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University of Groningen

Structure-Function Relationships in Dynamic Combinatorial Libraries

Altay, Meniz

DOI:

10.33612/diss.90038152

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.

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Publication date: 2019

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Altay, M. (2019). Structure-Function Relationships in Dynamic Combinatorial Libraries. University of Groningen. https://doi.org/10.33612/diss.90038152

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Structure-Function Relationships in

Dynamic Combinatorial Libraries

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Cover Design: Yi˘git Altay - www.yigitaltay.com Printed by: Gildeprint - The Netherlands

ISBN: 978-94-034-1805-6 (print) ISBN: 978-94-034-1804-9 (e-book)

The work described in this thesis was carried out at the Stratingh Institute for Chem-istry, University of Groningen, the Netherlands.

This work financially supported by the European Research Council (ERC), the Netherlands Organisation for Scientific Research (NWO) and the Ministry of Educa-tion, Culture and Science (Gravity program 024.001.035).

Structure-Function Relationships in

Dynamic Combinatorial Libraries

PhD Thesis

to obtain the degree of PhD at the University of Groningen

on the authority of the Rector Magnificus Prof. E. Sterken

and in accordance with the decision by the College of Deans. This thesis will be defended in public on

Friday 6 September 2019 at 11.00 hours

by

Meniz Altay

born on 11 October 1988 in Edirne, Turkey

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Cover Design: Yi˘git Altay - www.yigitaltay.com Printed by: Gildeprint - The Netherlands

ISBN: 978-94-034-1805-6 (print) ISBN: 978-94-034-1804-9 (e-book)

The work described in this thesis was carried out at the Stratingh Institute for Chem-istry, University of Groningen, the Netherlands.

This work financially supported by the European Research Council (ERC), the Netherlands Organisation for Scientific Research (NWO) and the Ministry of Educa-tion, Culture and Science (Gravity program 024.001.035).

Structure-Function Relationships in

Dynamic Combinatorial Libraries

PhD Thesis

to obtain the degree of PhD at the University of Groningen

on the authority of the Rector Magnificus Prof. C. Wijmenga

and in accordance with the decision by the College of Deans. This thesis will be defended in public on

Friday 6 September 2019 at 11.00 hours

by

Meniz Altay

born on 11 October 1988 in Edirne, Turkey

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Supervisors Prof. S. Otto Prof. W. R. Browne Assessment Committee Prof. M. Pittelkow Prof. R. P. Sijbesma Prof. M. D. Witte

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Supervisors Prof. S. Otto Prof. W. R. Browne Assessment Committee Prof. M. Pittelkow Prof. R. P. Sijbesma Prof. M. D. Witte

Contents

1 Advances on Complex Molecular Systems 1

1.1 Introduction . . . 2

1.2 Structure-to-Function in Biology . . . 2

1.3 What is Life? . . . 4

1.4 Steps Towards Synthetic ‘Living’ Systems . . . 5

1.5 Systems Chemistry . . . 6

1.6 Dynamic Combinatorial Chemistry (DCC) . . . 6

1.7 Out-of-equilibrium Systems . . . 7

1.8 Self-Replication . . . 9

1.9 Diversification of Replicators and Molecular Ecosystems . . . 13

1.10 Content and Outline of This Thesis . . . 15

1.11 References . . . 17

2 The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers 21 2.1 Introduction . . . 22

2.2 Results and Discussion . . . 24

2.3 Conclusions . . . 45 2.4 Acknowledgements . . . 46 2.5 Experimental Section . . . 47 2.6 Appendix . . . 49 2.7 References . . . 63 v

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Contents 3 Spacer Length: A Factor for Tuning Self-Replication in Dynamic

Combinatorial Libraries 65

3.1 Introduction . . . 66

3.2 Results and Discussion . . . 67

3.3 Conclusions . . . 83

3.4 Acknowledgements . . . 83

3.5 Experimental Section . . . 84

3.6 Appendix . . . 86

3.7 References . . . 117

4 Parasitic Behavior of Self-Replicating Molecules 119 4.1 Introduction . . . 120

4.2 Results and Discussion . . . 122

4.3 Conclusion . . . 126

4.4 Acknowledgements . . . 127

4.5 Materials and Methods . . . 128

4.6 References . . . 171

5 Towards Replicator Diversification Under Far-from-Equilibrium Con-ditions 175 5.1 Introduction . . . 176

5.2 Results and Discussion . . . 178

5.3 Conclusions . . . 193

5.4 Acknowledgements . . . 194

5.5 Experimental Section . . . 194

5.6 References . . . 203

6 Conclusion and Perspectives 205 6.1 References . . . 209 Summary 211 Samenvatting 213 Acknowledgements 215 vi

Chapter 1

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Contents 3 Spacer Length: A Factor for Tuning Self-Replication in Dynamic

Combinatorial Libraries 65

3.1 Introduction . . . 66

3.2 Results and Discussion . . . 67

3.3 Conclusions . . . 83

3.4 Acknowledgements . . . 83

3.5 Experimental Section . . . 84

3.6 Appendix . . . 86

3.7 References . . . 117

4 Parasitic Behavior of Self-Replicating Molecules 119 4.1 Introduction . . . 120

4.2 Results and Discussion . . . 122

4.3 Conclusion . . . 126

4.4 Acknowledgements . . . 127

4.5 Materials and Methods . . . 128

4.6 References . . . 171

5 Towards Replicator Diversification Under Far-from-Equilibrium Con-ditions 175 5.1 Introduction . . . 176

5.2 Results and Discussion . . . 178

5.3 Conclusions . . . 193

5.4 Acknowledgements . . . 194

5.5 Experimental Section . . . 194

5.6 References . . . 203

6 Conclusion and Perspectives 205 6.1 References . . . 209 Summary 211 Samenvatting 213 Acknowledgements 215 vi

Chapter 1

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2 1. Advances on Complex Molecular Systems

1.1

Introduction

S

cience has always been inspired by nature. What makes nature so attractive is the perfect harmony between its constituents. From a scientific point of view, the key to understand nature is to resolve how it works and evolves over time. Scientists have always been fascinated by the assembly of natural structures and tried to mimic these assemblies to construct different materials. Especially after Darwin’s proposal of the evolution of species from a common ancestor, understanding nature in terms of how life emerged became a more crucial and challenging task. Considering that all living systems have evolved to give enormous diversity from a quite limited variety of resources, it is very impressive that all have different emergent functions as a result of evolution. However, this fascination also brought up debates on how life as we know emerged on earth. Many scientists claim that RNA emerged first since it unites two vital functions in the same molecule: the abilities to store information and to catalyze certain chemical reactions. But over time, theories explaining the origins of life moved beyond RNA. It has been argued that RNA is too large to exist in a prebiotic world and is a relatively poor catalyst. This notion has prompted the search for simpler molecular entities that could lead to the emergence of life. These entities are mostly peptides and nucleobases which are the main constituents of functional proteins and nucleic acids which take part in almost all cellular processes.

In this chapter, we will first give examples on how small structural variations affect protein function. Then we will briefly describe commonly believed and veri-fied hypotheses, covering biological and biochemical evolution and recently developed studies in chemistry to understand origins of life on earth focused on complex molec-ular systems.

1.2

Structure-to-Function in Biology

In biology, even the smallest molecular details can have profound effects on the ul-timate function in life. Take, for example, the difference between methyl and ethyl alcohol: one being a toxic agent and causing blindness while the other is used as mild narcotic. Although sequential similarity is generally considered as a good indicator of functional similarity in proteins, there have been theoretical1and experimental2,3

studies with homologous, or nearly homologous, proteins possessing different or even opposite functions. For example, in 2015, Amir et al. provided a molecular ex-planation for two structurally homologous proteins exerting opposite functions with different interaction phases.4 They performed their study in a class of apoptosis

stimulating proteins (ASPP) and showed that, while one of them (ASPP2) induces apoptosis, the other (iASPP) inhibits it (Figure 1.1).

