Predicting the growth and dynamics of ATP-based protocells through modeling

Abstract The emergence of a minimal cell cycle required the presence of growing compartments, likely regulated by complex molecular networks. Reactions that produce phase separating molecules can produce such growing compartments, resulting in a direct connection between anabolic reactions and protocell growth. Here, we derive a kinetic rate model for the growth of coacervate droplets derived from experimentally observed droplet distributions of active ATP-based protein coacervates. With this model, we can predict how adjustments in rates, such as the transport from molecules in or out of the droplet phase influences the number of droplets that form. We demonstrate how a population balance modeling framework can predict the formation and growth dynamics of coacervate droplets under varying reaction conditions, integrating theoretical simulations and experiments. Our results highlight the critical role of initial reactant concentrations and reaction kinetics in regulating droplet size distribution and composition, providing insights into the tunability of protocell-like systems.

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Publication Details

Journal
Physica Scripta
Published
2025-09-18
DOI
https://doi.org/10.1088/1402-4896/ae08fa
Primary Topic
Lipid Membrane Structure and Behavior
Type
article
Field-Weighted Citation Impact
0.00

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article

Predicting the growth and dynamics of ATP-based protocells through modeling

Nazila Yaghini
Physica Scripta
Lipid Membrane Structure and Behavior
article

Predicting the growth and dynamics of ATP-based protocells through modeling

Nazila Yaghini
article en

Abstract

Abstract The emergence of a minimal cell cycle required the presence of growing compartments, likely regulated by complex molecular networks. Reactions that produce phase separating molecules can produce such growing compartments, resulting in a direct connection between anabolic reactions and protocell growth. Here, we derive a kinetic rate model for the growth of coacervate droplets derived from experimentally observed droplet distributions of active ATP-based protein coacervates. With this model, we can predict how adjustments in rates, such as the transport from molecules in or out of the droplet phase influences the number of droplets that form. We demonstrate how a population balance modeling framework can predict the formation and growth dynamics of coacervate droplets under varying reaction conditions, integrating theoretical simulations and experiments. Our results highlight the critical role of initial reactant concentrations and reaction kinetics in regulating droplet size distribution and composition, providing insights into the tunability of protocell-like systems.

Physica Scripta
Eindhoven University of Technology (NL)
Radboud Universiteit
Openalex Percentile: Top 78%
Lipid Membrane Structure and Behavior
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Predicting the growth and dynamics of ATP-based protocells through modeling — Nazila Yaghini · Physica Scripta (2025) | TGRS Research Map | TGRS