Lyman Edward, Zuckerman Daniel M
Department of Computational Biology, School of Medicine, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Biophys J. 2006 Jul 1;91(1):164-72. doi: 10.1529/biophysj.106.082941. Epub 2006 Apr 14.
Assessing the convergence of a biomolecular simulation is an essential part of any careful computational investigation, because many fundamental aspects of molecular behavior depend on the relative populations of different conformers. Here we present a physically intuitive method to self-consistently assess the convergence of trajectories generated by molecular dynamics and related methods. Our approach reports directly and systematically on the structural diversity of a simulation trajectory. Straightforward clustering and classification steps are the key ingredients, allowing the approach to be trivially applied to systems of any size. Our initial study on met-enkephalin strongly suggests that even fairly long trajectories (approximately 50 ns) may not be converged for this small--but highly flexible--system.
评估生物分子模拟的收敛性是任何严谨的计算研究的重要组成部分，因为分子行为的许多基本方面取决于不同构象异构体的相对丰度。在此，我们提出一种物理直观的方法，用于自洽地评估由分子动力学及相关方法生成的轨迹的收敛性。我们的方法直接且系统地报告模拟轨迹的结构多样性。简单的聚类和分类步骤是关键要素，使得该方法能够轻松应用于任何规模的系统。我们对甲硫氨酸脑啡肽的初步研究强烈表明，对于这个小而高度灵活的系统，即使是相当长的轨迹（约50纳秒）也可能未达到收敛。
