Genetic Information as a "Chord" of Chemical Oscillations: Emergence of Catalyst-RNA Systems Driven by Superposed Rhythms
Takeshi Ishida

TL;DR
This study presents a computational model showing how internal chemical oscillations can bias sequence formation, leading to the emergence of catalytic and informational molecules relevant to the origin of life.
Contribution
It introduces a novel cognitive model with coupled chemical oscillators that enhances the formation of functional, information-bearing polymers compared to random selection.
Findings
The model significantly increases the rate of catalytic loop formation.
It promotes accumulation of functional molecules and reduces sequence entropy.
Superposed rhythms outperform random processes across various sensitivity analyses.
Abstract
A central challenge in the origin of life is understanding how catalytic peptide-like polymers and information-bearing nucleic acid-like polymers emerged as an interde-pendent system. This study constructs a primordial cognitive model incorporating two internal Lotka-Volterra chemical oscillators to investigate, through simulation, whether a catalytic loop, primordial tRNAs, and nucleic acids that record and amplify them, can form through the interaction of polymers represented by binary (0/1) sequences. In this model, a mechanism was introduced where the synthesis of internal oscillations pro-vides a temporal bias for 0/1 selection during polymer elongation, while generated functional sequences are protected, recorded, and re-amplified. Simulation results demonstrated that the proposed cognitive model significantly outperformed a contrast model based on random 0/1 selection in terms of…
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