Histone modifications have great importance in epigenetic regulation. JMJD2A is a histone demethylase which is selective for di- and trimethyl forms of residues Lys9 and Lys36 of Histone 3 tail (H3K9 and H3K36). We present a molecular dynamics simulations of mono-, di- and trimethylated histone tails in complex with JMJD2A catalytic domain to gain insight into how JMJD2A discriminates between the methylation states of H3K9. The methyl groups are located at specific distances and orientations with respect to Fe(II) in methylammonium binding pocket. For the trimethyllysine the mechanism which provides the effectual orientation of methyl groups is the symmetry, whereas for the dimethyllysine case the determining factors are the interactions between methyllysine head and its environment and subsequently the restriction on angular motion. The occurrence frequency of methyl groups in a certain proximity of Fe(II) comes out as the explanation of the enzyme activity difference on di- and tri-methylated peptides. Energy analysis suggests that recognition is mostly driven by van der Waals and followed by Coulombic interactions in the enzyme-substrate interface. The number (mono, di or tri) and orientations of methyl groups and water molecules significantly affect the extent of van der Waals interaction strengths. Hydrogen bonding analysis suggests that the interaction between JMJD2A and its substrates mainly comes from main chain-side chain interactions. Binding free energy analysis points out Arg8 as an important residue forming an intra-substrate hydrogen bond with tri and dimethylated Lys9 of the H3 chain. Our study provides new insights into how JMJD2A discriminates between its substrates from both a structural and dynamical point of view.
References
[1]
Moss T, Wallrath L (2007) Connections between epigenetic gene silencing and human disease. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 618: 163–174.
[2]
Chen Z, Zang J, Whetstine J, Hong X, Davrazou F, et al. (2006) Structural insights into histone demethylation by JMJD2 family members. Cell 125: 691–702.
[3]
Chen Z, Zang J, Kappler J, Hong X, Crawford F, et al. (2007) Structural basis of the recognition of a methylated histone tail by JMJD2A. Proceedings of the National Academy of Sciences 104: 10818.
[4]
Ng S, Kavanagh K, McDonough M, Butler D, Pilka E, et al. (2007) Crystal structures of histone demethylase JMJD2A reveal basis for substrate specificity. Nature 448: 87–91.
[5]
Couture J, Collazo E, Ortiz-Tello P, Brunzelle J, Trievel R (2007) Specificity and mechanism of JMJD2A, a trimethyllysine-specific histone demethylase. Nature Structural & Molecular Biology 14: 689–695.
[6]
Derewenda Z, Lee L, Derewenda U (1995) The occurence of CH··· O hydrogen bonds in proteins. Journal of molecular biology 252: 248–262.
[7]
Cortez CC, Jones PA (2008) Chromatin, cancer and drug therapies. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 647: 44–51.
[8]
Shin S, Janknecht R (2007) Activation of androgen receptor by histone demethylases JMJD2A and JMJD2D. Biochemical and biophysical research communications 359: 742–746.
[9]
Ozboyaci M, Gursoy A, Erman B, Keskin O (2011) Molecular recognition of H3/H4 histone tails by the tudor domains of JMJD2A: a comparative molecular dynamics simulations study. PLoS One 6: e14765.
[10]
Simmons J, Müller T, Hausinger R (2008) Fe II/-ketoglutarate hydroxylases involved in nucleobase, nucleoside, nucleotide, and chromatin metabolism. Dalton Transactions 2008: 5132–5142.
[11]
Couture J, Hauk G, Thompson M, Blackburn G, Trievel R (2006) Catalytic roles for carbon-oxygen hydrogen bonding in SET domain lysine methyltransferases. Journal of Biological Chemistry 281: 19280.
[12]
Whetstine J, Nottke A, Lan F, Huarte M, Smolikov S, et al. (2006) Reversal of histone lysine trimethylation by the JMJD2 family of histone demethylases. Cell 125: 467–481.
[13]
Wan S, Coveney P, Flower D (2005) Peptide recognition by the T cell receptor: comparison of binding free energies from thermodynamic integration, Poisson–Boltzmann and linear interaction energy approximations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 363: 2037.
[14]
Karlin S, Zhu Z, Karlin K (1997) The extended environment of mononuclear metal centers in protein structures. Proceedings of the National Academy of Sciences of the United States of America 94: 14225.
[15]
Jorgensen W (1981) Transferable intermolecular potential functions for water, alcohols, and ethers. Application to liquid water. J Am Chem Soc 103: 335–340.
[16]
Duan Y, Wu C, Chowdhury S, Lee M, Xiong G, et al. (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. Journal of computational chemistry 24: 1999–2012.
[17]
Case D, Darden T, Cheatham T III, Simmerling C, Wang J, et al. (2008) AMBER 10. University of California, San Francisco.
[18]
Wang J, Wolf R, Caldwell J, Kollman P, Case D (2004) Development and testing of a general amber force field. Journal of computational chemistry 25: 1157–1174.
[19]
Peraro M, Spiegel K, Lamoureux G, Vivo M, DeGrado W, et al. (2007) Modeling the charge distribution at metal sites in proteins for molecular dynamics simulations. Journal of Structural Biology 157: 444–453.
[20]
Kalé L, Skeel R, Bhandarkar M, Brunner R, Gursoy A, et al. (1999) NAMD2: Greater Scalability for Parallel Molecular Dynamics* 1. Journal of Computational Physics 151: 283–312.
[21]
Phillips J, Braun R, Wang W, Gumbart J, Tajkhorshid E, et al. (2005) Scalable molecular dynamics with NAMD. Journal of computational chemistry 26: 1781.
[22]
Martyna G, Tobias D, Klein M (1994) Constant pressure molecular dynamics algorithms. The Journal of Chemical Physics 101: 4177.
[23]
Feller S, Zhang Y, Pastor R, Brooks B (1995) Constant pressure molecular dynamics simulation: the Langevin piston method. The Journal of Chemical Physics 103: 4613.
[24]
Miyamoto S, Kollman P (2004) SETTLE: an analytical version of the SHAKE and RATTLE algorithm for rigid water models. Journal of computational chemistry 13: 952–962.
[25]
Kollman P, Massova I, Reyes C, Kuhn B, Huo S, et al. (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33: 889–897.
[26]
Gohlke H, Kiel C, Case D (2003) Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes. Journal of molecular biology 330: 891–913.
[27]
Jianyin Shao SWT, Thompson Nephi, Cheatham ThomasE (2007) Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms. J Chem Theory Comput 3: 2312–2334.
[28]
Case DA, Cheatham TE, Darden T, Gohlke H, Luo R, et al. (2005) The Amber biomolecular simulation programs. J Comput Chem 26: 1668–1688.
