Noncompetitive inhibitors of sarco- and endoplasmic reticulum calcium-ATPase (SERCA) have important therapeutic value in the treatment of cancer, due to their ability to induce apoptosis in cancer cells in a proliferation-independent manner. Thapsigargin (TG) and its analogues are one such class of inhibitors that bind to a hydrophobic pocket located in the transmembrane region of SERCA near the biomembrane surface and interfere with calcium transport. The binding free energies of thapsigargin-based inhibitors of SERCA were computed using a novel linear interaction energy (LIE) method with a surface generalized Born (SGB) continuum solvation model. A training set of 20 TG analogues was used to build a binding affinity model for estimating the free energy of binding for 18 new inhibitors with a root-mean-square (rms) error of 1.36 kcal/mol with respect to experimental data. For 15 out of the 18 inhibitors in the test set, the rms error was 1.02 kcal/mol, which is on the order of the accuracy level achieved by highly rigorous free energy of perturbation (FEP) or thermodynamic integration (TI) methods. On the basis of the analysis of the binding cavity at the interface of the membrane surface and the cytoplasmic region, we propose that side chains of TG derivatives at the O-8 position orient toward the cytoplasmic region through a hydrophobic channel. On the basis of this insight, four analogues of varying side chain length at the O-8 position with a charged moiety at the end were designed, tested with LIE methodology, and then validated experimentally for their SERCA inhibition activity. Low levels of rms error for the majority of inhibitors establish the structure-based LIE method as an efficient tool for generating more potent and specific inhibitors of SERCA by testing rationally designed lead compounds based on thapsigargin derivatization.