Explicit Representation of Cation-π Interactions in Force Fields with 1/r4 Nonbonded Terms.
Aysegul TurupcuJulian Tirado-RivesWilliam L JorgensenPublished in: Journal of chemical theory and computation (2020)
The binding energies for cation-π complexation are underestimated by traditional fixed-charge force fields owing to their lack of explicit treatment of ion-induced dipole interactions. To address this deficiency, an explicit treatment of cation-π interactions has been introduced into the OPLS-AA force field. Following prior work with atomic cations, it is found that cation-π interactions can be handled efficiently by augmenting the usual 12-6 Lennard-Jones potentials with 1/r4 terms. Results are provided for prototypical complexes as well as protein-ligand systems of relevance for drug design. Alkali cation, ammonium, guanidinium, and tetramethylammonium were chosen for the representative cations, while benzene and six heteroaromatic molecules were used as the π systems. The required nonbonded parameters were fit to reproduce structure and interaction energies for gas-phase complexes from density functional theory (DFT) calculations at the ωB97X-D/6-311++G(d,p) level. The impact of the solvent was then examined by computing potentials of mean force (pmfs) in both aqueous and tetrahydrofuran (THF) solutions using the free-energy perturbation (FEP) theory. Further testing was carried out for two cases of strong and one case of weak cation-π interactions between druglike molecules and their protein hosts, namely, the JH2 domain of JAK2 kinase and macrophage migration inhibitory factor. FEP results reveal greater binding by 1.5-4.4 kcal/mol from the addition of the explicit cation-π contributions. Thus, in the absence of such treatment of cation-π interactions, errors for computed binding or inhibition constants of 101-103 are expected.
Keyphrases
- ionic liquid
- density functional theory
- molecular dynamics
- adipose tissue
- binding protein
- emergency department
- small molecule
- genome wide
- protein protein
- oxidative stress
- dna binding
- replacement therapy
- patient safety
- transcription factor
- computed tomography
- tyrosine kinase
- molecular docking
- dna methylation
- adverse drug
- monte carlo
- quality improvement