title: Exploring the ligand recognition properties of the human vasopressin V1a receptor using QSAR and molecular modeling studies.
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.
authors.affiliation: Departamento de Fisiología y Farmacología, Centro de Ciencias Básicas, Universidad Autónoma de Aguascalientes, Av. Universidad 940, 20131, Aguascalientes, México.
authors.forename: Martha C
authors.initials: MC
authors.lastname: Contreras-Romo
authors.forename: Marlet
authors.initials: M
authors.lastname: Martínez-Archundia
authors.forename: Omar
authors.initials: O
authors.lastname: Deeb
authors.forename: Magdalena J
authors.initials: MJ
authors.lastname: Slusarz
authors.forename: Gema
authors.initials: G
authors.lastname: Ramírez-Salinas
authors.forename: Ramón
authors.initials: R
authors.lastname: Garduño-Juárez
authors.forename: Andrés
authors.initials: A
authors.lastname: Quintanar-Stephano
authors.forename: Guillermo
authors.initials: G
authors.lastname: Ramírez-Galicia
authors.forename: José
authors.initials: J
authors.lastname: Correa-Basurto
mesh_terms: D065092:Antidiuretic Hormone Receptor Antagonists; D001569:Benzodiazepines / Q000737:chemistry; D001665:Binding Sites; D006801:Humans; D057927:Hydrophobic and Hydrophilic Interactions; D008024:Ligands; D062105:Molecular Docking Simulation; D016571:Neural Networks, Computer; D017434:Protein Structure, Tertiary; D021281:Quantitative Structure-Activity Relationship; D017483:Receptors, Vasopressin / Q000378:metabolism*
chemical_list: D065092:Antidiuretic Hormone Receptor Antagonists; D008024:Ligands; D017483:Receptors, Vasopressin; D001569:Benzodiazepines
keywords: MD simulations; QSAR studies; V1aR; docking; vaptans