Abstract
There is a need for improved and generally applicable scoring functions for fragment-based approaches to ligand design. Here, we evaluate the performance of a computationally efficient model for inhibitory activity estimation, which is composed only of multipole electrostatic energy and dispersion energy terms that approximate long-range ab initio quantum mechanical interaction energies. We find that computed energies correlate well with inhibitory activity for a compound series with varying substituents targeting two subpockets of the binding site of Trypanosoma brucei pteridine reductase 1. For one subpocket, we find that the model is more predictive for inhibitory activity than the ab initio interaction energy calculated at the MP2 level. Furthermore, the model is found to outperform a commonly used empirical scoring method. Finally, we show that the results for the two subpockets can be combined, which suggests that this simple nonempirical scoring function could be applied in fragment–based drug design.
Highlights
Empirical computational methods are widely used in ligand discovery projects for ligand docking and computing ligand–receptor binding energetics
An example is the finding that for polar or charged inhibitors of phenylalanine ammonialyase and leucine aminopeptidase, the nonempirical first-order electrostatic interaction energy defined within perturbation theory [5] alone yielded a reasonable correlation with experimental inhibitory activity data
Such a simple model is insufficient for nonpolar receptors, like fatty acid amide hydrolase (FAAH), where inclusion of a nonempirical dispersion term, in addition to the electrostatic multipole
Summary
Empirical computational methods are widely used in ligand discovery projects for ligand docking and computing ligand–receptor binding energetics. An example is the finding that for polar or charged inhibitors of phenylalanine ammonialyase and leucine aminopeptidase, the nonempirical first-order electrostatic interaction energy defined within perturbation theory [5] (or its multipole component [6]) alone yielded a reasonable correlation with experimental inhibitory activity data. Such a simple model is insufficient for nonpolar receptors, like fatty acid amide hydrolase (FAAH), where inclusion of a nonempirical dispersion term, in addition to the electrostatic multipole
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