Theoretical and Computational Biophysics Group, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , 405 North Mathews Avenue, Urbana, Illinois 61801, United States.
Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7565, Université de Lorraine , B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France.
J Phys Chem B. 2017 Apr 20;121(15):3502-3514. doi: 10.1021/acs.jpcb.6b09350. Epub 2016 Nov 30.
Millisecond-scale conformational transitions represent a seminal challenge for traditional molecular dynamics simulations, even with the help of high-end supercomputer architectures. Such events are particularly relevant to the study of molecular motors-proteins or abiological constructs that convert chemical energy into mechanical work. Here, we present a hybrid-simulation scheme combining an array of methods including elastic network models, transition path sampling, and advanced free-energy methods, possibly in conjunction with generalized-ensemble schemes to deliver a viable option for capturing the millisecond-scale motor steps of biological motors. The methodology is already implemented in large measure in popular molecular dynamics programs, and it can leverage the massively parallel capabilities of petascale computers. The applicability of the hybrid method is demonstrated with two examples, namely cyclodextrin-based motors and V-type ATPases.
纳秒级构象转变是传统分子动力学模拟面临的一个重大挑战,即使借助高端超级计算机架构也是如此。这类事件对于研究分子马达(将化学能转化为机械能的蛋白质或非生物构建体)尤为重要。在此,我们提出了一种混合模拟方案,结合了一系列方法,包括弹性网络模型、跃迁路径采样和高级自由能方法,可能还结合了广义系综方案,为捕捉生物马达的纳秒级马达步骤提供了可行的选择。该方法已经在流行的分子动力学程序中得到了广泛的实现,并可以利用千万亿次级计算机的大规模并行能力。该混合方法的适用性通过两个实例得到了证明,即基于环糊精的马达和 V 型 ATP 酶。