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Download (7Mb) University of Warwick institutional repository: http://go.warwick.ac.uk/wrap A Thesis Submitted for the Degree of PhD at the University of Warwick http://go.warwick.ac.uk/wrap/74165 This thesis is made available online and is protected by original copyright. Please scroll down to view the document itself. Please refer to the repository record for this item for information to help you to cite it. Our policy information is available from the repository home page. MENS T A T A G I MOLEM U N IS IV S E EN RS IC ITAS WARW Coarse-Grained Simulations of Intrinsically Disordered Peptides by Gil Rutter Thesis Submitted to the University of Warwick for the degree of Doctor of Philosophy Department of Physics October 2015 Contents List of Tables iv List of Figures vi Acknowledgments xvii Declarations xviii Abstract xix Chapter 1 Introduction 1 1.1 Proteinstructure ............................. 1 1.1.1 Dependence on ambient conditions . 3 1.2 Proteindisorder.............................. 6 1.2.1 Determinants of protein disorder . 6 1.2.2 Functions of IDPs . 7 1.3 Experimentaltechniques. 8 1.3.1 Intrinsicdisorder ......................... 8 1.3.2 Biomineralisation systems . 10 1.4 Molecular dynamics for proteins . 12 1.4.1 Approaches to molecular simulation . 12 1.4.2 Statistical ensembles . 13 1.5 Biomineralisation . 15 1.6 n16N.................................... 16 1.7 Summary ................................. 20 Chapter 2 Accelerated simulation techniques 21 2.1 Coarse-graining . 21 2.1.1 DefiningtheCGmapping . 22 2.1.2 Explicit and implicit solvation . 24 i 2.1.3 Validating a CG model . 26 2.1.4 Choices of coarse-grained models . 26 2.2 Acceleratedsamplingtechniques . 29 2.2.1 Replica exchange molecular dynamics . 30 2.2.2 Statistical temperature molecular dynamics . 31 2.3 Summary ................................. 34 Chapter 3 Software modifications and validation 35 3.1 PRIME20 initial parametrisation . 35 3.1.1 PRIME model validation . 36 3.1.2 Parametrising a PRIME20-like model . 40 3.2 Implementation work in LAMMPS . 42 3.2.1 The PLUM model . 42 3.2.2 Statistical temperature molecular dynamics . 46 3.3 Summary ................................. 52 Chapter 4 Single-chain simulations 53 4.1 PLUM model simulations . 53 4.1.1 Over-stabilisation of the ↵-helix . 53 4.1.2 PLUM* validation work . 54 4.1.3 The n16N-1 system in PLUM* . 58 4.1.4 The n16NN-1 system . 61 4.1.5 TheS1system .......................... 62 4.2 PRIME20-like model simulations . 64 4.2.1 TheS1system .......................... 64 4.2.2 The n16N-1 system . 65 4.2.3 The n16NN-1 system . 70 4.3 Summary ................................. 71 Chapter 5 Multiple-chain simulations 73 5.1 The n16N-2 system . 73 5.1.1 PLUM* . 73 5.1.2 PLUM . 74 5.1.3 PRIME20-like . 78 5.2 The n16NN-2 system . 81 5.2.1 PLUM* . 81 5.2.2 PRIME20-like . 82 5.3 Discussionofdimersystems . 83 ii 5.4 The n16N-3 system . 84 5.4.1 PLUM* . 84 5.4.2 PRIME20-like . 85 5.5 The n16NN-3 system . 87 5.6 Discussionoftrimersystems. 90 5.7 The n16N-6 system . 91 5.7.1 PLUM* . 91 5.7.2 PRIME20-like . 92 5.8 The n16NN-6 system . 97 5.9 Discussion of hexamer systems . 99 5.10Summary ................................. 101 Chapter 6 Conclusions 103 6.1 PLUM*model .............................. 103 6.1.1 Simulation results . 103 6.1.2 Furtherwork ........................... 105 6.2 ThePRIME20-likemodel ........................ 106 6.2.1 Simulation results . 106 6.2.2 Furtherwork ........................... 107 6.3 Outlook for coarse-grained models to study IDPs . 108 iii List of Tables 1.1 Relative frequencies of residues in common secondary structure mo- tifs [Creighton, 1992] [Berg et al., 2002, page 67] and disorder propen- sity according to the TOP-IDP scale [Campen et al., 2008], in which higher values are more disordered. This is one of many scales on which residue disorder propensity has been ranked [Galzitskaya et al., 2006; Oldfield et al., 2005; Vihinen et al., 1994; Garbuzynskiy et al., 2004]. The highest values are highlighted. .............. 7 1.2 Summary of experimental research on n16N peptide, with a focus on experimental techniques used. All assays contain n16N in water solution with calcium and carbonate ions for crystal growth. AFM - Atomic force microscopy CD - Circular dichroism spectroscopy DLS - Dynamic light scattering EDX - Energy dispersive X-ray spectroscopy FM - Fluorescence microscopy FTIR - Fourier-transformed infrared spectroscopy Raman - Raman spectroscopy SEM - Scanning electron microscopy TEM - Tunnelling electron microscopy XANES - X-ray absorption near edge spectromicroscopy XRD - X-ray di↵raction X-PEEM - X-ray photoelectron emission spectromicroscopy .... 11 1.3 Suggested roles of the subdomains of n16N [Brown et al., 2014]. .. 20 iv 4.1 Top interactions between residues ranked by frequency of occurrence. To qualify, any atom on residue A has to be in the square well of any atom on residue B, with A and B separated with at least three residues in-between. Tyrosine dominates the rankings, and is clearly a cornerstone of intrapeptide stabilisation. .............. 