Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland.
Nationwide Children's Hospital, Columbus, OH 43205, USA.
Int J Mol Sci. 2018 Nov 6;19(11):3496. doi: 10.3390/ijms19113496.
Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this minireview, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions, and highly simplified structure-based elastic network models of protein flexibility. In contrast to classical all-atom molecular dynamics, the modeling strategies discussed here allow the quite accurate modeling of much larger systems and longer-time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.
蛋白质三维结构的涨落和大规模构象转变对于蛋白质及其复合物的生物功能至关重要。此类现象的实验研究仍然极具挑战性，因此分子建模可以作为研究大的分子体系和长时间事件的良好替代方法或有价值的辅助工具。在这篇简要综述中，我们介绍了两种粗粒化 (CG) 建模方法来研究蛋白质体系的动态特性。我们讨论了两种用于蛋白质局部动力学和构象转变的蒙特卡罗动力学模拟的多肽链 CG 表示，以及高度简化的基于结构的蛋白质柔性弹性网络模型。与经典的全原子分子动力学相比，这里讨论的建模策略允许对更大的体系和更长时间的动态现象进行相当准确的建模。我们简要描述了这些模型的主要特点，并概述了它们的一些应用，包括模拟近天然结构的涨落、对蛋白质构象空间的大区域进行采样，或可能支持大蛋白质及其复合物的结构预测。
