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Helix Interactions in Membranes:  Lessons from Unrestrained Monte Carlo Simulations
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    Helix Interactions in Membranes:  Lessons from Unrestrained Monte Carlo Simulations
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    M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, Moscow V-437, 117997 GSP, Russia
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    Journal of Chemical Theory and Computation

    Cite this: J. Chem. Theory Comput. 2005, 1, 6, 1252–1264
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    https://doi.org/10.1021/ct0501250
    Published September 2, 2005
    Copyright © 2005 American Chemical Society

    Abstract

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    We describe one of the first attempts at unrestrained modeling of self-association of α-helices in implicit heterogeneous membrane-mimic media. The computational approach is based on the Monte Carlo conformational search for peptides in dihedral angles space. The membrane is approximated by an effective potential. The method is tested in calculations of two hydrophobic segments of human glycophorin A (GpA), known to form membrane-spanning dimers in real lipid bilayers. Our main findings may be summarized as follows. Modeling in vacuo does not adequately describe the behavior of GpA helices, failing to reproduce experimental structural data. The membrane environment stabilizes α-helical conformation of GpA monomers, inducing their transmembrane insertion and facilitating interhelical contacts. The voltage difference across the membrane promotes “head-to-head” orientation of the helices. “Fine-tuning” of the monomers in a complex is shown to be regulated by van der Waals interactions. Detailed exploration of conformational space of the system starting from arbitrary locations of two noninteracting helices reveals only several groups of energetically favorable structures. All of them represent tightly packed transmembrane helical dimers. In overall, they agree reasonably well with mutagenesis data, some of them are close to NMR-derived structures. A possibility of left-handed dimers is discussed. We assume that the observed moderate structural heterogeneity (the existence of several groups of states with close energies) reflects a real equilibrium dynamics of the monomersat least in membrane mimics used in experimental studies of GpA. The elaborated computational approach is universal and may be employed in studies of a wide class of membrane peptides and proteins.

    Copyright © 2005 American Chemical Society

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     Corresponding author phone:  (7-095) 336 20 00; e-mail:  [email protected].

    Supporting Information Available

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    Distance restraints used in MC simulations of the GpANMR model in implicit membrane and interatomic distances in models calculated via MC simulations in implicit membrane and in models obtained by NMR spectroscopy (Tables 1−3). This material is available free of charge via the Internet at http://pubs.acs.org.

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    Cited By

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    This article is cited by 12 publications.

    1. Andrey S. Kuznetsov, Anton A. Polyansky, Markus Fleck, Pavel E. Volynsky, and Roman G. Efremov . Adaptable Lipid Matrix Promotes Protein–Protein Association in Membranes. Journal of Chemical Theory and Computation 2015, 11 (9) , 4415-4426. https://doi.org/10.1021/acs.jctc.5b00206
    2. Han Cao, Marcus C. K. Ng, Siti Azma Jusoh, Hio Kuan Tai, Shirley W. I. Siu. TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers. Journal of Computer-Aided Molecular Design 2017, 31 (9) , 855-865. https://doi.org/10.1007/s10822-017-0047-0
    3. Antreas C. Kalli, Benjamin A. Hall, Iain D. Campbell, Mark S.P. Sansom. A Helix Heterodimer in a Lipid Bilayer: Prediction of the Structure of an Integrin Transmembrane Domain via Multiscale Simulations. Structure 2011, 19 (10) , 1477-1484. https://doi.org/10.1016/j.str.2011.07.014
    4. Anton A. Polyansky, Pavel E. Volynsky, Roman G. Efremov. Structural, dynamic, and functional aspects of helix association in membranes. 2011, 129-161. https://doi.org/10.1016/B978-0-12-381262-9.00004-5
    5. Eduard V. Bocharov, Pavel E. Volynsky, Konstantin V. Pavlov, Roman G. Efremov, Alexander S. Arseniev. Structure elucidation of dimeric transmembrane domains of bitopic proteins. Cell Adhesion & Migration 2010, 4 (2) , 284-298. https://doi.org/10.4161/cam.4.2.11930
    6. P E Volynsky, E A Mineeva, M V Goncharuk, Ya S Ermolyuk, A S Arseniev, R G Efremov. Computer simulations and modeling-assisted ToxR screening in deciphering 3D structures of transmembrane α-helical dimers: ephrin receptor A1. Physical Biology 2010, 7 (1) , 016014. https://doi.org/10.1088/1478-3975/7/1/016014
    7. A. O. Chugunov, R. G. Efremov. Prediction of the spatial structure of proteins: Emphasis on membrane targets. Russian Journal of Bioorganic Chemistry 2009, 35 (6) , 670-684. https://doi.org/10.1134/S106816200906003X
    8. Alan Grossfield. Chapter 5 Implicit Modeling of Membranes. 2008, 131-157. https://doi.org/10.1016/S1063-5823(08)00005-7
    9. Yana A. Vereshaga, Pavel E. Volynsky, Julia E. Pustovalova, Dmitry E. Nolde, Alexander S. Arseniev, Roman G. Efremov. Specificity of helix packing in transmembrane dimer of the cell death factor BNIP3: A molecular modeling study. Proteins: Structure, Function, and Bioinformatics 2007, 69 (2) , 309-325. https://doi.org/10.1002/prot.21555
    10. Anton O. Chugunov, Valery N. Novoseletsky, Dmitry E. Nolde, Alexander S. Arseniev, Roman G. Efremov. Method To Assess Packing Quality of Transmembrane α-Helices in Proteins. 1. Parametrization Using Structural Data. Journal of Chemical Information and Modeling 2007, 47 (3) , 1150-1162. https://doi.org/10.1021/ci600516x
    11. A. O. Chugunov, V. N. Novoseletsky, A. S. Arseniev, R. G. Efremov. A novel method for packing quality assessment of transmembrane α-helical domains in proteins. Biochemistry (Moscow) 2007, 72 (3) , 293-300. https://doi.org/10.1134/S0006297907030066
    12. Roman G. Efremov, Yana A. Vereshaga, Pavel E. Volynsky, Dmitry E. Nolde, Alexander S. Arseniev. Association of transmembrane helices: what determines assembling of a dimer?. Journal of Computer-Aided Molecular Design 2006, 20 (1) , 27-45. https://doi.org/10.1007/s10822-006-9034-6

    Journal of Chemical Theory and Computation

    Cite this: J. Chem. Theory Comput. 2005, 1, 6, 1252–1264
    Click to copy citationCitation copied!
    https://doi.org/10.1021/ct0501250
    Published September 2, 2005
    Copyright © 2005 American Chemical Society

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