This formalism shows that RNA--protein coevolution is not a static optimization but a dynamic balance of interdependent forces.
The persistence of the genetic code reflects the system settling into a stable attractor basin rather than reaching a one-time evolutionary solution.
By embedding Lotka--Volterra coupling into the replicator--mutator framework, we obtain a multi-level model: local mutations and codon reassignments feed into global ecological-style dynamics, producing oscillations, bifurcations, and attractors. This provides a rigorous account of how RNA and proteins could have co-stabilized through emergent coevolution.
E. Emergent attractors and bifurcations
One of the central advantages of framing RNA--protein coevolution within Complex Adaptive Systems is the ability to analyze emergent attractors and bifurcations that arise from coupled dynamics.
1. Attractors as co-adapted states.
In the coupled replicator--mutator and Lotka--Volterra model, equilibria correspond to co-adapted RNA--protein configurations where mutual dependencies are balanced. These attractors can represent ribosome-like states: RNA motifs that efficiently encode protein domains, and proteins that stabilize RNA and facilitate translation.
2. Multiple attractors (multistability).
Depending on initial conditions and parameter regimes (e.g., mutation rate, thermal stress, coupling strength), the system may converge to different attractors:
High-stability/low-diversity regime, favoring thermostable proteins but limited coding innovation.
High-diversity/low-stability regime, favoring exploratory RNA mutability with fragile protein stability.
Balanced coadaptation regime, approximating observed ribonucleoprotein complexes.
3. Bifurcations as evolutionary transitions.
Small changes in parameters can shift the system between attractors, creating bifurcation points analogous to punctuated equilibria. For example, exceeding a critical mutation rate threshold may destabilize an RNA--protein attractor, leading to collapse or transition into a new adaptive regime.
