Shin J K, Jhon M S
Department of Chemistry, Korea Advanced Institute of Science and Technology, Seoul.
Biopolymers. 1991 Feb 5;31(2):177-85. doi: 10.1002/bip.360310206.
A high directional Monte Carlo procedure that predicts the topology of the energy hypersurface before it walks, is developed as a method to obtain a global energy minimum structure of polypeptides and proteins. It calculates its covariance matrix, which controls the individual trial step distribution of the next set of steps, from the second moment of the actual walk segment in the previous set. The method is successfully applied to the pentapeptide Metenkephalin system. And it is shown that some initial heating process, which provides the more flexible molecule, is necessary in order to overcome the energy barriers that can be overestimated by some biases in the empirical description of the system. The sampling efficiency, traced by an average conformational changes, is found to be at least 20 times greater than the one in the conventional Metropolis Monte Carlo methods, and it is expected that this increases in efficiency will be more prominent when the system is larger.
一种高定向蒙特卡罗方法被开发出来，用于在多肽和蛋白质的能量超曲面游走之前预测其拓扑结构，以此获得全局能量最小结构。该方法根据前一组实际游走片段的二阶矩计算协方差矩阵，协方差矩阵控制下一组步骤的单个试验步长分布。该方法成功应用于五肽脑啡肽系统。结果表明，为了克服系统经验描述中某些偏差可能高估的能量障碍，需要一些初始加热过程来提供更灵活的分子。通过平均构象变化追踪的采样效率比传统的 metropolis 蒙特卡罗方法至少高 20 倍，并且预计当系统更大时，这种效率的提高将更加显著。
