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Development and validation of hydrophobic molecular fields derived from the quantum mechanical IEF/PCM-MST solvation models in 3D-QSAR.

Authors :
Ginex, Tiziana
Muñoz‐Muriedas, Jordi
Herrero, Enric
Gibert, Enric
Cozzini, Pietro
Luque, F. J.
Source :
Journal of Computational Chemistry; May2016, Vol. 37 Issue 13, p1147-1162, 16p
Publication Year :
2016

Abstract

Since the development of structure-activity relationships about 50 years ago, 3D-QSAR methods belong to the most refined ligand-based in silico techniques for prediction of biological data using physicochemical molecular fields. In this scenario, this study reports the development and validation of quantum mechanical (QM)-based hydrophobic descriptors derived from the parametrized MST continuum solvation model to be used in 3D-QSAR studies within the framework of the Hydrophobic Pharmacophore (HyPhar) method. To this end, five sets of compounds reported in the literature (dopamine D2/D4 antagonists, antifungal 2-aryl-4-chromanones, and inhibitors of GSK-3, cruzain and thermolysin) have been revisited. The results derived from the QM/MST-based hydrophobic descriptors have been compared with previous CoMFA and CoMSIA studies, and examined in light of the available X-ray crystallographic structures of the targets. The analysis reveals that the combination of electrostatic and nonelectrostatic components of the octanol/water partition coefficient yields pharmacophoric models fully comparable with the predictive potential of standard 3D-QSAR techniques. Moreover, the graphical representation of the hydrophobic maps provides a direct linkage with the pattern of interactions found in crystallographic structures. Overall, the introduction of the QM/MST-based descriptors, which could be easily adapted to other continuum solvation formalisms, paves the way to novel computational strategies for disclosing structure-activity relationships in drug design. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01928651
Volume :
37
Issue :
13
Database :
Complementary Index
Journal :
Journal of Computational Chemistry
Publication Type :
Academic Journal
Accession number :
114641968
Full Text :
https://doi.org/10.1002/jcc.24305