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Selection dynamics in autocatalytic systems: templates replicating through binary ligation

P R Wills1, S A Kauffman, B M Stadler

  • 1Santa Fe Institute, NM 87501, USA. p.wills@auckland.ac.nz

Bulletin of Mathematical Biology
|December 29, 1998
PubMed
Summary
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Autocatalytic binary ligation theory, using Michaelis-Menten kinetics, explains self-replication. This research details experimental parameters and models diverse outcomes like Darwinian selection and parabolic growth for nucleic acids and peptides.

Area of Science:

  • Biochemistry
  • Chemical Kinetics
  • Systems Biology

Background:

  • Autocatalytic processes are fundamental to life's origins and molecular evolution.
  • Understanding the kinetics of self-replication is crucial for fields like synthetic biology and astrobiology.
  • Previous models often simplified the complex interactions in autocatalytic systems.

Purpose of the Study:

  • To review and extend the theory of autocatalytic binary ligation.
  • To provide a detailed protocol for experimental parameter elucidation.
  • To analyze the kinetic behavior of systems with multiple self-replicating templates.

Main Methods:

  • Application of the Michaelis-Menten quasi-steady-state approximation.
  • Derivation of explicit analytical solutions for time-course data.

Related Experiment Videos

  • Generalization of kinetic equations for self- and cross-catalysis.
  • Analysis of systems with two competing templates.

    • Main Results:

    • Explicit analytical results describing experimental time-course data.
    • A protocol for determining essential experimental parameters.
    • Demonstration of diverse kinetic behaviors including exponential and parabolic growth laws.
    • Identification of conditions leading to selective coexistence or exclusion of species.

    Conclusions:

    • The generalized model accurately describes complex autocatalytic systems.
    • The framework is applicable to both nucleic acid and peptide self-replication.
    • This work provides a robust theoretical basis for studying molecular evolution and origin of life scenarios.