Mutations in coding regions of enzymes necessary for organismal functioning generally have negative impacts. However, little is known about how mutations in transcription factor binding motifs (TFBMs) can modify the impact of mutations in coding regions of enzymes. This study uses population genetic simulation to assess the correlative fitness impacts between accruing mutations within TFBMs and coding regions of an enzyme. We find that, generally, increases in expression through the recruitment of novel TFs can compensate for accruing mutations that confer negative impacts on fitness within an enzyme’s coding regions. Further, we find the optimal quantity of fixed mutations within TFBMs fluctuates in response to the quantity and types of mutations within coding regions. This optimum has a direct relationship with the number of mutations that confer negative fitness impacts in coding regions and an indirect relationship with the number of mutations that confer positive fitness. Our study provides a novel and translatable method of simulating the effects of TFBMs on potential enzyme diversification.