Graded Autocatalysis Replication Domain Model Research Articles

The GARD Prebiotic Reproduction Model Described in Order and Complexity.

Early steps in the origin of life were necessarily connected to the unlikely formation of self-reproducing structures from chaotic chemistry. Simulations of chemical kinetics based on the graded autocatalysis replication domain (GARD) model demonstrate the ability of a micellar system to become self-reproducing units away from equilibrium. Even though they may be very rare in the initial state of the system, the property of their endogenous mutually catalytic networks being dynamic attractors greatly enhanced reproduction propensity, revealing their potential for selection and Darwinian evolution processes. In parallel, order and complexity have been shown to be crucial parameters in successful evolution. Here, we probe these parameters in the dynamics of GARD-governed entities in an attempt to identify characteristic mechanisms of their development in non-covalent molecular assemblies. Using a virtual random walk perspective, a value for consecutive order is defined based on statistical thermodynamics. The complexity, on the other hand, is determined by the size of a minimal algorithm fully describing the statistical properties of the random walk. By referring to a previously published diagonal line in an order/complexity diagram that represents the progression of evolution, it is shown that the GARD model has the potential to advance in this direction. These results can serve as a solid foundation for identifying general criteria for future analyses of evolving systems.

Protobiotic Systems Chemistry Analyzed by Molecular Dynamics.

Systems chemistry has been a key component of origin of life research, invoking models of life’s inception based on evolving molecular networks. One such model is the graded autocatalysis replication domain (GARD) formalism embodied in a lipid world scenario, which offers rigorous computer simulation based on defined chemical kinetics equations. GARD suggests that the first pre-RNA life-like entities could have been homeostatically-growing assemblies of amphiphiles, undergoing compositional replication and mutations, as well as rudimentary selection and evolution. Recent progress in molecular dynamics has provided an experimental tool to study complex biological phenomena such as protein folding, ligand-receptor interactions, and micellar formation, growth, and fission. The detailed molecular definition of GARD and its inter-molecular catalytic interactions make it highly compatible with molecular dynamics analyses. We present a roadmap for simulating GARD’s kinetic and thermodynamic behavior using various molecular dynamics methodologies. We review different approaches for testing the validity of the GARD model by following micellar accretion and fission events and examining compositional changes over time. Near-future computational advances could provide empirical delineation for further system complexification, from simple compositional non-covalent assemblies towards more life-like protocellular entities with covalent chemistry that underlies metabolism and genetic encoding.

Primordial evolvability: Impasses and challenges

While it is generally agreed that some kind of replicating non-living compounds were the precursors of life, there is much debate over their possible chemical nature. Metabolism-first approaches propose that mutually catalytic sets of simple organic molecules could be capable of self-replication and rudimentary chemical evolution. In particular, the graded autocatalysis replication domain (GARD) model, depicting assemblies of amphiphilic molecules, has received considerable interest. The system propagates compositional information across generations and is suggested to be a target of natural selection. However, evolutionary simulations indicate that the system lacks selectability (i.e. selection has negligible effect on the equilibrium concentrations). We elaborate on the lessons learnt from the example of the GARD model and, more widely, on the issue of evolvability, and discuss the implications for similar metabolism-first scenarios. We found that simple incorporation-type chemistry based on non-covalent bonds, as assumed in GARD, is unlikely to result in alternative autocatalytic cycles when catalytic interactions are randomly distributed. An even more serious problem stems from the lognormal distribution of catalytic factors, causing inherent kinetic instability of such loops, due to the dominance of efficiently catalyzed components that fail to return catalytic aid. Accordingly, the dynamics of the GARD model is dominated by strongly catalytic, but not auto-catalytic, molecules. Without effective autocatalysis, stable hereditary propagation is not possible. Many repetitions and different scaling of the model come to no rescue. Despite all attempts to show the contrary, the GARD model is not evolvable, in contrast to reflexively autocatalytic networks, complemented by rare uncatalyzed reactions and compartmentation. The latter networks, resting on the creation and breakage of chemical bonds, can generate novel (‘mutant’) autocatalytic loops from a given set of environmentally available compounds. Real chemical reactions that make or break covalent bonds, rather than mere incorporation of components, are necessary for open-ended evolvability. The issue of whether or not several concrete chemical systems (rather than singular curiosities) could realize reflexively autocatalytic macromolecular networks will ultimately determine the relevance of metabolism-first approaches to the origin of life, as stepping stones towards true open-endedness that requires the combination of rich combinatorial chemistry controlled by information stored in template replicators.

