Cross-reactions and other systematic difficulties generated by the coupling of functional chemical subsystems pose the largest challenge for assembling a viable protocell in the laboratory. Our current work seeks to identify and clarify such key issues as we represent and analyze in simulation a full implementation of a minimal protocell. Using a 3D dissipative particle dynamics simulation method, we are able to address the coupled diffusion, self-assembly, and chemical reaction processes required to model a full life cycle of a protocell composed of coupled genetic, metabolic, and container subsystems. Utilizing this minimal structural and functional representation of the constituent molecules, their interactions, and their reactions, we identify and explore the nature of the many linked processes for the full protocellular system. Obviously the simplicity of this simulation method combined with the inherent system complexity prevents us from expecting quantitative simulation predictions from these investigations. However, we report important findings on systemic processes, some previously predicted and some newly discovered, as we couple the protocellular self-assembly processes and chemical reactions.

Army ant colonies display complex foraging raid patterns involving thousands of individuals communicating through chemical trails. In this article we explore, by means of a simple search algorithm, the properties of these trails in order to test the hypothesis that their structure reflects an optimized mechanism for exploring and exploiting food resources. The raid patterns of three army ant species, Eciton hamatum , Eciton burchelli , and Eciton rapax , are analyzed. The respective diets of these species involve large but rare, small but common, and a combination of large but rare and small but common food sources. Using a model proposed by Deneubourg et al. [4], we simulate the formation of raid patterns in response to different food distributions. Our results indicate that the empirically observed raid patterns maximize return on investment, that is, the amount of food brought back to the nest per unit of energy expended, for each of the diets. Moreover, the values of the parameters that characterize the three optimal pattern-generating mechanisms are strikingly similar. Therefore the same behavioral rules at the individual level can produce optimal colony-level patterns. The evolutionary implications of these findings are discussed.