An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions

Abstract

A central question in origins of life research is how non-entailed chemical processes, which simply dissipate chemical energy because they can do so due to immediate reaction kinetics and thermodynamics,...

The Effects of Iron on In Silico Simulated Abiotic Reaction Networks

“…Various constraints can be imposed on the rule set to ensure that the generated reaction network is specific and not a generalized combinatorial set of all possible graphs, i.e., it accurately represents real-world chemistry. We note that previous applications of these methods, even using 200 AMU expansion cutoffs, manage to faithfully reproduce diverse product suites detected in real world chemistry, match high-resolution mass spectra of real reactions, and faithfully predict trends in real chemistry-derived Van Krevelen and Kendrick plots [20], attesting to these methods' ability to predict real world chemistry. We briefly review the use of these methods here, more complete information can be found in [20].…”

“…We note that previous applications of these methods, even using 200 AMU expansion cutoffs, manage to faithfully reproduce diverse product suites detected in real world chemistry, match high-resolution mass spectra of real reactions, and faithfully predict trends in real chemistry-derived Van Krevelen and Kendrick plots [20], attesting to these methods' ability to predict real world chemistry. We briefly review the use of these methods here, more complete information can be found in [20]. This pipeline is open-source, written mostly in Python, and can be accessed along with relevant documentation at https:// github.com/Reaction-Space-Explorer/reac-space-exp (accessed on 10 July 2021).…”

“…Recently, it has been shown that large complex reaction networks (CRNs) can be accurately and efficiently modeled using graph theory-based reaction network expansion techniques [20] to produce complex reaction network representations (CRNRs). These CRNRs are computed using reaction rules that are in silico representations of known real-world chemical reaction mechanisms.…”

“…This reaction network expansion technique allows rapid CRNR modification by introducing new reaction rules. While such techniques are "kinetically naive,", e.g., they are not able to predict kinetics, and are practically computationally limited by the mass and number of compounds/reactions they can model, they can nevertheless accurately reproduce complex reported product suites, match high-resolution mass spectra of such reaction mixtures, and reproduce compositional trends in extended Van Krevelen and Kendrick plots from experimental data [20].…”

Can prebiotic systems survive in the wild? An interference chemistry approach

“…Given the absence of empirical evidence for the nature of environments and chemistry on the prebiotic Earth, we envisage that data integration accounting for interference effects will at some level rely on linked simulations. Progress is this regard being made in several relevant areas, including the formulation of selfconsistent global biogeochemical models, which are being employed to reconstruct the evolution of Earth's surface environment over time (Lenton et al, 2018;Mills et al, 2018), and rule-based models of complex chemical systems in the modelling of physical chemistry (Goldford et al, 2019;Wołos et al, 2020;Arya et al, 2022). We view these tools as being likely essential for bridging spatial and timescales that are not tractable in the lab and for linking fields (e.g., feeding simulations of prebiotic systems into models of planetary geochemistry).…”