Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900 Lugano, Ticino, Switzerland.
J Chem Phys. 2018 Nov 21;149(19):194113. doi: 10.1063/1.5053566.
Many processes of scientific importance are characterized by time scales that extend far beyond the reach of standard simulation techniques. To circumvent this impediment, a plethora of enhanced sampling methods has been developed. One important class of such methods relies on the application of a bias that is a function of a set of collective variables specially designed for the problem under consideration. The design of good collective variables can be challenging and thereby constitutes the main bottle neck in the application of these methods. To address this problem, recently we have introduced Harmonic Linear Discriminant Analysis, a method to systematically construct collective variables as linear combinations of a set of descriptors. The method uses input information that can be gathered in short unbiased molecular dynamics simulations in which the system is trapped in the metastable states. Here, to scale up our examination of the method's efficiency, we applied it to the folding of chignolin in water. Interestingly, already before any biased simulations were run, the constructed one-dimensional collective variable revealed much of the physics that underlies the folding process. In addition, using it in metadynamics, we were able to run simulations in which the system goes from the folded state to the unfolded one and back, where to get fully converged results, we combined metadynamics with parallel tempering. Finally, we examined how the collective variable performs when different sets of descriptors are used in its construction.
许多具有重要科学意义的过程的时间尺度远远超出了标准模拟技术的范围。为了克服这一障碍，已经开发了大量的增强采样方法。这类方法中的一类重要方法依赖于应用一个偏差，该偏差是为所考虑的问题专门设计的一组集体变量的函数。好的集体变量的设计可能具有挑战性，因此构成了这些方法应用的主要瓶颈。为了解决这个问题，我们最近引入了调和线性判别分析，这是一种将集体变量构建为一组描述符的线性组合的方法。该方法使用可以在短时间无偏分子动力学模拟中收集的输入信息，其中系统被困在亚稳态中。在这里，为了扩大我们对该方法效率的检查，我们将其应用于水合 chignolin 的折叠。有趣的是，在运行任何有偏差的模拟之前，构建的一维集体变量就揭示了折叠过程的大部分物理性质。此外，我们在元动力学中使用它，能够运行系统从折叠态到展开态再回到折叠态的模拟，为了得到完全收敛的结果，我们将元动力学与并行温度结合使用。最后，我们检查了当在其构建中使用不同的描述符集时集体变量的性能。
