An Examination of the Role of Autocatalytic Cycles in the Chemistry of Proposed Primordial Reactions

An Amplificative Detection Approach for Autocatalytic Sensing of Ethylene

Amplified sensing offers the potential for high sensitivity; however, the vast majority of molecular strategies involve stoichiometric detection and signal transduction, including numerous recent examples of systems inspired by transition-metal-catalyzed reactions. Activation of latent precatalysts by a target analyte represents an attractive strategy for detecting low-concentration species. Analyte amplification represents another attractive approach, akin to PCR-based assays. Here we report an autocatalytic detection system based on the ethylene activation of Ru-I2 olefin metathesis precatalysts. Signal transduction is amplified by both catalytic ring closing metathesis of profluorescent substrates and ethylene propagation to activate additional units of catalyst. High sensitivity is observed as a result of this dual-mode amplified detection of ethylene. Detection of endogenous ethylene from fruit and oxidation-decomposition of polyunsaturated fatty acids via lipid peroxides is demonstrated.

Autoinhibition in (Bio)Chemistry: Identification and Mechanistic Classification

Autoinhibition is a frequently invoked self-regulatory mechanism involved in various cellular processes to interpret clearly how these cells may control their complex functioning. This type of temporal behavior generally results in self-retardation or even in complete shuts down of the undesired reactions to occur meaning that the rate of a certain biochemical reaction is partially or completely retarded. Precise characterization and classification of a complex system where deceleration of the reaction rate is found, however, requires special circumspection to avoid false interpretation. Hereby, it was clearly demonstrated that the retardation effect of an inhibitor is unexpectedly often misidentified as autoinhibition, especially in complex biochemical enzymatic systems. It prompted us to clarify unambiguously the difference between inhibition and autoinhibition. The latter kinetic phenomenon is a special type of inhibition where the inhibitor forms by the result of a chemical or biochemical event exerting the self-decelerating effect on the rate of its own formation resulting thus in significantly different temporal patterns compared to the ones observed in the case of simple inhibitions. Kinetic activity of autoinhibitor towards the species involved in the given system allowed us to classify direct, indirect and dual autoinhibitions to be supported by real chemical examples.

Cross-chiral exponential amplification of an RNA enzyme

An RNA ligase ribozyme that catalyzes the joining of RNA molecules of the opposite chiral handedness was optimized for the ability to synthesize its own enantiomer from two component fragments. The mirror-image D- and L-ligases operate in concert to provide a system for cross-chiral replication, whereby they catalyze each other's synthesis and undergo mutual amplification at constant temperature, with apparent exponential growth and a doubling time of about 1 h. Neither the D- nor the L-RNA components alone can achieve autocatalytic self-replication. Cross-chiral exponential amplification can be continued indefinitely through a serial-transfer process that provides an ongoing supply of the component D- and L-substrates. Unlike the familiar paradigm of semiconservative nucleic acid replication that relies on Watson-Crick pairing between complementary strands, cross-chiral replication relies on tertiary interactions between structured nucleic acids "across the mirror." There are few examples, outside of biology, of autocatalytic self-replication systems that undergo exponential amplification and there are no prior examples, in either biological or chemical systems, of cross-chiral replication enabling exponential amplification.

Rethinking life and predicting its origin

The definition, origin and recreation of life remain elusive. As others have suggested, only once we put life into reductionist physical terms will we be able to solve those questions. To that end, this work proposes the phenomenon of life to be the product of two dissipative mechanisms. From them, one characterises extant biological life and deduces a testable scenario for its origin. The proposed theory of life allows its replication, reinterprets ecological evolution and creates new constraints on the search for life.

