| INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
Prev
Next
|
|
|
Exploring protein conformations by cluster-guided iterative multiple independent molecular dynamics simulations |
| Chengtao Ding(丁成涛)1,2,†, Guanglin Chen(陈光临)3,†, Qingguo Gong(龚庆国)2, and Zhiyong Zhang(张志勇)2,3,‡ |
1 Department of Clinical Laboratory Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, China; 2 Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; 3 Department of Physics and Anhui Center for Fundamental Science in Theoretical Physics, University of Science and Technology of China, Hefei 230026, China |
|
|
|
|
Abstract Enhanced sampling methods in molecular dynamics (MD) simulations have been gaining popularity in the past decades because they can explore conformations of proteins more efficiently than conventional MD simulations. In this paper, we implement a protocol of enhanced sampling that combines iterative multiple independent MD simulations and cluster analysis. After a set of independent simulations, the combined trajectory is divided into clusters. The representative structures picked from the clusters are utilized to start the next cycle of MD simulations. By using different strategies to pick the representative structures, the enhanced sampling can be either targeted or non-targeted. Two multi-domain proteins, Escherichia coli adenylate kinase (AdK) and the three-domain (PHD-Bromo-PWWP) structure in the BS69 protein, were selected to test the method. The data indicate that conformations of the proteins can be efficiently explored, and the results show better agreement with the experimental data than those obtained through conventional MD simulations.
|
Received: 28 July 2025
Revised: 11 September 2025
Accepted manuscript online: 18 September 2025
|
|
PACS:
|
87.15.ap
|
(Molecular dynamics simulation)
|
| |
87.14.E-
|
(Proteins)
|
| |
87.15.B-
|
(Structure of biomolecules)
|
|
| Fund: Research and Development Program of China (Grant No. 2021YFA1301504), Anhui University of Chinese Medicine 2024 Clinical Research Project (Grant No. 2024YFYLCZX26), the National Natural Science Foundation of China (Grant No. 91953101), and Chinese Academy of Sciences Strategic Priority Research Program (Grant No. XDB37040202). |
Corresponding Authors:
Zhiyong Zhang
E-mail: zzyzhang@ustc.edu.cn
|
Cite this article:
Chengtao Ding(丁成涛), Guanglin Chen(陈光临), Qingguo Gong(龚庆国), and Zhiyong Zhang(张志勇) Exploring protein conformations by cluster-guided iterative multiple independent molecular dynamics simulations 2026 Chin. Phys. B 35 058702
|
[1] Yon J M, Perahia D and Ghelis C 1998 Biochimie 80 33 [2] Berendsen H J and Hayward S 2000 Curr. Opin. Struct. Biol. 10 165 [3] Kern D and Zuiderweg E R 2003 Curr. Opin. Struct. Biol. 13 748 [4] Lipfert J and Doniach S 2007 Annu. Rev. Biophys Biomol. Struct. 36 307 [5] Joo C, Balci H, Ishitsuka Y, Buranachai C and Ha T 2008 Annu. Rev. Biochem. 77 51 [6] Sinz A 2003 J. Mass Spectrom 38 1225 [7] Karplus M and McCammon J A 2002 Nat. Struct. Biol. 9 646 [8] Adcock S A and McCammon J A 2006 Chem. Rev. 106 1589 [9] Dror R O, Dirks R M, Grossman J P, Xu H and Shaw D E 2012 Annu. Rev. Biophys. 41 429 [10] Anderson J A, Lorenz C D and Travesset A 2008 J. Comput. Phys. 227 5342 [11] Friedrichs M S, Eastman P, Vaidyanathan V, Houston M, Legrand S, Beberg A L, Ensign D L, Bruns C M and Pande V S 2009 J. Comput. Chem. 30 864 [12] HarveyMJ, Giupponi G and Fabritiis G D 2009 J. Chem. Theory Comput. 