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1.2. Structure-to-Function in Biology 3

Figure 1.1: a) All the ASPP proteins contain a proline domain (Pro), four ankyrin repeats (Ank) and an SH3 domain. ASPP2 and ASPP1 also contain a putative α-helical domain at their N-termini. The N-terminal part of ASPP2 has the structure of a β-Grasp ubiquitin-like fold (UBL). It has been stated that the N-terminal domain that is unique to ASPP2 is not responsible for the opposite activity in apoptosis regulation. b) Overlapped crystal structures of ASPP2 Ank-SH3 (orange) and iASPP Ank-SH3 (red). The alignment shows the structural similarity between the two protein parts. Figure adapted from reference.4

From an evolutionary point of view, the main information carriers, i.e. the ones that determine function, are the genes. Spontaneous changes in genes direct the ulti-mate diversity in living organisms when the information they carry is translated into proteins. These proteins are responsible for many cellular activities, like catalyzing certain reactions, transporting small molecules etc. They perform their functions with the help of regulatory molecules which are either other enzymes or smaller molecules such as amino acids or nucleotides. While some of these regulators can turn proteins on and off, some others regulate the enzyme activity.5 Considering

that many structural mutations occur spontaneously in nature, even a small change, such as a single base of a gene, results in a single amino acid being changed in the encoded protein, may have a dramatic impact on evolution. In order to understand

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4 1. Advances on Complex Molecular Systems how today’s complex biochemical machineries evolved, one approach is to search for the first/simplest molecule or system that is able to carry out the basic functions of a living system.

1.3

What is Life?

‘What is life?’ is a question that is much more complicated than one might think, to the point that attempts to define ‘life’ are threatening to hinder the actual search of life’s origins. Since the last century, scientists have been trying to reach consensus on how to define life but there is still no clear definition. A full understanding of living systems would possibly require resolving how the first living entity arose on earth.

What is called ‘living’ might differ for each biological species. As Carl Sagan states in the book chapter Definitions of life:6‘Man tends to define life in terms of the

familiar. But the fundamental truths may not be familiar’. Therefore, he introduced five different approaches to define life: 1) physiological: a system capable of eating, reproducing, breathing, growing etc; 2) metabolic: a living system that exchanges materials with surroundings but still has a certain boundary; 3) biochemical: systems that contain hereditary information coded in nucleic acids and metabolism in the form of certain chemical reactions catalyzed and controlled by enzymes; 4) genetic: systems that are able to reproduce and evolve as a result of natural selection and 5) thermodynamic: systems that are open, meaning being dependent on a flow of energy. All these definitions address important aspects of life, but each also misses elements when viewed from a different perspective.

Combining the transition from non-living to living with insights from biological evolution, provides a lot of research questions to explore. After theories related to origins of life proposed by Darwin7 and Oparin,8 the first iconic experiment that

supported these theories was published in 1953 by Stanley Miller and aimed at mim-icking the early atmosphere of earth.9 With electrical sparks in a gas mixture, they

were able to produce some of the vital building blocks of life, such as glycine and ala-nine. Nearly 50 years after this experiment, re-analysis of the residues from Miller’s samples actually showed that all 22 amino acids were present.10Although

geoscien-tists argue that the early atmosphere may not have had such a reducing power,11

this key experiment still supports the idea that localized prebiotic synthesis may have been powerful enough to synthesize the simple building blocks that form the basis of living systems.

Life on earth, as we know it, comprises three main functions: replication, meta-bolism and compartment formation. Although it is extremely difficult to functionally integrate these aspects in a single system, there have been many attempts to create minimal cells: synthetic cellular structures that contain important features of ‘living’

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1.4. Steps Towards Synthetic ‘Living’ Systems 5 cells in biology.12–14Recent examples will be discussed in the following subchapters.

1.4

Steps Towards Synthetic ‘Living’ Systems

Life that we know today is a highly complex and dynamically evolving system. In a commonly believed prebiotic scenario, life could have started from simple organic molecules that were stable in the harsh conditions of early earth which then formed larger biomolecules. After this stage, those biomolecules may have started to inter-act with each other, thus fulfilling different functions. When membrane-like species started to form, less stable biopolymers could have been isolated in such environ-ments allowing them to participate in biochemical evolution.15Depending on such a

scenario, different scientific areas approach evolution by investigating different life-like functions such as replication, metabolic activity or formation of cell-life-like com-partments. While chemists have mostly focused on information carrying molecules potentially capable of undergoing evolution, the synthesis of replicating minimal cells has been one of the major focusses in synthetic biology.

Figure 1.2: a) A possible pathway a synthetic cell by merging a replicase with a self-replicating vesicle. b) Proposal of vesicle growth from a bilayer forming precursors followed by division, either spontaneously, or by an external stimulus. Figure adapted from reference.16

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6 1. Advances on Complex Molecular Systems Even the simplest compartmentalized living entities that we know are comprised of a drastic number of expressed proteins and catalytic reactions. Therefore, it is crit-ical to define what is minimal, in order to define what is an artificial cell and which functions/reactions must be carried out. In their review published in 2001, Szostak and co-workers describe their designed protocells as compartmentalized entities com-prised of a replicating RNA replicase in a replicating membrane vesicle.16 Although

in that form the protocell is still incapable of autonomous reproduction, they claim that coupling it with ribozymes that can synthesize lipids for membrane-growth might allow the ‘living’ protocell to act as an autonomously replicating system. Figure 1.2 summarizes two proposed pathways towards the synthesis of life.

1.5

Systems Chemistry

In nature, every biophysical process happens through interactions between different (classes of) molecules. While lipid-like bio(macro)molecules keep the cellular ma-terials isolated and achieve chemical transport, different proteins inside the cell are responsible for keeping the cell alive. Each vital function is achieved through ordered assembly of molecules and their co-operation with each other. Learning and mimick-ing the nature would require to study its constituents with a systems approach.

Systems chemistry is a relatively new field in chemistry that deals with dynami-cally complex systems that are comprised of structurally relatively simple molecules. The term was first used in a study by von Kiedrowski in 2005 where auto- and cross-catalysis was achieved in a Diels-Alder reaction.17Since then, this new concept

has been developed by utilizing oscillating reactions,18self-assembling materials,19,20

dynamic combinatorial chemistry,21 out-of-equilibrium systems22,23 etc. Complex

chemical networks are one of the major focusses of systems chemistry together with (Darwinian) approaches to the origins of life and aspects of material science.

1.6

Dynamic Combinatorial Chemistry (DCC)

Dynamic combinatorial chemistry is a useful tool to develop new, and possibly not so easy to synthesize, molecules with the help of reversible covalent linkages.24 The

most widely used dynamic covalent reactions in DCC are disulfide, acetal, imine and hydrazone exchange.21Building on concepts in supramolecular chemistry, DCC gives

access to adaptive systems through templated synthesis and intra- and intermolecular assembly processes.25 Since dynamic combinatorial libraries (DCLs) are generally

under thermodynamic control, library distribution can easily be altered by external templates or self-templating.26,27 Figure 1.3 shows an overview of template-induced

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1.7. Out-of-equilibrium Systems 7 processes in DCLs.

Figure 1.3: Cartoon representation for different template induced processes in DCC me-diated by a) an external guest, b) an external host or by self-templating that is either c) intramolecular or d) intermolecular. Figure adapted from references.26,27

1.7

Out-of-equilibrium Systems

Nature is a highly dynamic system and possesses many functional characteristics which have inspired scientists for a very long time. Some of these functions are the result of thermodynamically stable assemblies, like lipid bilayer membranes, while more complex functions require constant input of matter and energy. It is useful to classify the different thermodynamic regimes in nature and in supramolecular chemistry.28 Early examples of supramolecular chemistry mostly involved

thermo-dynamically stable assemblies, like complex interlocked molecules or supramolecular polymers.29–31More recently, attention has shifted to kinetically controlled systems.

Such systems are either in a kinetically trapped state from which they may or may not transform into the thermodynamically stable state (Figure 1.4b) or in a dynamic high-energy state that can only be sustained with a constant input of energy (Figure 1.4c).

For example, kinetically controlled self-assembly processes can give rise to dif-ferent nanostructures depending on external stimuli. Ulijn and co-workers reported such a system with short peptide building blocks.32 In the study, they used

Fmoc-dipeptide precursors with different substituents in the R positions (tyrosine, phenyl alanine, leucine or valine) for self-assembly and a hydrolytic enzyme (subtilisin) that hydrolyzes methyl ester precursors to self-assembling peptide derivatives (Figure 1.5). Nucleation and early growth happen at site of enzyme action as evident from AFM images which show enzymes as bright spots at the end of newly-formed fibers. Since

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8 1. Advances on Complex Molecular Systems

Figure 1.4: Thermodynamic regimes observed in chemical systems. a) Thermodynamic equilibrium: final state is determined by the Boltzmann distribution and irrelevant of the pathway. b) Kinetic control: final distribution depends on the synthetic pathway. c) Far from equilibrium systems in which continuous energy supply is required to persist. Final dis-tribution reflects the balance between continuous synthesis and degradation. Figure adapted from reference.28

the self-assembly occurs as a result of enzyme activity (hydrolysis), the rate of growth and higher order chirality in some cases can be altered by varying the amount of en-zyme.