Enhanced condensation kinetics in aqueous microdroplets driven by coupled surface reactions and gas-phase partitioning

Although aqueous microdroplets have been shown to exhibit enhanced chemical reactivity compared to bulk solutions, mechanisms for these enhancements are not completely understood. Here we combine experimental measurements and kinetic modeling to show the strong coupling of interfacial reactions and gas/droplet partitioning in the condensation reaction of pyruvic acid (PA) to yield zymonic acid (ZA) in acidic aqueous microdroplets. Experimental analysis of single microdroplets reveals the substantial influence of evaporation of PA and partitioning of water on the size-, relative humidity (RH)- and temperature-dependent sigmoidal reaction kinetics for the condensation reaction. A newly developed diffusion-reaction-partitioning model is used to simulate the complex kinetics observed in the microdroplets. The model can quantitatively predict the size and compositional changes as the reaction proceeds under different environmental conditions, and provides insights into how microdroplet reactivity is controlled by coupled interfacial reactions and the gas-phase partitioning of PA and water. Importantly, the kinetic model best fits the data when an autocatalytic step is included in the mechanism, i.e. a reaction step where the product, ZA, catalyzes the interfacial condensation reaction. Overall, the dynamic nature of aqueous microdroplet chemistry and the coupling of interfacial chemistry with gas-phase partitioning are demonstrated. Furthermore, autocatalysis of small organic molecules at the air-water interface for aqueous microdroplets, shown here for the first time, has implications for several fields including prebiotic chemistry, atmospheric chemistry and chemical synthesis.

Triple Adaptation of Constitutional Dynamic Networks of Imines in Response to Micellar Agents: Internal Uptake-Interfacial Localization-Shape Transition

Understanding the behavior of complex chemical reaction networks and how environmental conditions can modulate their organization as well as the associated outcomes may take advantage of the design of related artificial systems. Microenvironments with defined boundaries are of particular interest for their unique properties and prebiotic significance. Dynamic covalent libraries (DCvLs) and their underlying constitutional dynamic networks (CDNs) have been shown to be appropriate for studying adaptation to several processes, including compartmentalization. However, microcompartments (e.g., micelles) provide specific environments for the selective protection from interfering reactions such as hydrolysis and an enhanced chemical promiscuity due to the interface, governing different processes of network modulation. Different interactions between the micelles and the library constituents lead to dynamic sensing, resulting in different expressions of the network through pattern generation. The constituents integrated into the micelles are protected from hydrolysis and hence preferentially expressed in the network composition at the cost of constitutionally linked members. In the present work, micellar integration was observed for two processes: internal uptake based on hydrophobic forces and interfacial localization relying on attractive electrostatic interactions. The latter drives a complex triple adaptation of the network with feedback on the shape of the self-assembled entity. Our results demonstrate how microcompartments can enforce the expression of constituents of CDNs by reducing the hydrolysis of uptaken members, unravelling processes that govern the response of reactions networks. Such studies open the way toward using DCvLs and CDNs to understand the emergence of complexity within reaction networks by their interactions with microenvironments.

On the Emergence of Autonomous Chemical Systems through Dissipation Kinetics

This work addresses the kinetic requirements for compensating the entropic cost of self-organization and natural selection, thereby revealing a fundamental principle in biology. Metabolic and evolutionary features of life cannot therefore be separated from an origin of life perspective. Growth, self-organization, evolution and dissipation processes need to be metabolically coupled and fueled by low-entropy energy harvested from the environment. The evolutionary process requires a reproduction cycle involving out-of-equilibrium intermediates and kinetic barriers that prevent the reproductive cycle from proceeding in reverse. Model analysis leads to the unexpectedly simple relationship that the system should be fed energy with a potential exceeding a value related to the ratio of the generation time to the transition state lifetime, thereby enabling a process mimicking natural selection to take place. Reproducing life's main features, in particular its Darwinian behavior, therefore requires satisfying constraints that relate to time and energy. Irreversible reaction cycles made only of unstable entities reproduce some of these essential features, thereby offering a physical/chemical basis for the possible emergence of autonomy. Such Emerging Autonomous Systems (EASs) are found to be capable of maintaining and reproducing their kind through the transmission of a stable kinetic state, thereby offering a physical/chemical basis for what could be deemed an epigenetic process.