69 v List of Figures 1.1 Wikimedia user Dcrjsr, available under the Creative Commons Attri- bution 3.0 Unported license. The backbone atoms of a central amino acid residue is shown, with two neighbours labelled (-1) and (+1) partially shown. Each residue except glycine also has a side-chain, denoted Cβ. The dihedral angles φ, and ! which determine the secondary structure are labelled. 2 1.2 [Hollingsworth and Karplus, 2010] adapted from [Ramachandran and Sasisekharan, 1968]. A Ramachandran plot showing both example data and outlines of commonly accepted regions. The data is comprised of 63,149 residues from crystal structures and each point indicates the (φ, ) values rep- resenting the secondary structure of a single residue. The outlines are divided into core allowed regions (solid lines) and allowed regions (dashed lines). Several forms of secondary structure have their location indicated; these are ↵-helix (↵), 310-helix (3), ⇡- helix (⇡), left-handed ↵-helix (↵l), 2.27 ribbon (2), polyproline-II (II), collagen (C), parallel β-sheet ( ) and anti-parallel β-sheet ( ). 4 "" "# vi 1.3 A steric map, in which steric clashes leading to forbidden regions are shown in (φ, ) phase space and labelled according to the clashing pair of atoms [Ho et al., 2003]. Dashed blue lines and blue labels denote clashes. Favourable dipole-dipole backbone interactions are also plot- ted, with red dashed lines and red labels. Areas of the map are white if forbidden, and otherwise coloured according to the legend below. The atom labels match the illustration in fig. 1.1. Boundaries ---Attractive dipole-dipole interactions ---Steric clashes Accessible regions ⌅⌅⌅ Sterically permitted ⌅⌅⌅ Single steric clash (outlier region) ⌅⌅⌅ Left- and right-handed ↵-helix regions ⌅⌅⌅ β-strand region .......................... 5 1.4 [Levi-Kalisman et al., 2001] A putative scheme for the organic biomineralisation matrix which grows nacre. Interlamellar matrix sheets are composed mainly of aligned β-chitin fibres in several layers, with acidic glycoproteins at their surface which lead to electron-dense patches (not labelled). Arag- onite biomineralisation occurs in the disordered silk fibroin gel region, most likely nucleating epitaxially on the chitin framework [Weiner et al., 1984]. .............................. 17 1.5 Amino acid sequence of the 30AA N-terminal region of n16, called n16N. An ellipsis indicates where the full n16 sequence continues, and braces indicate suggested subdomains [Brown et al., 2014], sum- marised in table 1.3. Cationic amino acid residues shown in bold blue, anionic residues shown in bold red. The last 14 residues, labelled SD3, represent a highly charged region which may be the mineral assembly subdomain. ............................... 18 vii 1.6 [Amos et al., 2011] Two-stage mineralisation experiment to test whether pre-formed n16N assemblies could nucleate calcium carbonate polymorphs. In stage one, n16N deposits are allowed to form in typical mineralisation con- ditions (50 µMn16N,16h,16◦C). In stage two, washed supports with n16N deposits are transferred to a mineralisation solution with or without n16N content. (A) Calcium carbonate mineralisation without n16N IDP. Calcite polymorph dominates. (B) n16N present during first stage of mineralisation, yielding more vaterite (v). (C,D) n16N present during both stages of mineralisation. The ar- rows indicate fibril-spheroidal deposits of n16N on the exposed surface of a crystal. ............................... 19 2.1 The PRIME20 and PLUM models are identical in their mappings of atoms to coarse-grained sites. All residues feature a single side-chain site, except for glycine which has no side-chain site. The PLUM model backbone maintains its spatial arrangement through continuous- potential bonds, angles and dihedrals as in equation (2.2),whilethe PRIME20 model relies upon square bonds and square pseudo-bonds, seen in fig. 2.1b. ............................. 27 3.1 Ramachandran plots showing the exploration of (φ, ) phase space for PRIME2001 chains, according to the reference [Voegler Smith and Hall, 2001], our independent reproduction, and a reproduction with a modified parameter set. Note that T =0.15 is a high simulation temperature, certainly above that used by the original authors. By modifying the parameter set, it is possible to reproduce the reference data’s accessible regions with moderate accuracy. ........... 37 3.2 Behaviour of a chain of A20 in PRIME2001, PRIME2001-like and PRIME20-like models. After altering the 2001 model to reproduce the authors’ accessible areas (see fig. 3.1), we see here that the hydrogen bond interaction strength, ✏HB,needsraisingto1.26 to match the reference data best. In the PRIME20-like model, ↵-helices are far more stable. Unfortunately, no data for the behaviour of A20 in the canonical PRIME20 model is available. ................ 39 viii 3.3 Ramachandran plots in the custom PRIME2001-like model at T = 0.125,with✏HB =1.26. These plots illustrate that the PRIME2001 data in fig.
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