6533b7d0fe1ef96bd125a3f3

RESEARCH PRODUCT

Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification

Francisco TorrensRamón García-domenechJuan A. Castillo-garitJ. Enrique Rodríguez-borgesYovani Marrero-ponceYovani Marrero-ponce

subject

Quantitative structure–activity relationshipTheoretical computer scienceComputer scienceChemistryOrganic ChemistryComparabilityComputer Science ApplicationsData setSet (abstract data type)Quadratic equationComputational chemistryDrug DiscoveryMolecular symmetryBenchmark (computing)Trigonometry

description

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 nonstochastic and stochastic bond-based 3D-chiral quadratic indices appear to provide a rather interesting alternative to other more common 3D-QSAR descriptors.

https://doi.org/10.1002/qsar.200960085