Journal
QSAR & COMBINATORIAL SCIENCE
Volume 28, Issue 11-12, Pages 1465-1477Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/qsar.200960085
Keywords
Nonstochastic and stochastic bond-based 3D-chiral quadratic indices; 3D-QSAR; Angiotesin-converting enzyme inhibitor; sigma-Receptor antagonist; Binding affinity steroid; Environmental chemistry; Bioinformatics
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Funding
- Fondo de Investigacion Sanitaria, Ministerio de Sanidad, Spain [SAF2005-PI052128]
- Spanish MEC [CTQ2004-07768-C02-01/BQU, CCT-005-0700365]
- EU (Program FEDER)
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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 sigma-stereoisorners 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 sigma-receptors. The validation of this method is achieved by comparison with earlier publications applied to the same data sets. The nonstochastic and stochastic bond-based 3D-chiral quadratic indices appear to provide a rather interesting alternative to other more common 3D-QSAR descriptors.
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