Coevolution of compositional protocells and their environment

The coevolution of environment and living organisms is well known in nature. Here, it is suggested that similar processes can take place before the onset of life, where protocellular entities, rather than full-fledged living systems, coevolve along with their surroundings. Specifically, it is suggested that the chemical composition of the environment may have governed the chemical repertoire generated within molecular assemblies, compositional protocells, while compounds generated within these protocells altered the chemical composition of the environment. We present an extension of the graded autocatalysis replication domain (GARD) model--the environment exchange polymer GARD (EE-GARD) model. In the new model, molecules, which are formed in a protocellular assembly, may be exported to the environment that surrounds the protocell. Computer simulations of the model using an infinite-sized environment showed that EE-GARD assemblies may assume several distinct quasi-stationary compositions (composomes), similar to the observations in previous variants of the GARD model. A statistical analysis suggested that the repertoire of composomes manifested by the assemblies is independent of time. In simulations with a finite environment, this was not the case. Composomes, which were frequent in the early stages of the simulation disappeared, while others emerged. The change in the frequencies of composomes was found to be correlated with changes induced on the environment by the assembly. The EE-GARD model is the first GARD model to portray a possible time evolution of the composomes repertoire.

Polymer Gard: Computer Simulation of Covalent Bond Formation in Reproducing Molecular Assemblies

The basic Graded Autocatalysis Replication Domain (GARD) model consists of a repertoire of small molecules, typically amphiphiles, which join and leave a non-covalent micelle-like assembly. Its replication behavior is due to occasional fission, followed by a homeostatic growth process governed by the assembly's composition. Limitations of the basic GARD model are its small finite molecular repertoire and the lack of a clear path from a 'monomer world' towards polymer-based living entities. We have now devised an extension of the model (polymer GARD or P-GARD), where a monomer-based GARD serves as a 'scaffold' for oligomer formation, as a result of internal chemical rules. We tested this concept with computer simulations of a simple case of monovalent monomers, whereby more complex molecules (dimers) are formed internally, in a manner resembling biosynthetic metabolism. We have observed events of dimer 'take-over' - the formation of compositionally stable, replication-prone quasi stationary states (composomes) that have appreciable dimer content. The appearance of novel metabolism-like networks obeys a time-dependent power law, reminiscent of evolution under punctuated equilibrium. A simulation under constant population conditions shows the dynamics of takeover and extinction of different composomes, leading to the generation of different population distributions. The P-GARD model offers a scenario whereby biopolymer formation may be a result of rather than a prerequisite for early life-like processes.

Mutual catalysis in sets of prebiotic organic molecules: Evolution through computer simulated chemical kinetics

A thorough outlook on the origin of life needs to delineate a chemically rigorous, self-consistent path from highly heterogeneous, random ensembles of relatively simple organic molecules, to an entity that has rudimentary life-like characteristics. Such entity should be endowed with a capacity to express variation, undergo mutation-like changes and manifest a simple evolutionary process. For simulating such system we developed the Graded Autocatalysis Replication Domain (GARD) model for explicit kinetic analysis of mutual catalysis in sets of random oligomers derived from energized precursor monomers. The kinetic properties of the GARD model are based on vesicle enclosure and expansion. With the additional assumption of spontaneous vesicle splitting, a GARD evolution scenario is envisaged as a consequence of pure chemical kinetics. Here we show how the GARD model can serve as a platform for investigating the dynamics of self-organization mechanisms in molecular evolutionary processes.