The correlation between binding energies and bioactivities is the core of structure‐based computer‐aided drug design. However, many models to address this correlation are still strongly system‐dependent at current stage. We constructed two explicit models to correlate the binding energies with the inhibitory activities of flavonoids and sulfonyl‐pyridazinones as inhibitors of aldose reductase. The introduction of multiple complex states comprised of protein, coenzyme, substrate, and inhibitor can remarkably improve the correlation coefficients, compared with that using single complex state. Recombination of energy terms from complex structures and molecular descriptors of inhibitors can further improve the correlation. The explicit models provide correlation coefficients of 0.90 and 0.92 for flavonoids and sulfonyl‐pyridazinones, respectively. These models also steadily present the contribution from each energy term and the favorite of protein–inhibitor complex states. Meanwhile, we also observed that some inhibitors can accommodate alternative sites out of the conserved binding pocket at the presence/absence of coenzyme and substrate. It is responsible for the remarkable change in the binding energies and thus significantly influences the correlation between the structures and the inhibitory activities. Overall, this work presents a rational way to construct reliable explicit models through the combination of multiple physically accessible complex states, even though each of them only bears marginal information related to their activities.