This paper formalizes the genetic codon space — all 64 trinucleotide combinations over A, T, G, C — as a finite fractal structure under four properties: a closed rule set (the genetic code), a closed domain (64 elements), a five-level scale-invariant hierarchy (base → codon position → amino acid → functional class), and deterministic convergence to functional attractors. We introduce the Fractal Disruption Score (FD), a scale-weighted measure of mutational displacement within this structure. Exhaustive enumeration of all 549 possible single-nucleotide substitutions demonstrates that pathogenic transitions concentrate at FD ≥ 6, corresponding to functional class-crossing events. The framework is applied to nucleic acid drug target identification, where the finite structure of codon space permits exact target enumeration without approximation or statistical learning. This paper is a mathematical proposal. Clinical validation by qualified specialists is a prerequisite for any therapeutic application.
Takeo Yamamoto (Sun,) studied this question.