蛋白质折叠中多极小值问题的蒙特卡罗最小化方法。
Monte Carlo-minimization approach to the multiple-minima problem in protein folding.
作者信息
Li Z, Scheraga H A
机构信息
Baker Laboratory of Chemistry, Cornell University, Ithaca, NY 14853-1301.
出版信息
Proc Natl Acad Sci U S A. 1987 Oct;84(19):6611-5. doi: 10.1073/pnas.84.19.6611.
Abstract
A Monte Carlo-minimization method has been developed to overcome the multiple-minima problem. The Metropolis Monte Carlo sampling, assisted by energy minimization, surmounts intervening barriers in moving through successive discrete local minima in the multidimensional energy surface. The method has located the lowest-energy minimum thus far reported for the brain pentapeptide [Met5]enkephalin in the absence of water. Presumably it is the global minimum-energy structure. This supports the concept that protein folding may be a Markov process. In the presence of water, the molecules appear to exist as an ensemble of different conformations.
摘要
已开发出一种蒙特卡罗最小化方法来克服多极小值问题。在能量最小化的辅助下， metropolis蒙特卡罗采样跨越了多维能量表面上连续离散局部极小值之间的中间障碍。该方法找到了迄今为止在无水情况下脑五肽[Met5]脑啡肽报道的最低能量极小值。据推测，它是全局最小能量结构。这支持了蛋白质折叠可能是一个马尔可夫过程的概念。在有水的情况下，分子似乎以不同构象的集合形式存在。
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