The protometabolic nature of prebiotic chemistry

The field of prebiotic chemistry has been dedicated over decades to finding abiotic routes towards the molecular components of life. There is nowadays a handful of prebiotically plausible scenarios that enable the laboratory synthesis of most amino acids, fatty acids, simple sugars, nucleotides and core metabolites of extant living organisms. The major bottleneck then seems to be the self-organization of those building blocks into systems that can self-sustain. The purpose of this tutorial review is having a close look, guided by experimental research, into the main synthetic pathways of prebiotic chemistry, suggesting how they could be wired through common intermediates and catalytic cycles, as well as how recursively changing conditions could help them engage in self-organized and dissipative networks/assemblies (i.e., systems that consume chemical or physical energy from their environment to maintain their internal organization in a dynamic steady state out of equilibrium). In the article we also pay attention to the implications of this view for the emergence of homochirality. The revealed connectivity between those prebiotic routes should constitute the basis for a robust research program towards the bottom-up implementation of protometabolic systems, taken as a central part of the origins-of-life problem. In addition, this approach should foster further exploration of control mechanisms to tame the combinatorial explosion that typically occurs in mixtures of various reactive precursors, thus regulating the functional integration of their respective chemistries into self-sustaining protocellular assemblies.

From autocatalysis to survival of the fittest in self-reproducing lipid systems

Studying autocatalysis - in which molecules catalyse their own formation - might help to explain the emergence of chemical systems that exhibit traits normally associated with biology. When coupled to other processes, autocatalysis can lead to complex systems-level behaviour in apparently simple mixtures. Lipids are an important class of chemicals that appear simple in isolation, but collectively show complex supramolecular and mesoscale dynamics. Here we discuss autocatalytic lipids as a source of extraordinary behaviour such as primitive chemical evolution, chemotaxis, temporally controllable materials and even as supramolecular catalysts for continuous synthesis. We survey the literature since the first examples of lipid autocatalysis and highlight state-of-the-art synthetic systems that emulate life, displaying behaviour such as metabolism and homeostasis, with special consideration for generating structural complexity and out-of-equilibrium models of life. Autocatalytic lipid systems have enormous potential for building complexity from simple components, and connections between physical effects and molecular reactivity are only just beginning to be discovered.

Oscillatory dynamics in a reaction network based on imine hydrolysis

We have built an autocatalytic reaction network, based on the hydrolysis of certain imines, which exhibits bistability in an open system. The positive feedback originates from the interplay of fast acid-base equilibria, leading to hydroxide ion production, and pH-dependent hydrolysis rates. The addition of a first-order removal of the autocatalyst can result in sustained pH oscillations close to physiological conditions. The unit-amplitude pH oscillations are accompanied by the stoichiometric conversion of imine into amine back and forth. A systematic parameter search is carried out to characterize the rich observable dynamics and identify the evolving bifurcations.

Conditions for the origin of homochirality in primordial catalytic reaction networks

We study the generation of homochirality in a general chemical model (based on the homogeneous, fully connected Smoluchowski aggregation-fragmentation model) that obeys thermodynamics and can be easily mapped onto known origin of life models (e.g. autocatalytic sets, hypercycles, etc.), with essential aspects of origin of life modeling taken into consideration. Using a combination of theoretical modeling and numerical simulations, we look for minimal conditions for which our general chemical model exhibits spontaneous mirror symmetry breaking. We show that our model spontaneously breaks mirror symmetry in various catalytic configurations that only involve a small number of catalyzed reactions and nothing else. Of particular importance is that mirror symmetry breaking occurs in our model without the need for single-step autocatalytis or mutual inhibition, which may be of relevance for prebiotic chemistry.

