Rhee Young Min, Pande Vijay S
Department of Chemistry, Stanford University, Stanford California 94305-5080, USA.
Biophys J. 2003 Feb;84(2 Pt 1):775-86. doi: 10.1016/S0006-3495(03)74897-8.
Simulating protein folding thermodynamics starting purely from a protein sequence is a grand challenge of computational biology. Here, we present an algorithm to calculate a canonical distribution from molecular dynamics simulation of protein folding. This algorithm is based on the replica exchange method where the kinetic trapping problem is overcome by exchanging noninteracting replicas simulated at different temperatures. Our algorithm uses multiplexed-replicas with a number of independent molecular dynamics runs at each temperature. Exchanges of configurations between these multiplexed-replicas are also tried, rendering the algorithm applicable to large-scale distributed computing (i.e., highly heterogeneous parallel computers with processors having different computational power). We demonstrate the enhanced sampling of this algorithm by simulating the folding thermodynamics of a 23 amino acid miniprotein. We show that better convergence is achieved compared to constant temperature molecular dynamics simulation, with an efficient scaling to large number of computer processors. Indeed, this enhanced sampling results in (to our knowledge) the first example of a replica exchange algorithm that samples a folded structure starting from a completely unfolded state.
仅从蛋白质序列出发模拟蛋白质折叠热力学是计算生物学的一项重大挑战。在此，我们提出一种算法，可根据蛋白质折叠的分子动力学模拟计算正则分布。该算法基于副本交换方法，通过交换在不同温度下模拟的非相互作用副本克服动力学陷阱问题。我们的算法使用多路复用副本，在每个温度下进行多次独立的分子动力学运行。还尝试了这些多路复用副本之间的构型交换，使该算法适用于大规模分布式计算（即具有不同计算能力处理器的高度异构并行计算机）。我们通过模拟一个23个氨基酸的微型蛋白质的折叠热力学来证明该算法增强的采样能力。我们表明，与恒温分子动力学模拟相比，该算法实现了更好的收敛，并且能够高效扩展到大量计算机处理器。实际上，这种增强的采样（据我们所知）产生了第一个从完全未折叠状态开始采样折叠结构的副本交换算法实例。
