Catalysis by Self-Assembled Structures in Emergent Reaction Networks

Abstract

Abstract. We study a new variant of the dissipative particle dynamics (DPD) model that includes the possibility of dynamically forming and breaking strong bonds. The emergent reaction kinetics may then interact with self-assembly processes. We observe that self-assembled amphiphilic aggregations such as micelles have a catalytic effect on chemical reaction networks, changing both equilibrium concentrations and reaction frequencies. These simulation results are in accordance with experimental results on the so-called "concentration effect".

The Role of Environmental Dynamics in the Emergence of Autocatalytic Networks

“…The multi-agent modeling approach facilitates qualitatively different system features than the DE approach, including spatial heterogeneity, local interactions, and greater sensitivity to small effects and randomness (Scholl 2001). Within the broader category of multi-agent models, the dissipative particle dynamics (DPD) model paradigm was selected to use in this dissertation, for its appropriateness (specialized in middlescale molecules) and generality (not overly constrained by physical chemistry) (Flekkøy & Coveney 1999), and for its current application to related topics in OOL research (the formation of protocells [Fellermann et al 2007, Gazzola et al 2007). A particular DPD system was found (Gazzola et al 2007), and experiments from foundational ARN literature were selected for replicating in the DPD model .…”

“…Within the broader category of multi-agent models, the dissipative particle dynamics (DPD) model paradigm was selected to use in this dissertation, for its appropriateness (specialized in middlescale molecules) and generality (not overly constrained by physical chemistry) (Flekkøy & Coveney 1999), and for its current application to related topics in OOL research (the formation of protocells [Fellermann et al 2007, Gazzola et al 2007). A particular DPD system was found (Gazzola et al 2007), and experiments from foundational ARN literature were selected for replicating in the DPD model . The preliminary objective of replicating DE results in DPD models was undertaken to add credibility to the primary findings about the importance of environmental dynamics, and to give these findings greater relevance in the field of ARN research.…”

“…The primary phenomenon being researched here-the emergence of an autocatalytic reaction network-lives primarily in the field of ALife . The dissipative particle dynamics model that was adapted for this research is most commonly used in chemistry and biology (Flekkøy & Coveney 1999), but the particular software arrived via an ALife project in protocell membrane formation (Gazzola et al 2007). Models of the "hard science" DPD paradigm resemble the multiagent models of many "soft science" fields, from sociology to economics.…”

“…The related paradigm of molecular dynamics (MD) is designed for modeling much smaller systems and effects, close to the atomic scale, and is therefore not as useful for modeling at the scale of an ARN (Flekkøy & Coveney 1999). DPD models are also well suited to the study of hydrodynamic systems (like an ARN) and have been used to model the behaviors of lipids and lipid-like particles, including the formation of vesicles and protocells from these particles (Fellermann et al 2007;Gazzola et al 2007;Solé 2009). …”

“…The specific DPD modeling software used in this dissertation is derived from a package that has been used in other ALife research (Gazzola et al 2007). The source code for the software was generously made available, so that it could be modified as necessary for the ARN simulations.…”