In addition to self-assembly of small-scale building blocks, supramolecular poly-mers of larger molecules can also be formed under kinetic control. Transformations under different experimental conditions can result in helicity inversions,30 or

differ-Figure 1.5: Chemical structure of Fmoc-dipeptides that hydrolytic enzymes convert from a methyl ester (top) into a gelating carboxylic acid (bottom). Supramolecular assemblies (blue/yellow tube) are formed from these building blocks in solution. The assemblies consti-tute the framework for the gel in which enzymes (coloured ribbon structure) are embedded. The enzymes appear as bright spots at the fibre ends in the atomic force microscope image (right). Different enzyme concentrations yield different gel strengths. Figure adapted from reference.32

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1.8. Self-Replication 9 ent polymorphic self-assembling structures.33More recently, out-of-equilibrium

self-assembly has been combined with another process popular in material science: living supramolecular polymerization. Living polymerization provides better control and uniformity (lower polydispersity) to supramolecular polymers in which chain growth occurs only with an initiator.34 The first example was reported by Takeuchi and

co-workers in 2014.35They showed that self-assembling structures that are produced

from a porphyrin derivative follow two different aggregation pathways depending on kinetics, resulting in nanoparticles or fibers. While the nanoparticles are formed as kinetically stable products, they transform into fibers upon addition of a small aliquot from the solution containing nanofibers (initiators).

Figure 1.6: Cartoon representation of formation and transformation mechanism of supramolecular polymers made from porphyrin based monomers (1mono). Monomers in hot

methylcyclohexane solution self-assemble into nanoparticles (1j-agg) upon cooling. When this

nanoparticle solution is left unagitated, nanoparticles are transformed into fibers (1H-agg).

Both steps are reversible and it was reported that the transformation of nanoparticles into fibers was significantly faster in the presence of a small amount of fiber as initiator. Figure adapted from reference.35

Out-of-equilibrium systems are not only developed in material science but are also highly relevant for understanding the origins of life in terms of replication, speciation and adaptation. These topics will be discussed in the following sections.

1.8

Self-Replication

As we briefly discussed earlier in this chapter, self-replication is one of the prereq-uisites to call something ‘living’. No matter how the first living entities formed on

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10 1. Advances on Complex Molecular Systems earth, evolvable life would not be possible if those entities were not capable of making copies of themselves. In biology, genetic information is copied by replication of DNA during cell division, which is a process highly dependent on complex enzymes. Short RNA primers are required for the synthesis of DNA which lends some support for the RNA world hypothesis. These biologically vital molecules inspire scientists not only to construct new molecular networks that mimic biology but also to search for non-enzymatic replicating systems. Considering the fact that life on earth may have evolved from molecules that are much simpler than RNA, peptides and nucleobases would be the best candidates as they are the constituents of proteins and RNA, re-spectively. The minimal autocatalytic cycle features a template-directed synthesis of the autocatalytically active molecule.36According to this model, molecules A and B

first react to form either binary complex Tinactive or template molecule T (Figure

1.7a). When the template forms, it enters to the autocatalytic cycle by interacting with precursor molecules A and B which then react to form a dimer of the tem-plate molecule. Only if this dimer ([T.T]) is capable of dissociating into two distinct template molecules (T), the autocatalytic cycle can be completed. Figure 1.7b and Figure 1.7c show possible kinetic profiles in a such minimal system depending on the reaction dynamics.37,38

Figure 1.7: a) Cartoon representation of a minimal self-replicating cycle b) and c) possible kinetic profiles for the autocatalytic growth. Figure adapted from references.36–38

The first non-enzymatic replicating system was reported by von Kiedrowski in 1986.39In his study, he used two trinucleotides to form a hexamer with a palindromic

sequence. Therefore, the hexamer could template its own production. Following their pioneering contribution on self-replicating molecules, the same group, in 2014,

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1.8. Self-Replication 11 reported one of the first examples of template-directed synthesis of self-replicating peptide nucleic acids (PNAs) (Figure 1.8).40 In this study, they set up a reaction

network using water soluble carbodiimide (EDC) as a coupling agent to mediate imidazole catalyzed PNA ligation. Kinetic modelling studies verified the parabolic growth characteristics of the replicator.

In addition to von Kiedrowski’s studies, there have been many contributions to synthetic self-replicating systems.41–43Apart from nucleic acid-based design of

self-replicators, peptides are another important class of molecules in this area. The first

Figure 1.8: a) Chemical structures of building blocks for the self-replicating system based on PNA. Trimeric building blocks A and B react to give self-complementary hexa-PNA (T) upon condensation. Green: solubility enhancer; red: ligation site; blue: fluorine label; b) minimal model for the self-replication. Hexa-PNA (T) catalyzes its own formation from building blocks A and B with an autocatalytic ligation reaction. Figure adapted from reference.40

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12 1. Advances on Complex Molecular Systems self-replicating peptide was studied by Ghadiri’s group and dates back to 1996.44In

their study, they reported that a 32-residue α-helical peptide acts autocatalytically and templates its own synthesis from 15- and 17- residue fragments by amide bond condensation. Considering that nucleic acids can provide easier complementary in-teractions than peptides, their peptide-based study is the first that overcomes this inherent challenge. Additionally, achieving self-replication in an α-helical design is important since many naturally occurring proteins fold into α-helical coiled coils. After their discovery, Ghadiri’s research group reported many more replicators based on peptides.45–47In addition, other scientists also made prominent contributions to

peptide based self-replication including Chmielewski48,49 and Ashkenasy.50,51

Figure 1.9: General replication mechanism discovered by the Otto research group. First, dithiol-bearing building blocks are oxidized and give a dynamic disulfide exchange pool that contains differently sized macrocycles. When one of the species is capable of forming small stacks (self-nucleation), the equilibrium shifts towards more of this product and the small stacks are elongated into fibers. Upon mechanical agitation, fibers break into shorter fragments increasing the number of growing fiber ends, giving rise to an autocatalytic cycle.

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1.9. Diversification of Replicators and Molecular

Ecosystems 13

first synthetic peptide replicators can also self-replicate, driven by self-organization into ordered structures. Dynamic combinatorial chemistry served as a powerful tool to access these complex systems from simpler molecular entities. Our group made an important contribution following the discovery of a mechano-sensitive self-replicator in 2010.52Self-replicators emerged spontaneously from DCLs prepared from building

blocks bearing aromatic dithiol unit for disulfide exchange and a short peptide tail (Figure 1.9). The peptide contains alternating hydrophilic and hydrophobic residues which promote self-assembly by means of β-sheet formation. After this discovery, the self-assembly of the self-replicator has been studied both theoretically and ex-perimentally.53,54Furthermore, dynamic multi-building block systems and auto- and

cross-catalysis in complex molecular networks have been studied. Some representa-tive examples will be discussed in the following chapter and throughout this thesis.

1.9

Diversification of Replicators and Molecular

Ecosystems

The interplay between self-replicating molecules is an important topic in under-standing the origins of life on earth. Until recently, studies were only focusing on single replicators in isolated environments. However, scientists now start to study co-operation and competition in multi-building block systems. Some early exam-ples have been reported by Lehman,55,56 Ashkenasy57,58 and Philp.59–62 In one of

the studies, in 2017, Philp reported a molecular network in which self-replicating templates were produced from two maleimides and two nitrones with different sizes (Figure 1.10a).63When these molecules react via 1,3-dipolar cycloaddition reactions,

they produce four differently sized replicator templates. In isolation, three out of four of the templates can trigger their own formation from the constituents (SNSM, SNLM and LNLM). However, when the network is constructed from all four indi-vidual molecules without any template instruction, all four replicators are produced with significant percentages. Among these template molecules, only two of them can cross-catalyze the formation of each other in a cross-catalytic cycle (SNLMÑ LNSM and LNSMÑ SNLM). When one of the instructing templates is added, specific auto-and cross-catalytic behavior is observed, in each case in a predictable way (Figure 1.10b). The study clearly exemplifies how system-level responses can be generated from simple molecules.

In addition to these studies mainly based on RNA, α-helical peptides and other synthetic molecules, our group made an important contribution to dynamic molecular networks specifically based on self-replicating peptides. Diversification of replicators can be achieved by using multiple building block systems. In 2016, Sadownik et. al.

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14 1. Advances on Complex Molecular Systems reported such a system in which two sets of co-existing replicators compete for two common building blocks.64As one set of replicators is the ancestor of the second set,

the system shows behavior that resembles the process by which new species form in biology.

