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Contemporary efforts for modeling protein-ligand interactions entail a painful tradeoff – as reliable information on both noncovalent binding factors and the dynamic behavior of a protein-ligand complex is often beyond practical limits. In the following paper, we demonstrate that information drawn exclusively from static molecular structures can be used for the semi-quantitative prediction of experimentally-measured binding affinities for protein-ligand complexes. In the particular case considered here, inhibition constants (Ki) were calculated for eight different ligands of torpedo californica acetylcholinesterase using a simple, multiple-linearregression-based model. The latter, incorporating five informative and independent variables – drawn from QM cluster, DLPNO-CCSD(T) calculations and LED analyses on the eight complexes – is shown to recover no-lessthan 96% of the sum of squares for measured Ki values, and used to predict the inhibition potential for yet another ligand (E20, for which no Ki values are available in the literature). This thus challenges the widespread assumption that “static pictures” are inadequate for predicting reactivity properties of flexible and dynamic protein-ligand systems.