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多肽构象分析中的多极小值问题。III. 一种静电驱动的蒙特卡罗方法:对脑啡肽的测试。

The multiple-minima problem in the conformational analysis of polypeptides. III. An electrostatically driven Monte Carlo method: tests on enkephalin.

作者信息

Ripoll D R, Scheraga H A

机构信息

Baker Laboratory of Chemistry, Cornell University, Ithaca, New York 14853-1301.

出版信息

J Protein Chem. 1989 Apr;8(2):263-87. doi: 10.1007/BF01024949.

Abstract

The three-dimensional conformation of Met-enkephalin, corresponding to the lowest minimum of the empirical potential energy function ECEPP/2 (empirical conformational energy program for peptides), has been determined using a new algorithm, viz. the Electrostatically Driven Monte Carlo Method. This methodology assumes that a polypeptide or protein molecule is driven toward the native structure by the combined action of electrostatic interactions and stochastic conformational changes associated with thermal movements. These features are included in the algorithm that produces a Monte Carlo search in the conformational hyperspace of the polypeptide, using electrostatic predictions and a random sampling technique to locate low-energy conformations. In addition, we have incorporated an alternative mechanism that allows the structure to escape from some conformational regions representing metastable local energy minima and even from regions of the conformational space with great stability. In 33 test calculations on Met-enkephalin, starting from arbitrary or completely random conformations, the structure corresponding to the global energy minimum was found in all the cases analyzed, with a relatively small search of the conformational space. Some of these starting conformations were right or left-handed alpha-helices, characterized by good electrostatic interactions involving their backbone peptide dipoles; nevertheless, the procedure was able to convert such locally stable structures to the global-minimum conformation.

摘要

甲硫氨酸脑啡肽的三维构象对应于经验势能函数ECEPP/2(肽的经验构象能量程序)的最低最小值,已使用一种新算法即静电驱动蒙特卡罗方法确定。该方法假设多肽或蛋白质分子通过静电相互作用和与热运动相关的随机构象变化的联合作用被驱动至天然结构。这些特征包含在该算法中,该算法在多肽的构象超空间中进行蒙特卡罗搜索,利用静电预测和随机抽样技术来定位低能量构象。此外,我们纳入了一种替代机制,使结构能够从一些代表亚稳局部能量最小值的构象区域甚至从具有高度稳定性的构象空间区域逃逸。在对甲硫氨酸脑啡肽的33次测试计算中,从任意或完全随机的构象开始,在所有分析的案例中都找到了对应全局能量最小值的结构,且对构象空间的搜索相对较小。其中一些起始构象是右手或左手α螺旋,其特征是涉及主链肽偶极的良好静电相互作用;然而,该程序能够将此类局部稳定结构转化为全局最小构象。

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