To perform computationally efficient concurrent multiscale simulations of biological macromolecules in solution, where the all-atom (AT) models are coupled to supramolecular coarse-grained (SCG) solvent models, previous studies resorted to modified AT water models, such as the bundled-simple point charge (SPC) models, that use semiharmonic springs to restrict the relative movement of water molecules within a cluster. Those models can have a significant impact on the simulated biomolecules and can lead, for example, to a partial unfolding of a protein. In this work, we employ the recently developed alternative approach with a dynamical clustering algorithm, SWINGER, which enables a direct coupling of original unmodified AT and SCG water models. We perform an adaptive resolution molecular dynamics simulation of a Trp-Cage miniprotein in multiscale water, where the standard SPC water model is interfaced with the widely used MARTINI SCG model, and demonstrate that, compared to the corresponding full-blown AT simulations, the structural and dynamic properties of the solvated protein and surrounding solvent are well reproduced by our approach.

中文翻译：

---

使用SWINGER动态聚类算法的蛋白质水化多尺度模拟

为了在溶液中执行生物大分子的高效计算并发多尺度模拟，其中全原子（AT）模型与超分子粗粒（SCG）溶剂模型耦合，以前的研究采用了改进的AT水模型，例如捆绑简单模型点电荷（SPC）模型，它使用半谐波弹簧来限制簇中水分子的相对运动。这些模型可能会对模拟的生物分子产生重大影响，并可能导致例如蛋白质的部分展开。在这项工作中，我们采用了最近开发的带有动态聚类算法SWINGER的替代方法，该算法可以将原始未修改的AT和SCG水模型直接耦合。