Development and binding affinity predictions of inhibitors targeting protein-protein interactions (PPI) still represent a major challenge in drug discovery efforts. This work reports application of a predictive non-empirical model of inhibitory activity for PPI inhibitors, exemplified here for small molecules targeting the menin-mixed lineage leukemia (MLL) interaction. Systematic ab initio analysis of menin-inhibitor complexes was performed, revealing the physical nature of these interactions. Notably, the non-empirical protein-ligand interaction energy comprising electrostatic multipole and approximate dispersion terms (E(10)El,MTP + EDas) produced a remarkable correlation with experimentally measured inhibitory activities and enabled accurate activity prediction for new menin-MLL inhibitors. Importantly, this relatively simple and computationally affordable non-empirical interaction energy model outperformed binding affinity predictions derived from commonly used empirical scoring functions. This study demonstrates high relevance of the non-empirical model we developed for binding affinity prediction of inhibitors targeting protein-protein interactions that are difficult to predict using empirical scoring functions.