ENVIRONMENT: a computational platform to stochastically simulate reacting and self-reproducing lipid compartments

Area of Science:

• Biochemistry
• Computational Biology
• Astrobiology

Background:

• Protocellular systems are key to understanding the origin of life.
• Simulating these systems requires accounting for complex chemical reactions and compartmentalization.
• Heterogeneous conditions, like lipid structures coexisting with aqueous domains, are crucial for early cellular evolution.

Purpose of the Study:

• To introduce and describe the features of the ENVIRONMENT computational platform.
• To demonstrate the application of stochastic kinetics for simulating protocellular systems.
• To bridge theoretical simulations with experimental data in protocell research.

Main Methods:

• Development of the ENVIRONMENT computational platform.
• Stochastic kinetics simulations of reaction networks.
• Modeling of heterogeneous environments including lipid structures and aqueous domains.
• Comparison of simulation results with laboratory experiments.

Main Results:

• The ENVIRONMENT platform enables stochastic simulation of protocellular system dynamics.
• The platform effectively models reaction networks in heterogeneous conditions.
• Simulations provide insights into the stability and evolution of protocells.
• Validation of simulation results against experimental data.

Conclusions:

• The ENVIRONMENT platform is a valuable tool for studying protocell origins.
• Stochastic kinetics is a suitable approach for modeling complex protocellular systems.
• Integrating computational and experimental approaches accelerates research in minimal cell systems.