Spontaneous Emergence of Transient Chirality in Closed, Reversible Frank-like Deterministic Models

To explore abiotic theories related to the origin of biomolecular homochirality, we analyze two entirely reversible kinetic models composed of an enantioselective autocatalysis with limited stereoselectivity that is coupled to an enantiomeric mutual inhibition (Frank-like models). The two models differ in their autocatalytic steps in respect to the formation of monomer species in one model and of dimer species in the other. While fully reversible and running in a closed system, spontaneous mirror symmetry breaking (SMSB) gives rise to transient chiral excursions, even when starting from a strictly achiral situation. Before the SMSB, the two models differ in the main dissipative processes. At the SMSB, the entropy production rate reaches its maximum in both models. Here it is the enantioselective autocatalysis with retention of the winner enantiomer that dominates. During the terminal phase, the enantioselective autocatalysis with inversion prevails, while the entropy production rate vanishes, thus fulfilling the conditions of microscopic reversibility. SMSB does not occur if the autocatalytic rate constant is too strong or too weak. However, when the autocatalysis is relatively weak, the temporary chiral excursions last for long periods of time and could be the starting point of a cascade of asymmetric reactions. The realism of such Frank-like models is discussed from the viewpoint of their relevance to prebiotic chemistry.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

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SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11244-021-01543-9.

Exponential Amplification Using Photoredox Autocatalysis

Exponential molecular amplification such as the polymerase chain reaction is a powerful tool that allows ultrasensitive biodetection. Here, we report a new exponential amplification strategy based on photoredox autocatalysis, where eosin Y, a photocatalyst, amplifies itself by activating a nonfluorescent eosin Y derivative (EYH^3-) under green light. The deactivated photocatalyst is stable and rapidly activated under low-intensity light, making the eosin Y amplification suitable for resource-limited settings. Through steady-state kinetic studies and reaction modeling, we found that EYH^3- is either oxidized to eosin Y via one-electron oxidation by triplet eosin Y and subsequent 1e^-/H⁺ transfer, or activated by singlet oxygen with the risk of degradation. By reducing the rate of the EYH^3- degradation, we successfully improved EYH^3--to-eosin Y recovery, achieving efficient autocatalytic eosin Y amplification. Additionally, to demonstrate its flexibility in output signals, we coupled the eosin Y amplification with photoinduced chromogenic polymerization, enabling sensitive visual detection of analytes. Finally, we applied the exponential amplification methods in developing bioassays for detection of biomarkers including SARS-CoV-2 nucleocapsid protein, an antigen used in the diagnosis of COVID-19.

Correct classification and identification of autocatalysis

It is generally accepted that autocatalysis is a kinetic phenomenon, where a product of a reacting system functions as a catalyst. Consequently, the reaction proceeds faster upon adding the corresponding product to the unreacted mixture of reactants providing an unequivocal possibility of how a system may be identified either experimentally or theoretically as an autocatalysis. Once this is approved, it often results in sigmoidal concentration-time profiles, though it is neither a necessary nor sufficient prerequisite because appropriate mechanistic and parametric conditions must be met to give rise to the appearance of this kinetic feature. Several mass action type kinetic models producing sigmoidal concentration-time profiles are systematically analyzed to clarify their correct characterization and classification. This procedure has led us to refine the definitions of autocatalysis and autocatalyst. A kinetic phenomenon where a product of the overall chemical event serves as a catalyst for at least one of its subsystems or for the whole system itself is called autocatalysis. This definition makes it clear that in the case of autocatalysis, the concentration of autocatalyst necessarily increases during the course of any real overall chemical or biochemical reaction. The way it is achieved thereby provides a suitable tool to classify autocatalytic processes by their elucidated and fine mechanistic details.

A robust and tunable halogen bond organocatalyzed 2-deoxyglycosylation involving quantum tunneling

The development of noncovalent halogen bonding (XB) catalysis is rapidly gaining traction, as isolated reports documented better performance than the well-established hydrogen bonding thiourea catalysis. However, convincing cases allowing XB activation to be competitive in challenging bond formations are lacking. Herein, we report a robust XB catalyzed 2-deoxyglycosylation, featuring a biomimetic reaction network indicative of dynamic XB activation. Benchmarking studies uncovered an improved substrate tolerance compared to thiourea-catalyzed protocols. Kinetic investigations reveal an autoinductive sigmoidal kinetic profile, supporting an in situ amplification of a XB dependent active catalytic species. Kinetic isotopic effect measurements further support quantum tunneling in the rate determining step. Furthermore, we demonstrate XB catalysis tunability via a halogen swapping strategy, facilitating 2-deoxyribosylations of D-ribals. This protocol showcases the clear emergence of XB catalysis as a versatile activation mode in noncovalent organocatalysis, and as an important addition to the catalytic toolbox of chemical glycosylations.

