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Exploring the Ligand Recognition Properties of the Human Vasopressin V1a Receptor Using QSAR and Molecular Modeling Studies by: Dr. Omar Deeb

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Field of Research:   Pharmacology
Name of author and co-authors on the published work; Martha C. Contreras-Romo,  Marlet Martınez- Archundia, Omar Deeb, Magdalena J. Slusarz, Gema Ramırez-Salinas, Ramon Garduno-Juarez, Andres Quintanar-Stephano, Guillermo Ramırez-Galicia and Jose Correa-Basurto
Name of Journal or Book:    Chemical Biology and Drug Design
Journal Impact Factor:   2.485
# of Pages, from :   to:   207-223
Year:  2014
Journal volume:  83
Publisher’s name and address:  John Wiley & Sons

Abstract of Published work: 

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 compounds). 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 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.

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