Figure 1.10: System developed by the Philp research group; a) Chemical structures of the replicator precursors, b) four replicator molecules and diagram summarizing the auto- and cross-catalytic behavior in a single input system. Figure adapted from reference.63

As evolution is probably not possible for species existing in isolation, it is relevant to investigate how co-existing self-replicators affect each other. Recently we reported the emergence of a new self-replicator (16) based on a threonine containing building

block that was directed by an pre-existing one (48) (Figure 1.11).65 The formation

of the 6-ring replicator occurred only when seeded with an 8-ring replicator but not upon seeding with any other 6-ring replicator. This system features an important ingredient for evolution: replicator mutation.

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1.10. Content and Outline of This Thesis 15

Figure 1.11: Building block structures and different replicators that showed selective cross-catalysis. Figure adapted from reference.65

1.10

Content and Outline of This Thesis

Research into the origins of life is an important topic in systems chemistry. Since Darwinian evolution possibly started right after the emergence of first replicating species, the development of multi-replicator systems would be the next step to syn-thesize life de-novo. In this thesis, we take advantage of dynamic combinatorial chemistry to construct such systems from peptide based building blocks and investi-gated how small structural variations in these building blocks affect self-replication and the resulting self-assembly processes.

In Chapter 2 we used structurally closely related building blocks to control com-position and length of self-synthesizing supramolecular assemblies and synthesized

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16 1. Advances on Complex Molecular Systems supramolecular block-copolymers with varying composition and unprecedented low polydispersity indices. We modified one of the building blocks by introducing halogen atoms to one of the amino acid’s side chain and attempted the direct visualization of the block-copolymers by electron microscopy.

In Chapter 3 we investigated self-replicating behavior using building blocks with small structural variations in the peptide backbone. Without effecting the H-bonding propensity of the peptide chain, we were able to obtain differently sized self-replicators. In addition, we also showed how the environment affects the size of self-replicators in a single building block system. Lastly, we checked the history dependence in multi-building block DCLs made from structurally closely related pep-tide building blocks that all form differently sized self-assemblies.

Chapter 4 describes the emergence of a parasitic replicator which owes its exis-tence to another structurally related replicator in the same environment. Unidirec-tional parasitic behavior resulted from the disassembly of the pre-existing one in the cross-catalytic process. We were able to alter the composition of the parasitic repli-cator in two ways: changing the amount of the cross-seed or repeating cross-seeding events until the parasite becomes homogeneous and contains no trace of the initial replicator.

To achieve diversification in a dynamic system, in Chapter 5 we constructed a continuous flow set-up that infuses nutrients required for replication with constantly changing composition and outflows material to keep the population size constant. We tried to produce a continuous series of cross-catalytic replicators of which the final one should not be capable of cross-catalyzing formation of the original ancestor. Finally, Chapter 6 provides an overview and evaluation of the impact of our studies in the context of dynamic combinatorial chemistry in particular and systems chemistry and the origin of life / synthesis of de-novo life in general.

1.11. References 17

1.11

References

[1] Keskin, O.; Nussinov, R. Protein Eng. Des. Sel. 2005, 18, 11-24.

[2] Bioorganic Chemistry Frontiers - Volume 1; Springer-Verlag Berlin Heidelberg: 1990.

[3] Murzin, A. G. Trends Biochem. Sci. 1993, 18, 403-405.

[4] Amir, A. I.; van Rosmalen, M.; Mayer, G.; Lebendiker, M.; Danieli, T.; Friedler, A. Sci. Rep. 2015, 5, 11629.

[5] Petsko, G. A.; Ringe, D. Protein Structure and Function; Oxford University Press Inc.: 2014.

[6] Bedau, M. A.; Cleland, C. E. The Nature of Life:Classical and Contemporary Perspectives from Philosophy and Science; Cambridge University Press: 2010. [7] Darwin, C. On the Origin of Species by Means of Natural Selection, or the

Preservation of Favoured Races in the Struggle for Life; John Murray: 1859. [8] Oparin, A. I. The Origin of Life; New York: MacMillan: 1938.

[9] Miller, S. L. Science 1953, 117, 528-529.

[10] Johnson, A. P.; Cleaves, H. J.; Dworkin, J. P.; Glavin, D. P.; Lazcano, A.; Bada, J. L. Science 2008, 322, 404.

[11] Deamer, D. W. Microbiol. Mol. Biol. Rev. 1997, 61, 239-261.

[12] Luisi, P. L.; Ferri, F.; Stano, P. Naturwissenschaften 2006, 93, 1-13.

[13] Stano, P.; Carrara, P.; Kuruma, Y.; Souza, T.; Luisi, P. L. J. Mater. Chem. 2011, 21, 18887-18902.

[14] Stano, P.; Luisi, P. L. Curr. Opin. In Biol. 2013, 24, 633-638.

[15] Fitz, D.; Reiner, H.; M., R. B. Pure Appl. Chem. 2007, 79, 2101-2117. [16] Szostak, J. W.; Bartel, D. P.; Luisi, P. L. Nature 2001, 409, 387-390.

[17] Kindermann, M.; Stahl, I.; Reimold, M.; Pankau, W. M.; von Kiedrowski, G. Angew. Chem. Int. Ed. 2005, 44, 6750-6755.

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16 1. Advances on Complex Molecular Systems supramolecular block-copolymers with varying composition and unprecedented low polydispersity indices. We modified one of the building blocks by introducing halogen atoms to one of the amino acid’s side chain and attempted the direct visualization of the block-copolymers by electron microscopy.

In Chapter 3 we investigated self-replicating behavior using building blocks with small structural variations in the peptide backbone. Without effecting the H-bonding propensity of the peptide chain, we were able to obtain differently sized self-replicators. In addition, we also showed how the environment affects the size of self-replicators in a single building block system. Lastly, we checked the history dependence in multi-building block DCLs made from structurally closely related pep-tide building blocks that all form differently sized self-assemblies.

Chapter 4 describes the emergence of a parasitic replicator which owes its exis-tence to another structurally related replicator in the same environment. Unidirec-tional parasitic behavior resulted from the disassembly of the pre-existing one in the cross-catalytic process. We were able to alter the composition of the parasitic repli-cator in two ways: changing the amount of the cross-seed or repeating cross-seeding events until the parasite becomes homogeneous and contains no trace of the initial replicator.

To achieve diversification in a dynamic system, in Chapter 5 we constructed a continuous flow set-up that infuses nutrients required for replication with constantly changing composition and outflows material to keep the population size constant. We tried to produce a continuous series of cross-catalytic replicators of which the final one should not be capable of cross-catalyzing formation of the original ancestor. Finally, Chapter 6 provides an overview and evaluation of the impact of our studies in the context of dynamic combinatorial chemistry in particular and systems chemistry and the origin of life / synthesis of de-novo life in general.

1.11. References 17

1.11

References

[1] Keskin, O.; Nussinov, R. Protein Eng. Des. Sel. 2005, 18, 11-24.

[2] Bioorganic Chemistry Frontiers - Volume 1; Springer-Verlag Berlin Heidelberg: 1990.

[3] Murzin, A. G. Trends Biochem. Sci. 1993, 18, 403-405.

[4] Amir, A. I.; van Rosmalen, M.; Mayer, G.; Lebendiker, M.; Danieli, T.; Friedler, A. Sci. Rep. 2015, 5, 11629.

[5] Petsko, G. A.; Ringe, D. Protein Structure and Function; Oxford University Press Inc.: 2014.

[6] Bedau, M. A.; Cleland, C. E. The Nature of Life:Classical and Contemporary Perspectives from Philosophy and Science; Cambridge University Press: 2010. [7] Darwin, C. On the Origin of Species by Means of Natural Selection, or the

Preservation of Favoured Races in the Struggle for Life; John Murray: 1859. [8] Oparin, A. I. The Origin of Life; New York: MacMillan: 1938.

[9] Miller, S. L. Science 1953, 117, 528-529.

[10] Johnson, A. P.; Cleaves, H. J.; Dworkin, J. P.; Glavin, D. P.; Lazcano, A.; Bada, J. L. Science 2008, 322, 404.

[11] Deamer, D. W. Microbiol. Mol. Biol. Rev. 1997, 61, 239-261.

[12] Luisi, P. L.; Ferri, F.; Stano, P. Naturwissenschaften 2006, 93, 1-13.

[13] Stano, P.; Carrara, P.; Kuruma, Y.; Souza, T.; Luisi, P. L. J. Mater. Chem. 2011, 21, 18887-18902.

[14] Stano, P.; Luisi, P. L. Curr. Opin. In Biol. 2013, 24, 633-638.