Halogen bonding (HB) catalysis is rapidly gaining momentum, however, cases of XB activation for challenging bonds formation are rare. Here, the authors show a robust XB catalyzed 2-deoxyglycosylation with broad scope and featuring a quantum tunneling phenomenon in the proton transfer rate determining step.

Universal motifs and the diversity of autocatalytic systems

Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks. This allows for a classification of minimal autocatalytic motifs called cores. While all known autocatalytic systems indeed contain minimal motifs, the classification also reveals hitherto unidentified motifs. We further examine conditions for kinetic viability of such networks, which depends on the autocatalytic motifs they contain and is notably increased by internal catalytic cycles. Finally, we show how this framework extends the range of conceivable autocatalytic systems, by applying our stoichiometric and kinetic analysis to autocatalysis emerging from coupled compartments. The unified approach to autocatalysis presented in this work lays a foundation toward the building of a systems-level theory of chemical evolution.

Law of Mass Action Type Chemical Mechanisms for Modeling Autocatalysis and Hypercycles: Their Role in the Evolutionary Race

One of our most appealing challenge is to unravel the role of a presumably autocatalytic system in controlling the origin and spreading of Life on our entire planet. Here we show that in the simplest autocatalytic loop involving reactions capable of self-replication and obeying law of mass action kinetics, concentration growth of the autocatalyst may be characterized by parametrization of direct and autocatalytic pathways rather than by kinetic orders of the autocatalyst. Extending this model by feasible elementary steps allows us to outline super-exponential growth where kinetic order of the autocatalyst is higher than unity. Furthermore, it is shown in case of the simplest hypercycle that such a situation might appear where the otherwise more sluggish autocatalytic route receives a decisive support from the crosscatalytic pathway to become an apparently stronger autocatalytic loop even if the other route contains a more efficient autocatalysis. If the hypercycle is performed under flow conditions selection of autocatalyst depends on kinetic and flow parameters influenced by external factors mimicking that the most adaptive loop of hypercycle eventually finds its wining way in the evolutionary race.

Nonenzymatic Metabolic Reactions and Life's Origins

Prebiotic chemistry aims to explain how the biochemistry of life as we know it came to be. Most efforts in this area have focused on provisioning compounds of importance to life by multistep synthetic routes that do not resemble biochemistry. However, gaining insight into why core metabolism uses the molecules, reactions, pathways, and overall organization that it does requires us to consider molecules not only as synthetic end goals. Equally important are the dynamic processes that build them up and break them down. This perspective has led many researchers to the hypothesis that the first stage of the origin of life began with the onset of a primitive nonenzymatic version of metabolism, initially catalyzed by naturally occurring minerals and metal ions. This view of life's origins has come to be known as "metabolism first". Continuity with modern metabolism would require a primitive version of metabolism to build and break down ketoacids, sugars, amino acids, and ribonucleotides in much the same way as the pathways that do it today. This review discusses metabolic pathways of relevance to the origin of life in a manner accessible to chemists, and summarizes experiments suggesting several pathways might have their roots in prebiotic chemistry. Finally, key remaining milestones for the protometabolic hypothesis are highlighted.

Supramolecular interactions between catalytic species allow rational control over reaction kinetics

The adaptivity of biological reaction networks largely arises through non-covalent regulation of catalysts' activity. Such type of catalyst control is still nascent in synthetic chemical networks and thereby hampers their ability to display life-like behavior. Here, we report a bio-inspired system in which non-covalent interactions between two complementary phase-transfer catalysts are used to regulate reaction kinetics. While one catalyst gives bimolecular kinetics, the second displays autoinductive feedback, resulting in sigmoidal kinetics. When both catalysts are combined, the interactions between them allow rational control over the shape of the kinetic curves. Computational models are used to gain insight into the structure, interplay, and activity of each catalytic species, and the scope of the system is examined by optimizing the linearity of the kinetic curves. Combined, our findings highlight the effectiveness of regulating reaction kinetics using non-covalent catalyst interactions, but also emphasize the risk for unforeseen catalytic contributions in complex systems and the necessity to combine detailed experiments with kinetic modelling.

