Thermodynamic consistency of autocatalytic cycles

T Thomas Kosc (Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1) D Denis Kuperberg (Laboratoire de l’Informatique du Parallélisme) E Etienne Rajon (Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1) S Sylvain Charlat (Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1)

Abstract

Autocatalysis is seen as a potential key player in the origin of life, and perhaps more generally in the emergence of Darwinian dynamics. Building on recent formalizations of this phenomenon, we tackle the computational challenge of exhaustively detecting minimal autocatalytic cycles (autocatalytic cores) in reaction networks and further evaluate the impact of thermodynamic constraints on their realization under mass action kinetics. We first characterize the complexity of the detection problem by proving its NP-completeness. This justifies the use of constraint solvers to list all cores in a given reaction network, and also to group them into compatible sets, composed of cores whose stoichiometric requirements are not contradictory. Crucially, we show that the introduction of thermodynamic realism does constrain the composition of these sets. Compatibility relationships among autocatalytic cores can indeed be disrupted when the reaction kinetics obey thermodynamic consistency throughout the network. On the contrary, these constraints have no impact on the realizability of isolated cores, unless upper or lower bounds are imposed on the concentrations of the reactants. Overall, by better characterizing the conditions of autocatalysis in complex reaction systems, this work brings us a step closer to assessing the contribution of this collective chemical behavior to the emergence of natural selection in the primordial soup.

Article Details

Volume / Issue Vol. 122, Issue 18
Published May 06, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (4)

T

Thomas Kosc

Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1

D

Denis Kuperberg

Laboratoire de l’Informatique du Parallélisme

E

Etienne Rajon

Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1

S

Sylvain Charlat

Laboratoire de Biométrie & Biologie Evolutive, Université Lyon 1