Full Text:   <1253>

Summary:  <1039>

CLC number: Q51

On-line Access: 2019-05-15

Received: 2019-03-15

Revision Accepted: 2019-03-31

Crosschecked: 2019-04-12

Cited: 0

Clicked: 3384

Citations:  Bibtex RefMan EndNote GB/T7714


Chun Tang


-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE B 2019 Vol.20 No.6 P.496-502


On the necessity of an integrative approach to understand protein structural dynamics

Author(s):  Qing-fen Yang, Chun Tang

Affiliation(s):  Hubei Key Laboratory of Natural Medicinal Chemistry and Resource Evaluation, School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; more

Corresponding email(s):   tanglab@wipm.ac.cn

Key Words:  Conformational dynamics, Integrative structural biology, Distance restraint, Ensemble averaging, Nuclear magnetic resonance (NMR)

Qing-fen Yang, Chun Tang. On the necessity of an integrative approach to understand protein structural dynamics[J]. Journal of Zhejiang University Science B, 2019, 20(6): 496-502.

@article{title="On the necessity of an integrative approach to understand protein structural dynamics",
author="Qing-fen Yang, Chun Tang",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T On the necessity of an integrative approach to understand protein structural dynamics
%A Qing-fen Yang
%A Chun Tang
%J Journal of Zhejiang University SCIENCE B
%V 20
%N 6
%P 496-502
%@ 1673-1581
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1900135

T1 - On the necessity of an integrative approach to understand protein structural dynamics
A1 - Qing-fen Yang
A1 - Chun Tang
J0 - Journal of Zhejiang University Science B
VL - 20
IS - 6
SP - 496
EP - 502
%@ 1673-1581
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1900135

Proteins are dynamic, fluctuating between multiple conformational states. Protein dynamics, spanning orders of magnitude in time and space, allow proteins to perform specific functions. Moreover, under certain conditions, proteins can morph into a different set of conformations. Thus, a complete understanding of protein structural dynamics can provide mechanistic insights into protein function. Here, we review the latest developments in methods used to determine protein ensemble structures and to characterize protein dynamics. Techniques including X-ray crystallography, cryogenic electron microscopy, and small angle scattering can provide structural information on specific conformational states or on the averaged shape of the protein, whereas techniques including nuclear magnetic resonance, fluorescence resonance energy transfer (FRET), and chemical cross-linking coupled with mass spectrometry provide information on the fluctuation of the distances between protein domains, residues, and atoms for the multiple conformational states of the protein. In particular, FRET measurements at the single-molecule level allow rapid resolution of protein conformational states, where information is otherwise obscured in bulk measurements. Taken together, the different techniques complement each other and their integrated use can offer a clear picture of protein structure and dynamics.



Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Bahar I, Lezon TR, Bakan A, et al., 2010. Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins. Chem Rev, 110(3):1463-1497.

[2]Bai XC, McMullan G, Scheres SHW, 2015. How cryo-EM is revolutionizing structural biology. Trends Biochem Sci, 40(1):49-57.

[3]Bermejo GA, Clore GM, Schwieters CD, 2012. Smooth statistical torsion angle potential derived from a large conformational database via adaptive kernel density estimation improves the quality of NMR protein structures. Protein Sci, 21(12):1824-1836.

[4]Brady JP, Farber PJ, Sekhar A, et al., 2017. Structural and hydrodynamic properties of an intrinsically disordered region of a germ cell-specific protein on phase separation. Proc Natl Acad Sci USA, 114(39):E8194-E8203.

[5]Brodie NI, Popov KI, Petrotchenko EV, et al., 2017. Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations. Sci Adv, 3(7):e1700479.

[6]Bryngelson JD, Onuchic JN, Socci ND, et al., 1995. Funnels, pathways, and the energy landscape of protein folding: a synthesis. Proteins, 21(3):167-195.

[7]Clore GM, Iwahara J, 2009. Theory, practice, and applications of paramagnetic relaxation enhancement for the characterization of transient low-population states of biological macromolecules and their complexes. Chem Rev, 109(9):4108-4139.

[8]Ding YH, Gong Z, Dong X, et al., 2017. Modeling protein excited-state structures from “over-length” chemical cross-links. J Biol Chem, 292(4):1187-1196.

[9]Dong X, Gong Z, Lu YB, et al., 2017. Ubiquitin S65 phosphorylation engenders a pH-sensitive conformational switch. Proc Natl Acad Sci USA, 114(26):6770-6775.

[10]Dror RO, Dirks RM, Grossman JP, et al., 2012. Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys, 41:429-452.

[11]Elbaum-Garfinkle S, Kim Y, Szczepaniak K, et al., 2015. The disordered P granule protein LAF-1 drives phase separation into droplets with tunable viscosity and dynamics. Proc Natl Acad Sci USA, 112(23):7189-7194.

[12]Ferber M, Kosinski J, Ori A, et al., 2016. Automated structure modeling of large protein assemblies using crosslinks as distance restraints. Nat Methods, 13(6):515-520.

[13]Fraser JS, van den Bedem H, Samelson AJ, et al., 2011. Accessing protein conformational ensembles using room-temperature X-ray crystallography. Proc Natl Acad Sci USA, 108(39):16247-16252.

