Izaguirre J A, Sweet C R, Pande V S
Dept. of Computer Science and Engineering, Univ. of Notre Dame, Notre Dame, IN 46556, USA.
Pac Symp Biocomput. 2010:240-51. doi: 10.1142/9789814295291_0026.
Proteins and other macromolecules have coupled dynamics over multiple time scales (from femtosecond to millisecond and beyond) that make resolving molecular dynamics challenging. We present an approach based on periodically decomposing the dynamics of a macromolecule into slow and fast modes based on a scalable coarse-grained normal mode analysis. A Langevin equation is used to propagate the slowest degrees of freedom while minimizing the nearly instantaneous degrees of freedom. We present numerical results showing that time steps of up to 1000 fs can be used, with real speedups of up to 200 times over plain molecular dynamics. We present results of successfully folding the Fip35 mutant of WW domain.
蛋白质和其他大分子在多个时间尺度（从飞秒到毫秒及更长时间）上具有耦合动力学，这使得解析分子动力学具有挑战性。我们提出了一种基于可扩展粗粒度正常模式分析将大分子动力学周期性地分解为慢模式和快模式的方法。使用朗之万方程来传播最慢的自由度，同时最小化几乎瞬时的自由度。我们给出的数值结果表明，可以使用高达1000飞秒的时间步长，与普通分子动力学相比实际加速倍数高达200倍。我们展示了成功折叠WW结构域的Fip35突变体的结果。
