Significance Due to the development of resistance against commonly used antibiotics, new derivatives that avoid resistance mechanisms need to be developed. To address this problem, a rational prioritization strategy is outlined for macrolide antibiotics. Candidates are screened based on their solubility, membrane permeability, and binding affinity using a tiered optimization approach of free energy simulations and quantum mechanics/molecular mechanics calculations. After prioritization by computational methods, the best candidates are evaluated experimentally. The strategy creates a targeted substance library that is highly enriched in compounds with antibacterial activity. This allows for faster iterations in the development of new antibiotic derivatives.