Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, Sorbonne Université, Muséum National d'Histoire Naturelle, CNRS UMR 7590, 75005 Paris, France.
Biophysics of Tropical Diseases Max Planck Tandem Group, University of Antioquia, 050010 Medellín, Colombia.
J Phys Chem Lett. 2022 Aug 18;13(32):7490-7496. doi: 10.1021/acs.jpclett.2c01807. Epub 2022 Aug 8.
Simulations with adaptive time-dependent bias enable an efficient exploration of the conformational space of a system. However, the dynamic information is altered by the bias. Infrequent metadynamics recovers the transition rate of crossing a barrier, if the collective variables are ideal and there is no bias deposition near the transition state. Unfortunately, these conditions are not always fulfilled. To overcome these limitations, and inspired by single-molecule force spectroscopy, we use Kramers' theory for calculating the barrier-crossing rate when a time-dependent bias is added to the system. We assess the parameter by measuring how efficiently the bias accelerates the transitions. We present approximate analytical expressions of the survival probability, reproducing the barrier-crossing time statistics and enabling the extraction of the unbiased transition rate even for challenging cases. We explore the limits of our method and provide convergence criteria to assess its validity.
自适应时变偏差模拟能够有效地探索系统的构象空间。然而，这种偏差会改变动态信息。如果集体变量是理想的，并且在过渡状态附近没有偏差沉积，那么不频繁的元动力学可以恢复跨越势垒的跃迁率。不幸的是，这些条件并不总是满足的。为了克服这些限制，受单分子力谱学的启发，我们在系统中添加时变偏差时，使用克拉默斯理论来计算势垒穿越率。我们通过测量偏差加速跃迁的效率来评估参数。我们提出了生存概率的近似解析表达式，再现了势垒穿越时间统计，并能够提取无偏跃迁率，即使对于具有挑战性的情况也是如此。我们探索了我们方法的局限性，并提供了收敛标准来评估其有效性。