Mathematical Analysis of a Prototypical Autocatalytic Reaction Network

Network autocatalysis, which is autocatalysis whereby a catalyst is not directly produced in a catalytic cycle, is likely to be more common in chemistry than direct autocatalysis is. Nevertheless, the kinetics of autocatalytic networks often does not exactly follow simple quadratic or cubic rate laws and largely depends on the structure of the network. In this article, we analyzed one of the simplest and most chemically plausible autocatalytic networks where a catalytic cycle is coupled to an ancillary reaction that produces the catalyst. We analytically analyzed deviations in the kinetics of this network from its exponential growth and numerically studied the competition between two networks for common substrates. Our results showed that when quasi-steady-state approximation is applicable for at least one of the components, the deviation from the exponential growth is small. Numerical simulations showed that competition between networks results in the mutual exclusion of autocatalysts; however, the presence of a substantial noncatalytic conversion of substrates will create broad regions where autocatalysts can coexist. Thus, we should avoid the accumulation of intermediates and the noncatalytic conversion of the substrate when designing experimental systems that need autocatalysis as a source of positive feedback or as a source of evolutionary pressure.

Chemical Systems Involving Two Competitive Self-Catalytic Reactions

Self-catalytic reactions are chemical phenomena, in which a product catalyzes the reactions of substrates further to yield products. A significant amplification of product concentration occurs during the reactions in a dilute solution, which exhibit notable properties such as sigmoidal kinetics, seeding effects, and thermal hysteresis. Chemical systems involving two competitive self-catalytic reactions can be considered, in which the competitive formation of two products occurs, which is affected by environmental changes, subtle perturbations, and fluctuations, and notable chemical phenomena appear such as formation of different structures in response to slow/fast temperature changes, chiral symmetry breaking, shortcut in reaction time, homogeneous-heterogeneous transitions, and mechanical responses. Studies on such chemical systems provide understanding on biological systems and can also be extended to the development of novel functional materials.

Chemical Transformation Motifs-Modelling Pathways as Integer Hyperflows

We present an elaborate framework for formally modelling pathways in chemical reaction networks on a mechanistic level. Networks are modelled mathematically as directed multi-hypergraphs, with vertices corresponding to molecules and hyperedges to reactions. Pathways are modelled as integer hyperflows and we expand the network model by detailed routing constraints. In contrast to the more traditional approaches like Flux Balance Analysis or Elementary Mode analysis we insist on integer-valued flows. While this choice makes it necessary to solve possibly hard integer linear programs, it has the advantage that more detailed mechanistic questions can be formulated. It is thus possible to query networks for general transformation motifs, and to automatically enumerate optimal and near-optimal pathways. Similarities and differences between our work and traditional approaches in metabolic network analysis are discussed in detail. To demonstrate the applicability of the mathematical framework to real-life problems we first explore the design space of possible non-oxidative glycolysis pathways and show that recent manually designed pathways can be further optimized. We then use a model of sugar chemistry to investigate pathways in the autocatalytic formose process. A graph transformation-based approach is used to automatically generate the reaction networks of interest.

Controlling the Kinetics of Self-Reproducing Micelles by Catalyst Compartmentalization in a Biphasic System

Compartmentalization of reactions is ubiquitous in biochemistry. Self-reproducing lipids are widely studied as chemical models of compartmentalized biological systems. Here, we explore the effect of catalyst location on copper-catalyzed azide-alkyne cycloadditions which drive the self-reproduction of micelles from phase-separated components. Tuning the hydrophilicity of the copper-ligand complex, so that hydro-phobic or -philic catalysts are used in combination with hydro-philic and -phobic coupling partners, provides a wide range of reactivity patterns. Analysis of the kinetic data shows that reactions with a hydrophobic catalyst are faster than with a hydrophilic catalyst. Diffusion-ordered spectroscopy experiments suggest compartmentalization of the hydrophobic catalyst inside micelles while the hydrophilic catalyst remains in the bulk aqueous phase. The autocatalytic effects observed can be tuned by varying reactant structure and coupling a hydrophilic alkyne and hydrophobic azide results in a more pronounced autocatalytic effect. We propose and test a model that rationalizes the observations in terms of the phase behavior of the reaction components and catalysts.

