Eastman P, Doniach S
Department of Applied Physics, Stanford University, California 94305-4090, USA.
Proteins. 1998 Feb 15;30(3):215-27.
We present an algorithm for simulating the long time scale dynamics of proteins and other macromolecules. Our method applies the concept of multiple time step integration to the diffusive Langevin equation, in which short time scale dynamics are replaced by friction and noise. The macromolecular force field is represented at atomic resolution. Slow motions are modeled by constrained Langevin dynamics with very large time steps, while faster degrees of freedom are kept in local thermal equilibrium. In the limit of a sufficiently large molecule, our algorithm is shown to reduce the CPU time required by two orders of magnitude. We test the algorithm on two systems, alanine dipeptide and bovine pancreatic trypsin inhibitor (BPTI), and find that it accurately calculates a variety of equilibrium and dynamical properties. In the case of BPTI, the CPU time required is reduced by nearly a factor of 60 compared to a conventional, unconstrained Langevin simulation using the same force field.
我们提出了一种用于模拟蛋白质和其他大分子长时间尺度动力学的算法。我们的方法将多时间步积分的概念应用于扩散朗之万方程，其中短时间尺度动力学由摩擦力和噪声取代。大分子力场以原子分辨率表示。慢运动通过具有非常大时间步长的约束朗之万动力学进行建模，而较快的自由度则保持在局部热平衡状态。在分子足够大的极限情况下，我们的算法显示可将所需的CPU时间减少两个数量级。我们在两个系统上测试了该算法，即丙氨酸二肽和牛胰蛋白酶抑制剂（BPTI），并发现它能准确计算各种平衡和动力学性质。在BPTI的情况下，与使用相同力场的传统无约束朗之万模拟相比，所需的CPU时间减少了近60倍。
