Sequential data assimilation for single-molecule FRET photon-counting data.
作者： Yasuhiro Matsunaga , Akinori Kidera , Yuji Sugita
DOI: 10.1063/1.4921983
关键词: Experimental data 、 Molecular dynamics 、 Data assimilation 、 Computational chemistry 、 Conformational ensembles 、 Particle filter 、 Photon counting 、 Likelihood function 、 Chemistry 、 Single-molecule FRET 、 Biological system
摘要: Data assimilation is a statistical method designed to improve the quality of numerical simulations in combination with real observations. Here, we develop sequential data that incorporates one-dimensional time-series smFRET (single-molecule Forster resonance energy transfer) photon-counting into conformational ensembles biomolecules derived from “replicated” molecular dynamics (MD) simulations. A particle filter using large number MD likelihood function for employed screen match experimental data. We examine performance emulated and coarse-grained (CG) dye-labeled polyproline-20. The estimates end-to-end distance as well revealing latent variables. also able correct model parameter dependence CG discuss applicability biomolecules.
scitation.org
harvard.edu
aip.org
sci-hub.se 参考文章(64)
Gregory A Voth, None, Coarse-Graining of Condensed Phase and Biomolecular Systems CRC Press. ,(2008) , 10.1201/9781420059564
Daan Frenkel, Berend Smit, Molecular Dynamics Simulations Understanding Molecular Simulation (Second Edition)#R##N#From Algorithms to Applications. pp. 63- 107 ,(2002) , 10.1016/B978-012267351-1/50006-7
Sequential Monte Carlo methods in practice Springer. ,(2001) , 10.1007/978-1-4757-3437-9
Jaewoon Jung, Takaharu Mori, Chigusa Kobayashi, Yasuhiro Matsunaga, Takao Yoda, Michael Feig, Yuji Sugita, GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations Wiley Interdisciplinary Reviews: Computational Molecular Science. ,vol. 5, pp. 310- 323 ,(2015) , 10.1002/WCMS.1220
S. C. Kou, X. Sunney Xie, Jun S. Liu, Bayesian analysis of single‐molecule experimental data Journal of The Royal Statistical Society Series C-applied Statistics. ,vol. 54, pp. 469- 506 ,(2005) , 10.1111/J.1467-9876.2005.00509.X
Gunnar F. Schröder, Helmut Grubmüller, Maximum likelihood trajectories from single molecule fluorescence resonance energy transfer experiments Journal of Chemical Physics. ,vol. 119, pp. 9920- 9924 ,(2003) , 10.1063/1.1616511
Hiroyuki Oikawa, Yuta Suzuki, Masataka Saito, Kiyoto Kamagata, Munehito Arai, Satoshi Takahashi, Microsecond dynamics of an unfolded protein by a line confocal tracking of single molecule fluorescence Scientific Reports. ,vol. 3, pp. 2151- 2151 ,(2013) , 10.1038/SREP02151
Luis A Campos, Jianwei Liu, Xiang Wang, Ravishankar Ramanathan, Douglas S English, Victor Muñoz, A photoprotection strategy for microsecond-resolution single-molecule fluorescence spectroscopy Nature Methods. ,vol. 8, pp. 143- 146 ,(2011) , 10.1038/NMETH.1553
Soonkyo Jung, Robert M. Dickson, Hidden markov analysis of short single molecule intensity trajectories. Journal of Physical Chemistry B. ,vol. 113, pp. 13886- 13890 ,(2009) , 10.1021/JP907019P
Brian A. Camley, Frank L. H. Brown, Everett A. Lipman, Förster transfer outside the weak-excitation limit Journal of Chemical Physics. ,vol. 131, pp. 104509- ,(2009) , 10.1063/1.3230974