[15] Fitz, D.; Reiner, H.; M., R. B. Pure Appl. Chem. 2007, 79, 2101-2117. [16] Szostak, J. W.; Bartel, D. P.; Luisi, P. L. Nature 2001, 409, 387-390.

[17] Kindermann, M.; Stahl, I.; Reimold, M.; Pankau, W. M.; von Kiedrowski, G. Angew. Chem. Int. Ed. 2005, 44, 6750-6755.

(25)

18 1. Advances on Complex Molecular Systems [19] Maiti, S.; Fortunati, I.; Ferrante, C.; Scrimin, P.; Prins, L. J. Nat. Chem.

2016, 8, 725-731.

[20] Pezzato, C.; Prins, L. J. Nat. Commun. 2015, 6, 7790.

[21] Corbett, P. T.; Leclaire, J.; Vial, L.; West, K. R.; Wietor, J. L.; Sanders, J. K. M.; Otto, S. Chem. Rev. 2006, 106, 3652-3711.

[22] Hess, H.; Ross, J. L. Chem. Soc. Rev. 2017, 46, 5570-5587.

[23] Sorrenti, A.; Leire-Iglesias, J.; Markvoort, A. J.; de Greef, T. F. A.; Her-mans, T. M. Chem. Soc. Rev. 2017, 46, 5476-5490.

[24] Schaufelberger, F.; Timmer, B. J. J.; Ramstr¨om, O. Dynamic Covalent Chem-istry: Principles, Reactions, and Applications; John Wiley Sons: Chichester: 2018.

[25] Kom´aromy, D.; Nowak, P.; Otto, S. Dynamic Covalent Chemistry: Principles, Reactions, and Applications; John Wiley Sons: Chichester: 2018.

[26] Beeren, S. R.; Sanders, J. K. M. Dynamic Combinatorial Chemistry; Wiley-VCH: 2010.

[27] Otto, S. Acc. Chem. Res. 2012, 45, 2200-2210.

[28] Mattia, E.; Otto, S. Nat. Nanotechnol. 2015, 10, 111-119. [29] de Greef, T. F. A.; Meijer, E. W. Nature 2008, 453, 171-173.

[30] Korevaar, P. A.; George, S. J.; Markvoort, A. J.; Smulders, M. M. J.; Hilbers, P. A. J.; Schening, A. P. H. J.; de Greef, T. F. A.; Meijer, E. W. Nature 2012, 481, 492-496.

[31] Ponnuswamy, N.; Cougnon, F. B. L.; M., C. J.; Dan Panto¸s, G.; Sanders, J. K. M. Science 2012, 338, 783-785.

[32] Hirst, A. R.; Roy, S.; Arora, M.; Das, A. K.; Hodson, N.; Murray, P.; Mar-shall, S.; Javid, N.; Sefcik, J.; Boekhoven, J.; van Esch, J. H.; Santabarbara, S.; Hunt, N. T.; Ulijn, R. V. Nat. Chem. 2010, 2, 1089-1094.

[33] Tevis, I. D.; Palmer, L. C.; Herman, D. J.; Murray, I. P.; Stone, D. A.; Stupp, S. I. J. Am. Chem. Soc. 2011, 133, 16486-16494.

[34] Mukhopadhyay, R. D.; Ajayaghosh, A. Science 2015, 349, 241-241.

1.11. References 19

[35] Ogi, S.; Sugiyasu, K.; Manna, S.; Samitsu, S.; Takeuchi, M. Nat. Chem. 2014, 6, 188-195.

[36] Duim, H.; Otto, S. Beilstein J. Org. Chem. 2017, 13, 1189-1203.

[37] Dadon, Z.; Wagner, N.; Ashkenasy, G. Angew. Chem. Int. Ed. 2008, 47, 6128-6136.

[38] von Kiedrowski, G. Minimal Replicator Theory I: Parabolic Versus Exponential Growth; Springer: Berlin, Heidelberg: 1993.

[39] von Kiedrowski, G. Angew. Chem. Int. Ed. 1986, 25, 932-935.

[40] Pl¨oger, T. A.; von Kiedrowski, G. Org. Biomol. Chem. 2014, 12, 6908-6914. [41] Bag, B. J.; von Kiedrowski, G. Pure Appl. Chem. 2009, 68, 2145-2152. [42] Bissette, A. J.; Fletcher, S. L. Angew. Chem. Int. Ed. 2013, 52, 12800-12826. [43] Vidonne, A.; Philp, D. Eur. J. Org. Chem. 2009, 5, 593-610.

[44] Lee, D. H.; Granja, J. R.; Martinez, J. A.; Severin, K.; Ghadiri, M. R. Nature 1996, 382, 525-528.

[45] Ashkenasy, G.; Jagasia, R.; Yadav, M.; Ghadiri, M. R. Proc. Natl. Acad. Sci. USA 2004, 101, 10872-10877.

[46] Saghtelian, A.; Yobobayeshi, Y.; Soltani, K.; Ghadiri, M. R. Nature 2001, 409, 797-801.

[47] Severin, K.; Lee, D. H.; Martinez, J. A.; Ghadiri, M. R. Chem.-Eur. J. 1997, 3, 1017-1024.

[48] Isaac, R.; Ham, Y. W.; Chmielewski, J. Curr. Opin. Struct. Biol. 2001, 11, 458-463.

[49] Yao, S.; Ghosh, I.; Zutshi, R.; Chmielewski, J. Nature 1998, 396, 447-450. [50] Rubinov, B.; Wagner, N.; Rapaport, H.; Ashkenasy, G. Angew. Chem. Int.

Ed. 2009, 48, 6683-6686.

[51] Rubinov, B.; Wagner, N.; Matmor, M.; Regev, O.; Ashkenasy, N.; Ashke-nasy, G. ACS Nano 2012, 6, 7893-7901.

[52] Carnall, J. M. A.; Waudby, C. A.; Belenguer, A. M.; Stuart, M. C.; Peyralans, J. J. P.; Otto, S. Science 2010, 327, 1502-1506.

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18 1. Advances on Complex Molecular Systems [19] Maiti, S.; Fortunati, I.; Ferrante, C.; Scrimin, P.; Prins, L. J. Nat. Chem.

2016, 8, 725-731.

[20] Pezzato, C.; Prins, L. J. Nat. Commun. 2015, 6, 7790.

[21] Corbett, P. T.; Leclaire, J.; Vial, L.; West, K. R.; Wietor, J. L.; Sanders, J. K. M.; Otto, S. Chem. Rev. 2006, 106, 3652-3711.

[22] Hess, H.; Ross, J. L. Chem. Soc. Rev. 2017, 46, 5570-5587.

[23] Sorrenti, A.; Leire-Iglesias, J.; Markvoort, A. J.; de Greef, T. F. A.; Her-mans, T. M. Chem. Soc. Rev. 2017, 46, 5476-5490.

[24] Schaufelberger, F.; Timmer, B. J. J.; Ramstr¨om, O. Dynamic Covalent Chem-istry: Principles, Reactions, and Applications; John Wiley Sons: Chichester: 2018.

[25] Kom´aromy, D.; Nowak, P.; Otto, S. Dynamic Covalent Chemistry: Principles, Reactions, and Applications; John Wiley Sons: Chichester: 2018.

[26] Beeren, S. R.; Sanders, J. K. M. Dynamic Combinatorial Chemistry; Wiley-VCH: 2010.

[27] Otto, S. Acc. Chem. Res. 2012, 45, 2200-2210.

[28] Mattia, E.; Otto, S. Nat. Nanotechnol. 2015, 10, 111-119. [29] de Greef, T. F. A.; Meijer, E. W. Nature 2008, 453, 171-173.

[30] Korevaar, P. A.; George, S. J.; Markvoort, A. J.; Smulders, M. M. J.; Hilbers, P. A. J.; Schening, A. P. H. J.; de Greef, T. F. A.; Meijer, E. W. Nature 2012, 481, 492-496.

[31] Ponnuswamy, N.; Cougnon, F. B. L.; M., C. J.; Dan Panto¸s, G.; Sanders, J. K. M. Science 2012, 338, 783-785.

[32] Hirst, A. R.; Roy, S.; Arora, M.; Das, A. K.; Hodson, N.; Murray, P.; Mar-shall, S.; Javid, N.; Sefcik, J.; Boekhoven, J.; van Esch, J. H.; Santabarbara, S.; Hunt, N. T.; Ulijn, R. V. Nat. Chem. 2010, 2, 1089-1094.

[33] Tevis, I. D.; Palmer, L. C.; Herman, D. J.; Murray, I. P.; Stone, D. A.; Stupp, S. I. J. Am. Chem. Soc. 2011, 133, 16486-16494.

