The persistence of thermostability signals implies that early life likely emerged under fluctuating or extreme thermal conditions, where robustness was critical for survival. This environmental pressure would have acted simultaneously on RNA templates and peptide structures, favoring codon--amino acid assignments that maximized stability.
4. Theoretical challenge.
While correlations between genetic codes and protein thermostability are well documented, existing models treat them as post hoc optimizations rather than emergent properties of dynamic coevolution. In linear frameworks, it remains unclear how codon assignments and structural stability could have synchronized in the absence of foresight. Thus, the empirical record suggests that the genetic code and protein thermostability are deeply intertwined. Yet the mechanism by which such correlations emerged remains obscure. To resolve this, we require a formalism that captures feedback, trade-offs, and attractor dynamics---a role well suited to Complex Adaptive Systems modeling.
C. Current limitations: descriptive/statistical approaches without formal dynamics
Although proteomic and genomic studies have uncovered rich correlations linking genetic codes, dipeptide frequencies, and protein thermostability, the majority of current approaches remain descriptive and statistical. They identify patterns but do not capture the mechanisms that produce and stabilize them.
1. Correlations without causation.
Analyses such as codon--amino acid frequency distributions or dipeptide usage profiles show that the genetic code and protein structure are linked. However, these correlations stop short of explaining how co-selection pressures act dynamically to produce and maintain these linkages over evolutionary time.
2. Linear narratives.
RNA-first and protein-first models often retrofit observed data into linear evolutionary scenarios.
Such frameworks assume that either coding preceded structural adaptation or vice versa, overlooking the possibility of simultaneous, feedback-driven coevolution.
3. Lack of dynamic formalism.
Existing studies rarely employ mathematical models capable of describing nonlinear interactions, epistasis, or attractor dynamics. As a result, they cannot account for the stabilization of interdependent systems such as RNA--protein complexes, nor predict conditions under which coadapted states might emerge or fail.