[14]Gladkova C, Schubert AF, Wagstaff JL, et al., 2017. An invisible ubiquitin conformation is required for efficient phosphorylation by PINK1. EMBO J, 36(24):3555-3572.


[16]Gong Z, Ding YH, Dong X, et al., 2015. Visualizing the ensemble structures of protein complexes using chemical cross-linking coupled with mass spectrometry. Biophys Rep, 1(3):127-138.

[17]Henzler-Wildman K, Kern D, 2007. Dynamic personalities of proteins. Nature, 450(7172):964-972.

[18]Iwahara J, Anderson DE, Murphy EC, et al., 2003. EDTA-derivatized deoxythymidine as a tool for rapid determination of protein binding polarity to DNA by intermolecular paramagnetic relaxation enhancement. J Am Chem Soc, 125(22):6634-6635.

[19]Iwahara J, Tang C, Clore GM, 2007. Practical aspects of 1H transverse paramagnetic relaxation enhancement measurements on macromolecules. J Magn Reson, 184(2):185-195.

[20]Kalinin S, Valeri A, Antonik M, et al., 2010. Detection of structural dynamics by FRET: a photon distribution and fluorescence lifetime analysis of systems with multiple states. J Phys Chem B, 114(23):7983-7995.

[21]Kuznetsova IM, Turoverov KK, Uversky VN, 2014. What macromolecular crowding can do to a protein? Int J Mol Sci, 15(12):23090-23140.

[22]Lerner E, Cordes T, Ingargiola A, et al., 2018. Toward dynamic structural biology: two decades of single-molecule Förster resonance energy transfer. Science, 359(6373):eaan1133.

[23]Li PL, Banjade S, Cheng HC, et al., 2012. Phase transitions in the assembly of multivalent signalling proteins. Nature, 483(7389):336-340.

[24]Liu Z, Gong Z, Dong X, et al., 2016. Transient protein–protein interactions visualized by solution NMR. Biochim Biophys Acta, 1864(1):115-122.

[25]Liu Z, Gong Z, Cao Y, et al., 2018. Characterizing protein dynamics with integrative use of bulk and single-molecule techniques. Biochemistry, 57(3):305-313.

[26]Luchinat E, Banci L, 2016. A unique tool for cellular structural biology: in-cell NMR. J Biol Chem, 291(8):3776-3784.

[27]MacCallum JL, Perez A, Dill KA, 2015. Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference. Proc Natl Acad Sci USA, 112(22):6985-6990.

[28]Matthew Allen Bullock J, Schwab J, Thalassinos K, et al., 2016. The importance of non-accessible crosslinks and solvent accessible surface distance in modeling proteins with restraints from crosslinking mass spectrometry. Mol Cell Proteomics, 15(7):2491-2500.

[29]Pan BB, Yang F, Ye YS, et al., 2016. 3D structure determination of a protein in living cells using paramagnetic NMR spectroscopy. Chem Commun, 52(67):10237-10240.

[30]Peulen TO, Opanasyuk O, Seidel CAM, 2017. Combining graphical and analytical methods with molecular simulations to analyze time-resolved FRET measurements of labeled macromolecules accurately. J Phys Chem B, 121(35):8211-8241.

[31]Rieping W, Habeck M, Nilges M, 2005. Inferential structure determination. Science, 309(5732):303-306.

[32]Sakakibara D, Sasaki A, Ikeya T, et al., 2009. Protein structure determination in living cells by in-cell NMR spectroscopy. Nature, 458(7234):102-105.

[33]Sali A, Berman HM, Schwede T, et al., 2015. Outcome of the first wwPDB hybrid/integrative methods task force workshop. Structure, 23(7):1156-1167.

[34]Schwieters CD, Clore GM, 2014. Using small angle solution scattering data in Xplor-NIH structure calculations. Prog Nucl Magn Reson Spectrosc, 80:1-11.

[35]Schwieters CD, Bermejo GA, Clore GM, 2018. Xplor-NIH for molecular structure determination from NMR and other data sources. Protein Sci, 27(1):26-40.

[36]Sekhar A, Kay LE, 2013. NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers. Proc Natl Acad Sci USA, 110(32):12867-12874.

[37]Tang C, Schwieters CD, Clore GM, 2007. Open-to-closed transition in apo maltose-binding protein observed by paramagnetic NMR. Nature, 449(7165):1078-1082.

[38]Tang YF, Huang YJ, Hopf TA, et al., 2015. Protein structure determination by combining sparse NMR data with evolutionary couplings. Nat Methods, 12(8):751-754.

[39]Wagner G, Wüthrich K, 1978. Dynamic model of globular protein conformations based on NMR studies in solution. Nature, 275(5677):247-248.

[40]Xing Q, Huang P, Yang J, et al., 2014. Visualizing an ultra-weak protein–protein interaction in phosphorylation signaling. Angew Chem Int Ed Engl, 53(43):11501-11505.

[41]Yang B, Wu YJ, Zhu M, et al., 2012. Identification of cross-linked peptides from complex samples. Nat Methods, 9(9):904-906.

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE