Prediction of molecular interactions and physicochemical properties relevant for vasopressin V2 receptor antagonism

We have developed two ligand- and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity of vasopressin V2 receptor (V2R) antagonist and eventually to predict the expected binding mode to V2R. The obtained quantitative structure activity relationship (QSAR) model showed a correlation of the antagonist activity with the hydration energy (E-H2O), the polarizability (P), and the calculated partial charge on atom N7 (q6) of the common substructure. The first two descriptors showed a positive contribution to antagonist activity, while the third one had a negative contribution. V2R was modeled and further relaxed on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) membrane by molecular dynamics simulations. The receptor antagonist complexes were guessed by molecular docking, and the stability of the most relevant structures was also evaluated by molecular dynamics simulations. As a result, amino acid residues Q96, W99, F105, K116, F178, A194, F307, and M311 were identified with the probably most relevant antagonist-receptor interactions on the studied complexes. The proposed QSAR model could explain the molecular properties relevant to the antagonist activity. The contributions to the antagonist-receptor interaction appeared also in agreement with the binding mode of the complexes obtained by molecular docking and molecular dynamics. These models will be used in further studies to look for new V2R potential antagonist molecules.

Automated summary

In this study, two computational approaches based on ligand and receptor were developed to investigate the physicochemical properties of vasopressin V2 receptor (V2R) antagonist and predict the binding mode to V2R. The obtained quantitative structure-activity relationship (QSAR) model showed a correlation between antagonist activity and hydration energy, polarizability, and partial charge on atom N7 of the common substructure. The V2R was modeled and relaxed on a POPC membrane, and the receptor antagonist complexes were predicted by molecular docking. The stability of the relevant structures was evaluated by molecular dynamics simulations. Amino acid residues were identified as potentially important for antagonist-receptor interactions. The proposed QSAR model could explain the molecular properties relevant to antagonist activity and was consistent with the binding mode of the complexes obtained by docking and dynamics.