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Conformational Dynamics of Histone Lysine Methyltransferases by Millisecond-Timescale Molecular Dynamics on Folding@home

2017; Elsevier BV; Volume: 112; Issue: 3 Linguagem: Inglês

10.1016/j.bpj.2016.11.1048

1542-0086

Rafal Wiewiora, Shi Chen, Kyle A. Beauchamp, Minkui Luo, John D. Chodera,

Cancer-related gene regulation

Epigenetic regulation is essential for eukaryotic organisms in processes spanning from embryo development to longevity. Histone lysine methyltransferases (HKMTs) are amongst the key players that control these processes. HKMT dysregulation via mutation or altered expression has been implicated in many cancers' initiation, maintenance, aggressiveness and metastasis. Furthermore, roles of HKMTs in aging and drug addition have been shown in animal models. Development of selective inhibitors for many members of this protein family remains an unmet need. Conformational dynamics have been observed or proposed at both cofactor- and substrate-binding sites of most HKMTs; this structural plasticity has a crucial impact on the shapes and druggabilities of pockets in HKMTs and on inhibitor design. Here we will present multiple-millisecond aggregate timescale Molecular Dynamics simulations, collected on [email protected], for the SETD8, SETD2, NSD1, NSD2 and NSD3 methyltransferases. All these proteins were simulated in the apo form, and Markov State Models were constructed to map the thermodynamic and kinetic landscapes of the conformational ensembles. Furthermore, hypotheses for the dynamics within the catalytic cycle of the SETD8 methyltransferase, based on the available and two new crystal structures, were tested by Molecular Dynamics. In addition to the apo simulations, 'chimeric' homology models (assembled from domains of the protein from multiple crystal structures) were constructed and propagated in simulations; moreover a whole-catalytic-cycle set of simulations, comprising all possible combinations of the co-factor SAM, by-product SAH and histone H4 peptide, were conducted. Here we present a complete model of the catalytic cycle of the SETD8 methyltransferase, based on ∼5 ms aggregate simulation time. Furthermore, verification of the computational results via biochemical experiments is presented.