反应通量或最小化的平均第一次通过时间在给定的温度下，称为MaxFlux。我们解决了MaxFlux全局优化问题，一个有效的图论方法，概率路线图方法（PRM）。我们采用CHARMM 19和EEF 1隐式溶剂化模型来描述蛋白质溶液。我们的MaxFlux-PRM的有效性证明了我们有前途的模拟结果上的enrailed同源结构域的折叠途径。我们的MaxFlux-PRM方法提供了直接的证据来支持以前报道的中间状态是一个真正的通路上的中间体，和CPU功率的需求是适度的。
To predict a protein-folding pathway, we present an alternative to the time-consuming dynamic simulation of atomistic models. We replace the actual dynamic simulation with variational optimization of a reaction path connecting known initial and final protein conformations in such a way as to maximize an estimate of the reactive flux or minimize the mean first passage time at a given temperature, referred to as MaxFlux. We solve the MaxFlux global optimization problem with an efficient graph-theoretic approach, the probabilistic roadmap method (PRM). We employed CHARMM19 and the EEF1 implicit solvation model to describe the protein solution. The effectiveness of our MaxFlux-PRM is demonstrated in our promising simulation results on the folding pathway of the engrailed homeodomain. Our MaxFlux-PRM approach provides the direct evidence to support that the previously reported intermediate state is a genuine on-pathway intermediate, and the demand of CPU power is moderate.