Improving the binding affinity of a chemical series by systematically probing one of its exit vectors is a medicinal chemistry activity that can benefit from molecular modeling input. Herein, we compare the effectiveness of four approaches in prioritizing building blocks with better potency: selection by a medicinal chemist, manual modeling, docking followed by manual filtering, and free energy calculations (FEP). Our study focused on identifying novel substituents for the apolar S2 pocket of cathepsin L and was conducted entirely in a prospective manner with synthesis and activity determination of 36 novel compounds. We found that FEP selected compounds with improved affinity for 8 out of 10 picks compared to 1 out of 10 for the other approaches. From this result and other additional analyses, we conclude that FEP can be a useful approach to guide this type of medicinal chemistry optimization once it has been validated for the system under consideration.