Robust Predictive Power of the Electrostatic Term at Shortened Intermolecular Distances

At distances shorter than equilibrium, electrostatic interactions seem to be a more robust indicator of relative molecular dimer stability than more accurate electronic structure approaches. We arrive at this conclusion by investigating the nonparametric correlation between reference interaction energies at equilibrium geometries (coupled cluster with singles, doubles, and perturbative triples at the complete basis set limit, Δ<i>E</i>_CCSD(T)^CBS,ref) and its various approximate values obtained at a range of distances for a training set of 22 biologically relevant dimers. The reference and other costly methods start to fail to reproduce the equilibrium ranking of dimer stabilities when the intermolecular distance is shortened by more than 0.2 Å, but the full electrostatic component (includes penetration) maintains a high success rate. Such trends provide a new perspective for any applications where inaccurate structures are used out of necessity, such as the scoring of ligands docked to enzyme active sites

Robust Predictive Power of the Electrostatic Term at Shortened Intermolecular Distances

At distances shorter than equilibrium, electrostatic interactions seem to be a more robust indicator of relative molecular dimer stability than more accurate electronic structure approaches. We arrive at this conclusion by investigating the nonparametric correlation between reference interaction energies at equilibrium geometries (coupled cluster with singles, doubles, and perturbative triples at the complete basis set limit, Δ<i>E</i>_CCSD(T)^CBS,ref) and its various approximate values obtained at a range of distances for a training set of 22 biologically relevant dimers. The reference and other costly methods start to fail to reproduce the equilibrium ranking of dimer stabilities when the intermolecular distance is shortened by more than 0.2 Å, but the full electrostatic component (includes penetration) maintains a high success rate. Such trends provide a new perspective for any applications where inaccurate structures are used out of necessity, such as the scoring of ligands docked to enzyme active sites

Physical Nature of Fatty Acid Amide Hydrolase Interactions with Its Inhibitors: Testing a Simple Nonempirical Scoring Model

Fatty acid amide hydrolase (FAAH) is an enzyme responsible for the deactivating hydrolysis of fatty acid ethanolamide neuromodulators. FAAH inhibitors have gained considerable interest due to their possible application in the treatment of anxiety, inflammation, and pain. In the context of inhibitor design, the availability of reliable computational tools for predicting binding affinity is still a challenging task, and it is now well understood that empirical scoring functions have several limitations that in principle could be overcome by quantum mechanics. Herein, systematic ab initio analyses of FAAH interactions with a series of inhibitors belonging to the class of the <i>N</i>-alkylcarbamic acid aryl esters have been performed. In contrast to our earlier studies of other classes of enzyme–inhibitor complexes, reasonable correlation with experimental results required us to consider correlation effects along with electrostatic term. Therefore, the simplest comprehensive nonempirical model allowing for qualitative predictions of binding affinities for FAAH ligands consists of electrostatic multipole and second-order dispersion terms. Such a model has been validated against the relative stabilities of the benchmark S66 set of biomolecular complexes. As it does not involve parameters fitted to experimentally derived data, this model offers a unique opportunity for generally applicable inhibitor design and virtual screening