Self-reproducing micelles coupled to a secondary catalyst

We report a physical autocatalytic system where micelles self-reproduce via a copper-catalyzed azide-alkyne cycloaddition in a biphasic reaction mixture. The coupling of a secondary catalyst to an autocatalytic cycle opens up new opportunities to control and probe autocatalytic processes.

Autoinductive conversion of α,α-diiodonitroalkanes to amides and esters catalysed by iodine byproducts under O2

Studies to convert nitroalkanes into amides and esters using I2 and O2 revealed in situ-generated iodine species facilitate the homolytic C-I bond cleavage of α,α-diiodonitroalkanes, arguably in an autoinductive or autocatalytic manner. Consequently, we devised a rapid and economical I2/O2-based method to synthesise sterically hindered esters directly from primary nitroalkanes.

A transient self-assembling self-replicator

Developing physical models of complex dynamic systems showing emergent behaviour is key to informing on persistence and replication in biology, how living matter emerges from chemistry, and how to design systems with new properties. Herein we report a fully synthetic small molecule system in which a surfactant replicator is formed from two phase-separated reactants using an alkene metathesis catalyst. The replicator self-assembles into aggregates, which catalyse their own formation, and is thermodynamically unstable. Rather than replicating until the reactants are fully consumed, the metastable replicator is depleted in a second metathesis reaction, and closed system equilibrium is eventually reached. Mechanistic experiments suggest phase separation is responsible for both replicator formation and destruction.

Exploiting recognition-mediated assembly and reactivity in [2]rotaxane formation

A small molecular reaction network exploits recognition-mediated reactive processes in order to drive the assembly and formation of both a self-replicating linear template (thread) and a [2]rotaxane, in which the linear template is encircled by a diamide macrocycle. Complementary recognition sites, placed at strategic positions on the reactive building blocks, drive these assembly and replication processes. Template-instructed experiments show that the thread is capable of efficient self-replication and that no cross-catalytic relationships exist between the thread and the [2]rotaxane. The rate of [2]rotaxane formation is insensitive to the addition of a preformed template, however, [2]rotaxane formation does show enhanced diastereoselectivity, most likely originating from its recognition-mediated formation through a ternary reactive complex.

Signal transduction and amplification through enzyme-triggered ligand release and accelerated catalysis

An enzyme-triggered catalytic signal amplification cascade is described through the design of a novel enzyme substrate that selectively activates an organometallic transfer hydrogenation catalyst once triggered.

Signal transduction and signal amplification are both important mechanisms used within biological signalling pathways. Inspired by this process, we have developed a signal amplification methodology that utilises the selectivity and high activity of enzymes in combination with the robustness and generality of an organometallic catalyst, achieving a hybrid biological and synthetic catalyst cascade. A proligand enzyme substrate was designed to selectively self-immolate in the presence of the enzyme to release a ligand that can bind to a metal pre-catalyst and accelerate the rate of a transfer hydrogenation reaction. Enzyme-triggered catalytic signal amplification was then applied to a range of catalyst substrates demonstrating that signal amplification and signal transduction can both be achieved through this methodology.

The divergence and natural selection of autocatalytic primordial metabolic systems

The diversity of the central metabolism of modern organisms is caused by the existence of a few metabolic modules, combination of which produces multiple metabolic pathways. This paper analyzes biomimetically reconstructed coupled autocatalytic cycles as the basis of ancestral metabolic systems. The mechanism for natural selection and evolution in autocatalytic chemical systems may be affected by natural homeostatic parameters such as ambient chemical potentials, temperature, and pressure. Competition between separate parts of an autocatalytic network with positive-plus-negative feedback resulted in the formation of primordial autotrophic, mixotrophic, and heterotrophic metabolic systems. This work examined the last common ancestor of a set of coupled metabolic cycles in a population of protocells. Physical-chemical properties of these cycles determined the main principles of natural selection for the ancestral Bacteria and Archaea taxa.

