Essential dynamics:: A tool for efficient trajectory compression and management
Essential dynamics:: A tool for efficient trajectory compression and management
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DOI：
10.1021/ct050285b
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发表时间：
2006-03-01
影响因子：
5.5
通讯作者：
Orozco, M
中科院分区：
文献类型：
--
作者：
Meyer, T;Ferrer-Costa, C;Orozco, M
我们提出了一个简单的方法压缩和管理非常大的分子动力学轨迹。该方法是基于投影的笛卡尔快照收集沿着的轨迹到一个正交空间定义的特征向量通过对角化的协方差矩阵。当特征向量的数目等于3 N-6（N是原子的数目）时，变换在数学上是精确的，并且在实践中即使当特征向量的数目小得多时也是非常精确的，从而允许轨迹文件的大小的显著减小。此外，我们还研究了该方法的能力，当与插值相结合时，从更稀疏（低频）的数据中恢复密集的采样（以高频率收集的快照）作为进一步数据压缩的方法。最后，我们已经研究了使用该方法时，外推的系统的行为比原来的模拟周期更长的时间的可能性。总体而言，我们的研究结果表明，该方法是一个有吸引力的替代目前的方法，包括动态信息的静态结构文件，如那些存放在蛋白质数据库。
We present a simple method for compression and management of very large molecular dynamics trajectories. The approach is based on the projection of the Cartesian snapshots collected along the trajectory into an orthogonal space defined by the eigenvectors obtained by diagonalization of the covariance matrix. The transformation is mathematically exact when the number of eigenvectors equals 3N-6 (N being the number of atoms), and in practice very accurate even when the number of eigenvectors is much smaller, permitting a dramatic reduction in the size of trajectory files. In addition, we have examined the ability of the method, when combined with interpolation, to recover dense samplings (snapshots collected at a high frequency) from more sparse (lower frequency) data as a method for further data compression. Finally, we have investigated the possibility of using the approach when extrapolating the behavior of the system to times longer than the original simulation period. Overall our results suggest that the method is an attractive alternative to current approaches for including dynamic information in static structure files such as those deposited in the Protein Data Bank.