[34] Mukhopadhyay, R. D.; Ajayaghosh, A. Science 2015, 349, 241-241.

1.11. References 19

[35] Ogi, S.; Sugiyasu, K.; Manna, S.; Samitsu, S.; Takeuchi, M. Nat. Chem. 2014, 6, 188-195.

[36] Duim, H.; Otto, S. Beilstein J. Org. Chem. 2017, 13, 1189-1203.

[37] Dadon, Z.; Wagner, N.; Ashkenasy, G. Angew. Chem. Int. Ed. 2008, 47, 6128-6136.

[38] von Kiedrowski, G. Minimal Replicator Theory I: Parabolic Versus Exponential Growth; Springer: Berlin, Heidelberg: 1993.

[39] von Kiedrowski, G. Angew. Chem. Int. Ed. 1986, 25, 932-935.

[40] Pl¨oger, T. A.; von Kiedrowski, G. Org. Biomol. Chem. 2014, 12, 6908-6914. [41] Bag, B. J.; von Kiedrowski, G. Pure Appl. Chem. 2009, 68, 2145-2152. [42] Bissette, A. J.; Fletcher, S. L. Angew. Chem. Int. Ed. 2013, 52, 12800-12826. [43] Vidonne, A.; Philp, D. Eur. J. Org. Chem. 2009, 5, 593-610.

[44] Lee, D. H.; Granja, J. R.; Martinez, J. A.; Severin, K.; Ghadiri, M. R. Nature 1996, 382, 525-528.

[45] Ashkenasy, G.; Jagasia, R.; Yadav, M.; Ghadiri, M. R. Proc. Natl. Acad. Sci. USA 2004, 101, 10872-10877.

[46] Saghtelian, A.; Yobobayeshi, Y.; Soltani, K.; Ghadiri, M. R. Nature 2001, 409, 797-801.

[47] Severin, K.; Lee, D. H.; Martinez, J. A.; Ghadiri, M. R. Chem.-Eur. J. 1997, 3, 1017-1024.

[48] Isaac, R.; Ham, Y. W.; Chmielewski, J. Curr. Opin. Struct. Biol. 2001, 11, 458-463.

[49] Yao, S.; Ghosh, I.; Zutshi, R.; Chmielewski, J. Nature 1998, 396, 447-450. [50] Rubinov, B.; Wagner, N.; Rapaport, H.; Ashkenasy, G. Angew. Chem. Int.

Ed. 2009, 48, 6683-6686.

[51] Rubinov, B.; Wagner, N.; Matmor, M.; Regev, O.; Ashkenasy, N.; Ashke-nasy, G. ACS Nano 2012, 6, 7893-7901.

[52] Carnall, J. M. A.; Waudby, C. A.; Belenguer, A. M.; Stuart, M. C.; Peyralans, J. J. P.; Otto, S. Science 2010, 327, 1502-1506.

(27)

20 1. Advances on Complex Molecular Systems [53] Frederix, P. W. J. M.; Id´e, J.; Altay, Y.; Schaeffer, G.; Surin, M.; Beljonne, D.; Bondarenko, A. S.; Jansen, T. L. C.; Otto, S.; Marrink, S. J. ACS Nano 2017, 11, 7858-7868.

[54] Mattia, E.; Pal, A.; Leonetti, G.; Otto, S. Synlett 2017, 139, 13612-13615. [55] Higgs, P. G.; Lehman, N. Nat. Rev. Genet. 2015, 16, 7-17.

[56] Vaidya, N.; Manapat, M. L.; Chen, I. A.; Xulvi-Brunet, R.; Hayden, E. J.; Lehman, N. Nature 2012, 491, 72-77.

[57] Dadon, Z.; Wagner, N.; Alasibi, S.; Samiappan, M.; Mukherjee, R.; Ashke-nasy, G. Chem.-Eur. J. 2015, 21, 648-654.

[58] Nanda, J.; Rubinov, B.; Ivnitski, D.; Mukherjee, R.; Shtelman, E.; Motro, T.; Miller, Y.; Wagner, N.; Luria, R. C.; Ashkenasy, G. Nat. Commun. 2017, 8, 434.

[59] Kosikova, T.; Mackenzie, H.; Philp, D. Chem.-Eur. J. 2016, 22, 1831-1839. [60] Kosikova, T.; Philp, D. J. Am. Chem. Soc. 2017, 139, 12579-12590.

[61] Sadownik, J. W.; Philp, D. Org. Biomol. Chem. 2015, 13, 10392-10401. [62] Sadownik, J. W.; Kosikova, T.; Philp, D. J. Am. Chem. Soc. 2017, 139,

17565-17573.

[63] del Amo, V.; Philp, D. Chem.-Eur. J. 2010, 16, 13304-13318.

[64] Sadownik, J. W.; Mattia, E.; Nowak, P.; Otto, S. Nat. Chem. 2016, 8, 264-269. [65] Altay, Y.; Tezcan, M.; Otto, S. J. Am. Chem. Soc. 2017, 139, 13612-13615.

Parts of this chapter has been published in:

A. Pal, M. Malakoutikhah, G. Leonetti, M. Tezcan, M. Colomb-Delsuc, V.D. Nguyen, J. van der Gucht, S. Otto. “Controlling the Structure and Length of Self-Synthesizing Supramolecular Polymers through Nucleated Growth and Disassembly.”, Angew. Chem. Int. Ed. 2015, 54, 7852-7856.

Chapter 2

The Influence of Building Block Design on

the Outcome of Type and Size of

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20 1. Advances on Complex Molecular Systems [53] Frederix, P. W. J. M.; Id´e, J.; Altay, Y.; Schaeffer, G.; Surin, M.; Beljonne, D.; Bondarenko, A. S.; Jansen, T. L. C.; Otto, S.; Marrink, S. J. ACS Nano 2017, 11, 7858-7868.

[54] Mattia, E.; Pal, A.; Leonetti, G.; Otto, S. Synlett 2017, 139, 13612-13615. [55] Higgs, P. G.; Lehman, N. Nat. Rev. Genet. 2015, 16, 7-17.

[56] Vaidya, N.; Manapat, M. L.; Chen, I. A.; Xulvi-Brunet, R.; Hayden, E. J.; Lehman, N. Nature 2012, 491, 72-77.

[57] Dadon, Z.; Wagner, N.; Alasibi, S.; Samiappan, M.; Mukherjee, R.; Ashke-nasy, G. Chem.-Eur. J. 2015, 21, 648-654.

[58] Nanda, J.; Rubinov, B.; Ivnitski, D.; Mukherjee, R.; Shtelman, E.; Motro, T.; Miller, Y.; Wagner, N.; Luria, R. C.; Ashkenasy, G. Nat. Commun. 2017, 8, 434.

[59] Kosikova, T.; Mackenzie, H.; Philp, D. Chem.-Eur. J. 2016, 22, 1831-1839. [60] Kosikova, T.; Philp, D. J. Am. Chem. Soc. 2017, 139, 12579-12590.

[61] Sadownik, J. W.; Philp, D. Org. Biomol. Chem. 2015, 13, 10392-10401. [62] Sadownik, J. W.; Kosikova, T.; Philp, D. J. Am. Chem. Soc. 2017, 139,

17565-17573.

[63] del Amo, V.; Philp, D. Chem.-Eur. J. 2010, 16, 13304-13318.

[64] Sadownik, J. W.; Mattia, E.; Nowak, P.; Otto, S. Nat. Chem. 2016, 8, 264-269. [65] Altay, Y.; Tezcan, M.; Otto, S. J. Am. Chem. Soc. 2017, 139, 13612-13615.

Parts of this chapter has been published in:

A. Pal, M. Malakoutikhah, G. Leonetti, M. Tezcan, M. Colomb-Delsuc, V.D. Nguyen, J. van der Gucht, S. Otto. “Controlling the Structure and Length of Self-Synthesizing Supramolecular Polymers through Nucleated Growth and Disassembly.”, Angew. Chem. Int. Ed. 2015, 54, 7852-7856.