Amplification of enantiomeric excess, mirror-image symmetry breaking and kinetic proofreading in Soai reaction models with different oligomeric orders

A comprehensive kinetic analysis of three prototypical autocatalytic cycle models based on the absolute asymmetric Soai reaction is presented. The three models, which can give rise to amplification of enantiomeric excess and mirror-image symmetry breaking, vary by their monomeric, dimeric or trimeric order of the assumed catalytic species. Our numerical approach considered the entire chiral combinatorics of the diastereomeric interactions in the models as well as the multiplicity of coupled reversible reactions without applying fast equilibration or quasi-steady state approximations. For the simplest monomeric model, an extensive range of parameters was explored employing a random grid parameter scanning method that revealed the influence of the parameter values on the product distribution, the reaction-time, the attenuation or amplification of enantiomeric excess as well as on the presence or absence of mirror-image symmetry breaking. A symmetry breaking test was imposed on the three models showing that an increase in the catalytic oligomer size from one to three leads to a higher tolerance to poorer chiral recognition between the diastereoisomers and identifies the greater impact of the diastereoisomeric energy difference over an imperfect stereoselectivity in the catalytic step. This robustness is understood as a particular case of so-called kinetic proofreading in asymmetric autocatalysis.

Out of fuzzy chemistry: from prebiotic chemistry to metabolic networks

The origin of life on Earth was a chemical affair. So how did primitive biochemical systems originate from geochemical and cosmochemical processes on the young planet? Contemporary research into the origins of life subscribes to the Darwinian principle of material causes operating in an evolutionary context, as advocated by A. I. Oparin and J. B. S. Haldane in the 1920s. In its simplest form (e.g., a bacterial cell) extant biological complexity relies on the functional integration of metabolic networks and replicative genomes inside a lipid boundary. Different research programmes have explored the prebiotic plausibility of each of these autocatalytic subsystems and combinations thereof: self-maintained networks of small molecules, template chemistry, and self-reproductive vesicles. This tutorial review focuses on the debates surrounding the origin of metabolism and offers a brief overview of current studies on the evolution of metabolic networks. I suggest that a leitmotif in the origin and evolution of metabolism is the role played by catalysers' substrate ambiguity and multifunctionality.

Prebiotic chemistry: a new modus operandi

A variety of macromolecules and small molecules-(oligo)nucleotides, proteins, lipids and metabolites-are collectively considered essential to early life. However, previous schemes for the origin of life-e.g. the 'RNA world' hypothesis-have tended to assume the initial emergence of life based on one such molecular class followed by the sequential addition of the others, rather than the emergence of life based on a mixture of all the classes of molecules. This view is in part due to the perceived implausibility of multi-component reaction chemistry producing such a mixture. The concept of systems chemistry challenges such preconceptions by suggesting the possibility of molecular synergism in complex mixtures. If a systems chemistry method to make mixtures of all the classes of molecules considered essential for early life were to be discovered, the significant conceptual difficulties associated with pure RNA, protein, lipid or metabolism 'worlds' would be alleviated. Knowledge of the geochemical conditions conducive to the chemical origins of life is crucial, but cannot be inferred from a planetary sciences approach alone. Instead, insights from the organic reactivity of analytically accessible chemical subsystems can inform the search for the relevant geochemical conditions. If the common set of conditions under which these subsystems work productively, and compatibly, matches plausible geochemistry, an origins of life scenario can be inferred. Using chemical clues from multiple subsystems in this way is akin to triangulation, and constitutes a novel approach to discover the circumstances surrounding the transition from chemistry to biology. Here, we exemplify this strategy by finding common conditions under which chemical subsystems generate nucleotides and lipids in a compatible and potentially synergistic way. The conditions hint at a post-meteoritic impact origin of life scenario.