We apply quantum algorithms to mRNA sequence optimization with the goal of finding an mRNA sequence that encodes the target protein while satisfying various constraints, such as maximizing codon usage (via probabilities and CAI), chemical stability (via GC content), and minimizing nucleotide repeats. The system gradually evolves from an initial state representing all possible sequences to a final state corresponding to the optimal solution.