Kamerlin Shina C L, Vicatos Spyridon, Dryga Anatoly, Warshel Arieh
Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA.
Annu Rev Phys Chem. 2011;62:41-64. doi: 10.1146/annurev-physchem-032210-103335.
Recent years have witnessed an explosion in computational power, leading to attempts to model ever more complex systems. Nevertheless, there remain cases for which the use of brute-force computer simulations is clearly not the solution. In such cases, great benefit can be obtained from the use of physically sound simplifications. The introduction of such coarse graining can be traced back to the early usage of a simplified model in studies of proteins. Since then, the field has progressed tremendously. In this review, we cover both key developments in the field and potential future directions. Additionally, particular emphasis is given to two general approaches, namely the renormalization and reference potential approaches, which allow one to move back and forth between the coarse-grained (CG) and full models, as these approaches provide the foundation for CG modeling of complex systems.
近年来，计算能力呈爆炸式增长，促使人们尝试对越来越复杂的系统进行建模。然而，仍有一些情况，显然不能通过强力计算机模拟来解决问题。在这些情况下，使用合理的物理简化方法能带来很大益处。这种粗粒化方法的引入可追溯到蛋白质研究中简化模型的早期应用。从那时起，该领域取得了巨大进展。在本综述中，我们既涵盖了该领域的关键进展，也探讨了潜在的未来发展方向。此外，特别强调了两种通用方法，即重整化方法和参考势方法，这两种方法能让人们在粗粒化（CG）模型和全原子模型之间来回转换，因为它们为复杂系统的CG建模奠定了基础。
