Abstract
The origin of life must have involved an unlikely transition from chaotic chemistry to self-reproducing supramolecular structures. Previous quantitative analyses of self-reproducing mutually catalytic networks made of simple molecules have led to increasing popularity of this pre-RNA scenario for life’s origin. Here, we investigate in detail the reproduction characteristic of the graded autocatalysis replication domain (GARD) computer-simulated physicochemically rigorous lipid-based model. This model displays compatibility with heterogeneous environments, addresses the network’s spatial demarcation, and portrays trans-generational compositional information transfer. However, we find that compositionally reproducing states are extremely rare, suggesting that random roaming would be a vastly inefficient path toward reproduction. Rewardingly, the present study shows that all self-reproducing states are also dynamic attractors of the catalytic network. This suggests a greatly enhanced propensity for the spontaneous emergence of reproduction and primal evolution, augmenting the likelihood of protolife appearance.[Display omitted]
•Life’s origin may have involved self-reproducing supramolecular autocatalytic entities•Simulated physicochemical model for lipid assemblies shows frequent self-reproduction•Reproduction is observed only within very rare compositional states•Self-reproducers prove to be dynamic attractors, improving the chance for life’s origin
Simulations of the dynamic behavior of spontaneously formed lipid assemblies can offer insight into the origins of life, but few assembly compositions self-reproduce, presumably necessary for life to begin. Kahana et al. show that some self-reproducing compositions are dynamic attractors, making self-reproduction, and hence life’s emergence, much more plausible.
Original language | English |
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Article number | 101384 |
Number of pages | 19 |
Journal | Cell Reports Physical Science |
Volume | 4 |
Issue number | 5 |
DOIs | |
Publication status | Published - 17 May 2023 |