Yesylevskyy S O, Demchenko A P
A.V. Palladin Institute of Biochemistry, Leontovicha Street 9, Kiev 01030, Ukraine.
Biophys Chem. 2004 Apr 1;109(1):17-40. doi: 10.1016/j.bpc.2003.10.001.
Collective motions and the formation of clusters of residues play an important role in the folding of real proteins. However, existing Monte Carlo (MC) techniques of the protein folding simulations based on highly popular lattice models provide only a schematic representation of collective motions, which is rather far from physical reality. The Clustering Monte Carlo (CMC) algorithm was developed with particular aim to provide a realistic description of collective motions on the lattice. CMC allows modeling the cluster dynamics and the effects of the solvent viscosity, which is impossible in conventional algorithms. In this study two 2D lattice peptides, with the ground states of hierarchical and non-hierarchical design, were investigated comparatively using three methods: Metropolis MC with the local move set, Metropolis MC with unspecific rigid rotations and the CMC algorithm. We present evidence that the folding pathways and kinetics of hierarchically folding clustered sequence are not adequately described in conventional MC simulations, and the account for cluster dynamics provided by CMC allows to capture essential features of the folding process. Our data suggest that the methods, which enable specific cluster motions, such as CMC, should be used for a more realistic description of protein folding.
残基的集体运动和簇的形成在真实蛋白质的折叠过程中起着重要作用。然而，基于广受欢迎的晶格模型的现有蛋白质折叠模拟的蒙特卡罗（MC）技术仅提供了集体运动的示意性表示，这与物理现实相差甚远。聚类蒙特卡罗（CMC）算法的开发旨在特别提供对晶格上集体运动的现实描述。CMC允许对簇动力学和溶剂粘度的影响进行建模，这在传统算法中是不可能的。在本研究中，使用三种方法对具有层次化和非层次化设计基态的两种二维晶格肽进行了比较研究：具有局部移动集的Metropolis MC、具有非特定刚性旋转的Metropolis MC和CMC算法。我们提供的证据表明，传统MC模拟中没有充分描述层次化折叠簇序列的折叠途径和动力学，而CMC提供的簇动力学解释能够捕捉折叠过程的基本特征。我们的数据表明，能够实现特定簇运动的方法，如CMC，应该用于更真实地描述蛋白质折叠。
