MONTE-CARLO-MINIMIZATION APPROACH TO THE MULTIPLE-MINIMA PROBLEM IN PROTEIN FOLDING
MONTE-CARLO-MINIMIZATION APPROACH TO THE MULTIPLE-MINIMA PROBLEM IN PROTEIN FOLDING
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DOI：
10.1073/pnas.84.19.6611
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发表时间：
1987-10-01
影响因子：
11.1
通讯作者：
SCHERAGA, HA
中科院分区：
文献类型：
--
作者：
LI, ZQ;SCHERAGA, HA
为了克服多极值问题，提出了一种蒙特卡罗极小化方法。Metropolis蒙特卡罗抽样在能量最小化的辅助下，跨越了穿过多维能量面上连续的离散局部极小的中间障碍。该方法已经找到了到目前为止报道的大脑五肽脑啡肽在没有水的情况下的最低能量最小值。据推测，这就是全球最低能源结构。这支持了蛋白质折叠可能是一个马尔可夫过程的概念。在水的存在下，分子似乎以不同构象的系综形式存在。
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 appare to exist as an ensemble different conformations.