Chapter 2

The Influence of Building Block Design on

the Outcome of Type and Size of

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22

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

2.1

Introduction

S

upramolecular polymers find applications in bioactive materialsscience.2 Apart from their chemical structure, controlling the size and dimen-1 and material

sions of the supramolecular polymers is important to produce well-defined materi-als.3 In conventional polymer synthesis, there are many examples where only co-valent linkages between blocks yield assembling materials with controlled lengths. In 2007, Winnik and co-workers reported one of the earliest examples of such sys-tems.4 They found out that block copolymers made from

polyferrocenyldimethylsi-lane (PFS) forms cylindirical micelles under thermodynamic control with low poly-dispersity from which rigid block co-micelles can grow also with controlled lengths. As the monomer:seed ratio varies, crystallization driven self-assembly (CDSA) also allowed to synthesize monodisperse cylinders with controllable lengths in micro me-ter scale.5 Additionally, this feature could also be used to obtain fiber-like block

co-micelles from poly(3-hexylthiophene) (P3HT) seeds that were generated by the CDSA process and polystyrene (PS) units.6 The group later extended the scope of

their crystallization driven block copolymers with controllable lengths including poly-carbonate derivatives, polyselenophenes and perylenediimide amphiphiles.7–9

How-ever, controlling the size and shape of supramolecular polymers in aqueous solutions is a challenging task. Meijer and co-workers showed that handedness of benzene-1,3,5-tricarboxamide (BTA) based helical architectures in water can be defined with certain Coulombic interactions.10 Moreover, as in conventional polymer synthesis,

living supramolecular polymerization has recently enabled access to self-synthesizing materials with very well-defined properties like uniformity and low polydispersity.11

In a more recent example, Takeuchi and co-workers reported that porphyrin-based supramolecular assemblies, with a polydispersity index of 1.1, form through a process resembling living polymerization featuring a nucleation-elongation mechanism.12

Our group previously developed a system13 in which living polymerization was

achieved through a nucleation-elongation mechanism with a peptide-based building block (Figure 2.1). As discussed in detail in Chapter 1 of this thesis, in an agitated solution, primary nuclei (short hexamer fibers) are formed and fragmented to produce more fiber ends (secondary nuclei) from which the highly polydisperse fibers grow. The key to enable control over fiber length is controllable primary and secondary nucleation. This is achieved by using pre-formed small seeds with uniform size so that fibers can grow with equal rate. The uniform seeds can be produced by either applying high shear stress or chemical degradation. More detailed discussion can be found in the following sub-chapters. We took steps to further elaborate the system by means of tuning the composition of the supramolecular block copolymers made out of two structurally closely related self-replicators. We investigated the morphology

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2.1. Introduction 23 of the system at different stages of self-assembly and the origins of the compositional preference of the system. The results show that small changes in structure design impact strongly on the nature of the self-assembling material.

Figure 2.1: Cartoon representation of self-synthesizing fibers growing through a nucleaction-elongation mechanism. The living nature of the fibers was demonstrated with sequential addition of ‘food’ consisting mostly of smaller macrocycles. Steps i, ii and iii show the cycles in which half of the solution containing the fibers was replaced with food mixture. Average fiber length distribution (bottom-left) proves that almost perfect control of dispersity has been made possible.

In the second part of the chapter, we describe studies of a set of DCLs made from building blocks with halogen modifications on the amino acid side chain to expand the scope of our supramolecular block copolymers. Furthermore, we aimed to provide a direct proof of supramolecular block copolymer formation by directly visualizing the polymers without the need of a stain or a fluorescent dye.

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24

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

2.2

Results and Discussion

2.2.1

Building blocks utilized in mixed block co-fiber

forma-tion

For the supramolecular block copolymer experiments, we selected two building blocks both of which can give self-replicating 6-ring macrocycles (Figure 2.2).14 Building

block 1 contains a phenylalanine unit in the peptide backbone and has previously been used to demonstrate the living supramolecular nature of our peptide replicators. Building block 2 differs only by one amino acid in the side chain; cyclohexylalanine instead of phenylalanine. By such selection, we aimed to minimize the differences in the self-assembly propensities of the two peptide building blocks. .

Figure 2.2: Cartoon representation of building blocks utilized in mixed block co-fiber sys-tems.

2.2.2

Experimental proof for the formation of A-B-A type

supramolecular block copolymers

Formation of mixed block co-fibers was first confirmed with an initial control exper-iment. We prepared a DCL from building block 2 and let the system evolve until the DCL contains mostly the replicator 26. We used 26 as seed and mixed it with

a pre-oxidized solution containing mostly 13/14with a seed:food ratio of 1:3. Since

the fibers of the two building blocks are indistinguishable by electron microscopy, we monitored the composition of the fibers by reducing them from their ends. Ad-dition of consecutive batches of reducing agent showed a step-wise decrease in the amount of 16. In contrast, the amount of 26remained almost unchanged until 25 %

DTT was added (Figure 2.3b). These data suggest the formation of an A-B-A type supramolecular block copolymer in our system.

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2.2. Results and Discussion 25

Figure 2.3: a) Cartoon representation of the preparation of A-B-A type supramolecular copolymer made from building block 1 (3.8 mM in borate buffer, pH 7.8) which was pre-oxidized at least 80% with respect to monomer with 80 mM sodium perborate and a solution containing 26 as seed (3.4 mM in 50 mM borate buffer, pH 7.8) with a seed:food volume

ratio of 3:1, b) Change in hexamer peak area in supramolecular block co-fibers upon DTT (1.9 mM) mediated partial reduction from the fiber ends. Sample was monitored by UPLC over a period of two days after adding the seed. Figure adapted from reference.13

We then performed a control experiment in which pre-formed hexamers 16and 26

were mixed in a ratio of 3:1. This time, even a very small amount of DTT addition resulted in reduction of both of the hexamers (Figure 2.4b).

Figure 2.4: a) Cartoon representation of a control experiment in which pre-formed cyclic hexamer fibers consist of 16 (3.8 mM in 50 mM borate buffer, pH 7.8) and 26 (3.4 mM in

50 mM borate buffer, pH 7.8) were mixed and b) DTT (1.9 mM) mediated partial reduction of the mixture of fibers showing the decrease in the amount of both macrocycles right after adding 5% batches of DTT. Sample was monitored by UPLC over a period of two days after mixing the two solutions. Figure adapted from reference.13

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26

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

2.2.3

Control of fiber length and composition of the

supramolec-ular block copolymers

In previous works from our group,15,16 it was shown that replication kinetics are

greatly influenced by the mode of agitation. As the number of catalytically active fiber ends increase with mechanical agitation, the rate of replication is also increased. However, one common feature in these studies is the polydispersity of the fibers. Irrespective of the mode of agitation (stirring with varying rpm, shaking, or standing), fiber lengths were found to be far from uniform with relatively high polydispersity indices.17 In order to control the length, to obtain monodisperse fibers, we used a

specially designed Couette cell which can apply high shear stress to a fiber solution as this is placed between two cylindrical surfaces one of which rotates at high speed (Figure 2.5).18

Figure 2.5: Cartoon representation (left) of the Couette cell with a cylindrical inner part (1) that applies a high shear stress by rotation and picture of the cell used in the study (right).

We performed the experiments in three phases: The first involved obtaining the monodisperse seeds of fibers formed from the first building block using the Couette cell. In the second phase, we added food solution of the second building block and let the system assemble for several days allowing newly formed macrocycles to assemble on the ends of the short seed. We followed the growth by monitoring the solution by UPLC (at 254 nm). Lastly, once the growth was completed, we confirmed the actual block copolymer composition by TCEP-mediated step-wise reduction followed by monitoring the species distribution by UPLC. The reason for changing the reducing agent from DTT to TCEP is that TCEP is less toxic and more stable at room temperature than DTT. The entire experiment is shown schematically in Figure 2.6.

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2.2. Results and Discussion 27

Figure 2.6: Cartoon representation for the experimental design for the synthesis of block co-fibers and confirming their composition by means of partial reduction with TCEP from fiber ends. Unless otherwise stated, seed and food solutions were prepared from 1.9 mM building block 1 or 2 in 50 mM borate buffer (pH 8.2). Block co-fiber solutions were left unagitated and monitored by UPLC for at least one week before reducing small aliquots with a 1.9 mM aqueous solution of TCEP.

In the course of synthesizing different copolymers, we followed a systematic ap-proach and set up the experiments with two different replicators (16 or 26) as seed

with seed:food ratios of 1:2 and 1:4 from libraries that were 1.9 mM in building block. Before reducing the fiber solutions, we analysed the fiber lengths by electron microscopy (Figure 2.7). As Figure 2.7b shows, in the solution with seed:food ratio of 1:2, resulting fiber lengths are approximately three times of the length of 26seeds

with a PDI=1.1. When compared with the seed dispersity (PDI=1.05) we can clearly say that growth is still under control in such composition. We, then took a step fur-ther and increased the amount of food and prepared a solution with a seed:food ratio of 1:4. This time, the resulting fibers were considerably more polydisperse with PDI=1.20. One potential drawback of increasing the amount of food could be the self-assembly of 16 (instead of block co-fibers). However, when compared with

previous studies, the time required for the formation of the block co-fibers is much less than the time required for the spontaneous nucleation of assemblies made from the ‘food’ without agitation. Based on this, we could eliminate the possibility of spontaneous assembly of cyclic hexamers of building block 1. These results show an important aspect of supramolecular block copolymers in which the relative amount of food (1mer/3mer/4mer solution) plays a decisive role in our ability to control the dispersity of the fibers.

