Javed Ramsha, Kapakayala Anji Babu, Nair Nisanth N
Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India.
J Chem Theory Comput. 2024 Oct 8;20(19):8450-8460. doi: 10.1021/acs.jctc.4c00776. Epub 2024 Sep 29.
Umbrella sampling has been a workhorse for free energy calculations in molecular simulations for several decades. In conventional umbrella sampling, restraining bias potentials are strategically applied along one or several collective variables. Major drawbacks associated with this method are the requirement of a large number of bias windows and the poor sampling of the transverse coordinates. In this work, we propose an alternate formalism that departs from the traditional umbrella sampling to mitigate these issues, where we replace umbrella-type restraining bias potentials with bucket-type wall potentials. This modification permits one to formulate an efficient computational strategy leveraging wall potentials and metadynamics sampling. This new method, called "bucket sampling", can significantly reduce the computational cost of obtaining converged high-dimensional free energy surfaces. Extensions of the proposed method with temperature acceleration and replica exchange solute tempering are also demonstrated.
几十年来,伞形抽样一直是分子模拟中自由能计算的主力军。在传统的伞形抽样中,沿着一个或几个集体变量策略性地应用约束偏差势。与该方法相关的主要缺点是需要大量的偏差窗口以及横向坐标的抽样效果不佳。在这项工作中,我们提出了一种替代形式,它不同于传统的伞形抽样,以缓解这些问题,我们用桶形壁势取代伞形约束偏差势。这种修改允许人们制定一种利用壁势和元动力学抽样的高效计算策略。这种新方法称为“桶抽样”,可以显著降低获得收敛的高维自由能表面的计算成本。还展示了所提出方法在温度加速和副本交换溶质回火方面的扩展。