Analyzing three additional enzyme systems in this study, we demonstrate the interpretive power and versatility of PyCPET to understand the nature of active site electric fields. For example, looking at the electric field configurations in Cyt C showed the dynamic sampling of reduction potentials, all while still reproducing averaged experimental results. The 3-D electric field and its dynamics in the HIV-1 protease studied shed light on the nature of preorganized 𝐸𝐸 "⃗ (𝑟𝑟) along and perpendicular to the peptide bond. Lastly, we utilized both 3-D field PCAs and topological calculations to tease out the impact of a mutation on the dynamics of 𝐸𝐸 "⃗ (𝑟𝑟) in liver alcohol dehydrogenases. Our discussion of the three example systems serve as a template for future uses of PyCPET. The power of PyCPET over other methods is two-fold: dynamics and highdimensional analysis. These two properties allow for much richer studies across molecular dynamics while also allowing users to focus on representative structures for higher-order analysis such as QM/MM mechanistic calculations.