5 1632 [13] Jung J, Naurse A, Kobayashi C and Sugita Y 2016 J. Chem. Theory Comput. 12 4947 [14] Bernardi R C, Melo M C R and Schulten K 2015 BBA-Gen. Subjects 1850 872 [15] Wang A H, Zhang Z C and Li G H 2019 Chinese Journal of Chemical Physics 32 277 [16] Tang Y, Yang Z, Yao Y, Zhou Y, Tan Y, Wang Z, Pan T, Xiong R, Sun J and Wei G 2024 Chin. Phys. B 33 030701 [17] Harada R and Kitao A 2013 J. Chem. Phys. 139 035103 [18] Harada R and Kitao A 2015 J. Chem. Theory Comput. 11 5493 [19] Harada R, Sladek V and Shigeta Y 2019 J. Chem. Theory Comput. 15 5144 [20] Shkurti A, Styliari I D, Balasubramanian V, Bethune I, Pedebos C, Jha S and Laughton C A 2019 J. Chem. Theory Comput. 15 2587 [21] Yuan Y, Zhu Q, Song R, Ma J and Dong H 2020 J. Chem. Theory Comput. 16 4631 [22] Zhang J and Gong H 2020 J. Chem. Theory Comput. 16 4813 [23] Harada R and Shigeta Y 2018 Journal of Molecular Graphics & Modelling 85 153 [24] Xu R and Wunsch D 2005 IEEE Transactions on Neural Networks 16 645 [25] Muller C W and Schulz G E 1992 J. Mol. Biol. 224 159 [26] Muller C W, Schlauderer G J, Reinstein J and Schulz G E 1996 Structure 4 147 [27] Wang J, Qin S, Li F, Li S, Zhang W, Peng J, Zhang Z, Gong Q, Wu J and Shi Y 2014 Cell Research 24 890 [28] Harada R and Shigeta Y 2018 Molecular Simulation 44 206 [29] Jain A K 2010 Pattern Recognition Letters 31 651 [30] Arora K and Brooks C L I 2007 Proc. Natl. Acad. Sci. USA 104 18496 [31] Ping J, Hao P, Li Y X and Wang J F 2013 Biomed Research International 2013 628536 [32] Li D, Liu M S and Ji B 2015 Biophysical Journal 109 647 [33] Zheng Y and Cui Q 2018 J. Chem. Theory Comput. 14 1716 [34] Abraham M J, Murtola T, Schulz R, Páll S, Smith J C, Hess B and Lindahl E 2015 SoftwareX 1-2 19 [35] Huang J, Rauscher S, Nawrocki G, Ran T, Feig M, de Groot B L, Grubmüller H and MacKerell A D 2017 Nature Methods 14 71 [36] Jorgensen W L, Chandrasekhar J, Madura J D, Impey R W and Klein M L 1983 J. Chem. Phys. 79 926 [37] Bussi G, Donadio D and Parrinello M 2007 J. Chem. Phys. 126 014101 [38] Hess B 2008 J. Chem. Theory Comput. 4 116 [39] Essmann U, Perera L, Berkowitz M L, Darden T, Lee H and Pedersen L G 1995 J. Chem. Phys. 103 8577 [40] Kumar S, Rosenberg J M, Bouzida D, Swendsen R H and Kollman P A 1992 J. Comput. Chem. 13 1011 [41] Hateboer G, Gennissen A, Ramos Y F, Kerkhoven R M, Sonntag-Buck V, Stunnenberg H G and Bernards R 1995 EMBO J. 14 3159 [42] Eswar N, Eramian D, Webb B, Shen M Y and Sali A 2008 Methods in molecular biology (Clifton, N.J.) 426 145 [43] Petoukhov M V and Svergun D I 2005 Biophysical Journal 89 1237 [44] Franke D, Petoukhov M V, Konarev P V, Panjkovich A, Tuukkanen A, Mertens H D T, Kikhney A G, Hajizadeh N R, Franklin J M, Jeffries C M and Svergun D I 2017 Journal of Applied Crystallography 50 1212 [45] Robustelli P, Piana S and Shaw D E 2018 Proc. Natl. Acad. Sci. USA 115 E4758 [46] Tria G, Mertens H D T, Kachala M and Svergun D I 2015 Iucrj 2 207 [47] Wolf-Watz M, Thai V, Henzler-Wildman K, Hadjipavlou G, Eisenmesser E Z and Kern D 2004 Nature Structural & Molecular Biology 11 945 [48] Maragakis P and Karplus M 2005 Journal of Molecular Biology 352 807 [49] Henzler-Wildman K A, Thai V, Lei M, Ott M, Wolf-Watz M, Fenn T, Pozharski E, Wilson M A, Petsko G A, Karplus M, Hübner C G and Kern D 2007 Nature 450 838 [50] Grossfield A http://membrane.urmc.rochester.edu/wordpress/?page_id=126 [51] Braitbard M, Schneidman-Duhovny D and Kalisman N 2019 Annu. Rev. Biochem. 88 113 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|