Metal-Amyloid Networks: Structure and Dynamics Across Reduced and Oxidized States Restricted; Files Only

Sementilli, Anthony (Spring 2021)

Permanent URL: https://etd.library.emory.edu/concern/etds/g445cf39n?locale=pt-BR
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Abstract

In essence, metabolism describes a system of compartmentalized reaction diffusion networks with the goals of anabolizing and catabolizing biomolecules largely through serialized redox events. Nature provides the sole working example of such a system that still escapes comprehensive definition, much less reduction to a simplified model. My primary aim is to construct and structurally define a synthetic metabolon—a self-assembling, catalytic structure capable of performing serialized redox reactions on multiple substrates derived from biomolecular components: amphiphilic amyloid beta (Aβ) peptide and transition metal ions. In this thesis, I first contextualize the past twenty years of Cu-Aβ electrochemistry from the perspective of Marcus Theory and the Entatic State Hypothesis. Herein, I describe how a simple peptide amphiphile, HHQALVFFA-NH2 (K16A), undergoes two-step nucleation to achieve a library of intermediate structures that self-select one morphology over time to propagate as homogeneous fibrils. I next demonstrate how this self-assembling peptide library can be intercepted by metal ions, especially Cu(II), to yield structurally distinct Cu(II)-K16A arrays capable of long-range electron hopping and redox cycling. Lastly, I synthesize my work on Cu(II)-K16A’s chemical prowess with its nuanced assembly mechanism to unveil valence-dependent templation effects on K16A’s assembly coordinate, demonstrating increased assembly and redox kinetics of Cu(I)-K16A over Cu(II)-K16A. These findings reveal a spontaneously organizing system capable of performing multiple redox turnovers reversibly, which we propose can facilitate templated oxidative heterobifunctional polymerization of 6-amino-2-napthaldehyde into a polyamide in the concluding remarks. Utilizing these highly redox-active arrays to cycle electrons from sacrificial donors to fuel polymer synthesis marks an unprecedented dissipative process analogous to natural polypeptide synthesis, providing a first step towards constructing a synthetic metabolism.

Table of Contents

Chapter 1: Electron Transfer in Soluble and Fibrillar Cu-Amyloid Beta 1

1.1 Introduction 1

1.2 Aβ Overview 2

1.3 Coordination Mode Effects on Aβ(1-16)’s Electrochemistry 4

1.4 ‘Poetic’ and Ecstatic Mechanisms for Cu-Aβ Redox 7

1.5 Cu-Aβ Electrochemistry in Unassembled, Pro-Fibrillar Sequences 11

1.6 Structure and Redox Mechanism of Fibrillar Cu-Aβ(1-40/42) 14

1.7 Structural Characterization of ‘Minimal Assemblers’ Aβ(10-21) and Aβ(13-21) 16

1.8 Extended Electron Transfer in Fibrillar Cu-Aβ Models 19

1.9 Concluding Remarks: A Marcus Theory Perspective on Cu-Aβ Redox 26

1.10 References 30

Chapter 2: Liquid-Like Phases Pre-Order Peptides for Supramolecular Assembly 38

2.1 Introduction 40

2.2. Results 41

2.3 Discussion 46

2.4. Supplementary Information 48

2.5 Materials and Methods 53

2.6 Acknowledgements 60

2.7 References 60

Chapter 3: Assembly and Reactivity of Oxidizing Polynuclear Copper-Peptide Arrays 64

3.1 Introduction 65

3.2 Results 66

3.3 Discussion 79

3.4 Supplementary Information 84

3.5 Materials and Methods 105

3.6 Acknowledgements 116

3.7 References 116

Chapter 4: Valence-sensitive template effects on assembly and redox activity of a Cu-amyloid beta peptide network 123

4.1 Introduction 124

4.2 Results 125

4.3 Discussion 137

4.4. Supplementary Information 139

4.5 Materials and Methods 159

4.6 Acknowledgements 166

4.7 References 166

Chapter 5: Next Steps Towards A Synthetic Metabolon 170

5.1. Introduction 170

5.2. Enhancing Cu-K16A’s Coordination Sphere Resolution 170

5.3. Mixed Metal K16A Assemblies 181

5.4. Expanding Redox Active Templates and Conjugates in the K16A System 196

5.5. Applying Cu-K16A’s redox prowess to condense a heterobifunctional model monomer 207

5.6. Outlook 213

5.7 Materials and Methods 214

5.8. References 215

Appendices 219

Appendix A: Constructing peptide models in Maestro 219

Appendix B: Debugging PDB exports 223

Appendix C: Configuring Gromacs for customized force-fields 229

Appendix D: Performing parametrized molecular dynamics on an amyloid array with dummies and/or customized forcefields 233

Appendix E: Including experimental parameters within Gromacs topologies 235

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