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Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification
* 1, 2, 3, 4 , 2, 4 , 4 , 3 , 5
1  Applied Chemistry Research Center, Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba
2  Unit of Computer-Aided Molecular “Biosilico” Discovery and Bioinformatic Research (CAMD-BIR Unit), Department of Pharmacy, Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba
3  Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, València, Spain
4  Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P. O. Box 22085, 46071 Valencia, Spain
5  Centro de Investigação em Química (UP), Departamento de Química, Faculdade de Ciências, Universidade do Porto, R. Campo Alegre, 687, P-4169-007 Porto, Portugal

Abstract: The concept of bond-based quadratic indices is generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design, we have modeled several well-known data sets. In particularly, Cramer's steroid data set has become a benchmark for the assessment of novel QSAR methods. This data set has been used by several researchers using 3D-QSAR approaches. Therefore, it is selected by us for the shake of comparability. In addition, to evaluate the effectiveness of this novel approach in drug design, we model the angiotensin-converting enzyme inhibitory activity of perindoprilate's σ-stereoisomers combinatorial library, as well as codify information related to a pharmacological property, highly dependent on the molecular symmetry, of a set of seven pairs of chiral N-alkylated 3-(3-hydroxyphenyl)-piperidines, which bind σ-receptors. The validation of this method is achieved by comparison with earlier publications applied to the same data sets. The non-stochastic and stochastic bond-based 3D-chiral quadratic indices appear to provide a rather interesting alternative to other more common 3D-QSAR descriptors.
Keywords: non-stochastic and stochastic bond-based 3D-chiral quadratic indices, 3D-QSAR, angiotesinconverting enzyme inhibitor, σ-receptor antagonist, binding affinity steroid
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