中国物理B ›› 2017, Vol. 26 ›› Issue (5): 50202-050202.doi: 10.1088/1674-1056/26/5/050202
Smoothing potential energy surface of proteins by hybrid coarse grained approach
Yukun Lu(卢禹锟), Xin Zhou(周昕), ZhongCan OuYang(欧阳钟灿)
- 1 Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Smoothing potential energy surface of proteins by hybrid coarse grained approach
Yukun Lu(卢禹锟)1,2, Xin Zhou(周昕)2, ZhongCan OuYang(欧阳钟灿)1
- 1 Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
摘要：
Coarse-grained (CG) simulations can more efficiently study large conformational changes of biological polymers but usually lose accuracies in the details. Lots of different hybrid models involving multiple different resolutions have been developed to overcome the difficulty. Here we propose a novel effective hybrid CG (hyCG) approach which mixes the fine-grained interaction and its average in CG space to form a more smoothing potential energy surface. The hyCG approximately reproduces the potential of mean force in the CG space, and multiple mixed potentials can be further combined together to form a single effective force field for achieving both high efficiency and high accuracy. We illustrate the hyCG method in Trp-cage and Villin headpiece proteins to exhibit the folding of proteins. The topology of the folding landscape and thus the folding paths are preserved, while the folding is boosted nearly one order of magnitude faster. It indicates that the hyCG approach could be applied as an efficient force field in proteins.
中图分类号: (Probability theory, stochastic processes, and statistics)
- 02.50.-r