Exploring the ligand recognition properties of the human vasopressin V1a receptor using QSAR and molecular modeling studies.
Chem Biol Drug Des
; 83(2): 207-23, 2014 Feb.
Article
in En
| MEDLINE
| ID: mdl-24010681
ABSTRACT
Vaptans are compounds that act as non-peptide vasopressin receptor antagonists. These compounds have diverse chemical structures. In this study, we used a combined approach of protein folding, molecular dynamics simulations, docking, and quantitative structure-activity relationship (QSAR) to elucidate the detailed interaction of the vasopressin receptor V1a (V1aR) with some of its blockers (134). QSAR studies were performed using MLR analysis and were gathered into one group to perform an artificial neural network (ANN) analysis. For each molecule, 1481 molecular descriptors were calculated. Additionally, 15 quantum chemical descriptors were calculated. The final equation was developed by choosing the optimal combination of descriptors after removing the outliers. Molecular modeling enabled us to obtain a reliable tridimensional model of V1aR. The docking results indicated that the great majority of ligands reach the binding site under π-π, π-cation, and hydrophobic interactions. The QSAR studies demonstrated that the heteroatoms N and O are important for ligand recognition, which could explain the structural diversity of ligands that reach V1aR.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Receptors, Vasopressin
/
Quantitative Structure-Activity Relationship
/
Molecular Docking Simulation
Limits:
Humans
Language:
En
Journal:
Chem Biol Drug Des
Journal subject:
BIOQUIMICA
/
FARMACIA
/
FARMACOLOGIA
Year:
2014
Document type:
Article