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28

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

Figure 2.7: Histograms for fiber length distribution and corresponding polydispersity in-dices of a) 26 fibers (1.9 mM building block concentration in 50 mM borate buffer, pH 8.2)

after shearing at 67405 s-1for 30 minutes in a Couette cell, b) fibers from a pre-oxidized (80%

with respect to monomer concentration with 40 mM sodium perborate) solution containing a mixture of 11, 13 and 14 as ‘food’ and 26 as ‘seed’ with seed:food volume ratio of 1:2

and c) fibers from a solution containing the same ‘food’ and ‘seed’ as in (b) with seed:food volume ratio of 1:4. Samples for fiber length analyses were blotted on TEM grids at least 10 days after cross-seeding.

We followed the species distribution by UPLC. Once essentially all food had been converted to hexamers, we reduced small aliquots from the solution with TCEP and followed the decrease in percent area of the hexamers and increase of the subsequent monomer formation. The results are shown in Figure 2.8.

Figure 2.9a and 2.9b shows that, in the first system (1:2 seed:food ratio), at least until 15% reduction, the amount of seed (26) remains almost constant and the

percentage of 21 is almost negligible compared to 11. This finding indicates the

formation of A-B-A type block fibers. Even with increased amount of food, the change in percent seed (26) is almost constant until at least 30% reduction (Figure

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2.2. Results and Discussion 29

Figure 2.8: UPLC chromatograms (monitored at 254 nm) 12 days after preparation show-ing species the distribution after 5µL aliquots from a DCL made from building blocks 1 and 2 as described above (with seed:food ratio of 1:4) were chemically reduced with different percentages of a 1.9 mM aqueous solution of TCEP: a) 0 %, b) 30 %, c) 50 % and d) 100 %.

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30

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

Figure 2.9: UPLC peak area over amount of reducing agent for the two cyclic hexamers (16

and 26) in the fibers and monomers (11and 21) in the solution as a result of reducing with

1.9 mM aqueaous TCEP solution: a) change in hexamer peak area b) change in monomer peak area when the seed:food volume ratio is 1:2; c) change in hexamer peak area and d) change in monomer peak area when the seed:food volume ratio is 1:4 (1.9 mM each in 50 mM borate buffer, pH 8.2).

Up to now, we focused on a system in which hexamers of 1 were grown on fibers constituted of hexamers of 2. As a next step, we inverted the system so that core of the anticipated supramolecular polymers contained the less hydrophobic phenylalanine instead of cyclohexylalanine. By doing so, we aimed to investigate how the nature of building blocks affect the block copolymer formation.

Different to the first system, this time we observed slightly shorter and more poly-disperse 16seeds (Figure 2.10a). In addition, regardless of the fiber composition, the

length distribution showed better control than the first system. However, especially with a seed:food ratio of 1:4, many of longer fibers could not be counted due to bend-ing of the fibers on the TEM grid. Therefore, the histograms and the PDI values are representative of only the stiffer fibers (Figure 2.10b and Figure 2.10c).

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2.2. Results and Discussion 31

Figure 2.10: Histograms as a result of the fiber length analyses and the corresponding polydispersity indices of a) seed 16 fibers in a DCL made from 1.9 mM building block 1 (in

50 mM borate buffer, pH 8.2) after shearing at 67405 s-1 for 30 minutes in a Couette cell, b) fibers in a 1.9 mM DCL made from 1.9 mM building block 2 (in 50 mM borate buffer, pH 8.2) and cross-seeded with short 16 fibers with the seed:food volume ratio of 1:2 and c)

fibers with the seed:food volume ratio of 1:4.

We again followed the change in UPLC peak area for both 16 and 26 and the

subsequent monomer formation. Partial reduction results showed that, despite the improved PDI values of fibers, both of the hexamers were reduced (Figure 2.11). This unexpected behaviour suggested unidirectional growth rather than a A-B-A type triblock formation.

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32

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers

Figure 2.11: UPLC peak area over amount of reducing agent for the hexamers (16and 26)

in the fibers and monomers (11and 21) in the solution as a result of reducing: a) change in

hexamer peak area b) change in monomer peak area when the seed:food volume ratio is 1:2; c) change in hexamer peak area and d) change in monomer peak area when the seed:food volume ratio is 1:4 (1.9 mM each in 50 mM borate buffer, pH 8.2).

We lastly designed a control experiment which could shed light on the assembly mechanism. We added small portions of food mixture stepwise. In each step, we changed the composition and increased the fraction of 23/24 to form a gradient

between the blocks. By doing so, we were still able to introduce small amount of 13/14 to 16 solution and were able to test if there is a recognition mechanism

to induce triblock copolymer formation. Although the resulting fibers have a low PDI (1.05), concurrent reduction of the two hexamers was observed indicative of unidirectional growth of diblock co-fibers (Figure 2.12).

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2.2. Results and Discussion 33

Figure 2.12: a) Cartoon representation for the control experiment where 1.9 mM food solution containing different volume fractions is added stepwise to a solution of shortened 16

seeds over days. Composition of the food is shown as volume percentage as the concentration is the same for both food solutions (1.9 mM in 50 mM borate buffer pH 8.2). Solution was kept two days without agitation between each step. b) Histogram showing the fiber length distribution after seeded-growth. Change in UPLC peak area of c) the hexamers (16 and

26) and d) the monomers (11 and 21) upon step-wise reduction with TCEP.

In conclusion, we showed that good control over fiber polydispersity could be achieved in seeded growth of fibers made from different building blocks. We observed an unexpected trend upon partially reducing the fibers from their ends: A-B-A type triblock co-fibers in which hexamers of 1 were grown on fibers constituted of hexamers of 2 and possible unidirectional growth when hexamers of 1 were used as seed instead of 2. In order to get more insight on self-assembly process and to shed light on any potential competing processes, we focused on the morphology of the two systems in the following sub-chapters.

2.2.4

Morphology and recombination of the fibers at different

stages of supramolecular polymerization

At this stage, we focused on the morphology of the assembling fibers both before and after shortening them in the Couette cell. Since we observed controlled growth in either case, we reasoned that the morphology of the fibers might play a decisive role

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34

2. The Influence of Building Block Design on the Outcome of Type and Size of Supramolecular Block Copolymers in determining the resulting composition. For imaging, we first used atomic force microscopy (AFM).

While the air oxidized DCLs made from building block 1 gave rise to cyclic 6-mer fibers assembling as pairs with a twist with a period of approximately 40 nm, cyclic hexamer fibers from building block 2 showed long single fibers without any twisting (Figure 2.13).

Figure 2.13: AFM images for the air-oxidized DCLs made from 1.9 mM building block 1 and 2 (in 50 mM borate buffer, pH 8.2) under mechanical agitation for; a) pairs of fibers of 16 and b) single fibers of 26.

After shortening the fibers using a Couette cell, the twisting in the 16 fibers

could no longer be observed. Instead, there were more single fibers and almost no association with surrounding fibers was observed (Figure 2.14a). On the contrary, higher level of lateral association in shorthened 26 fibers was observed with varying

number of single fibers in each assembling unit (Figure 2.14b). AFM images also revealed that strongly sheared fibers were much thicker (up to 12.6 nm) than the fibers before applying high shear stress.

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2.2. Results and Discussion 35

Figure 2.14: AFM images after shearing the 1.9 mM DCLs made from building blocks 1 and 2 (in 50 mM borate buffer, pH 8.2) at 67405 s-1 for 30 minutes in a Couette cell: a)

16 fibers and b) 26 fibers.

Subsequently the short 26seeds were mixed with 23/24containing ‘food’. In

con-trast to fibers in air-oxidized DCL made from building block 2, seeded growth showed a considerable difference in thickness of different segments of the same fiber (Figure 2.15). This result suggests that 26 containing fibers are shortened and irreversibly

transformed to a different morphology when high shear stress is applied. Yet they retain their ability to act as seeds and it appears that fibers can grow off these seeds from two sides.

Figure 2.15: AFM images for the 1.9 mM DCL made from building block 2 (in 50 mM borate buffer, pH 8.2) and seeded with 0.2 mol eq. short 26 fibers which were sheared at

67405 s-1for 30 minutes in a Couette cell.

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