Activity prediction models three-dimensional QSAR

For quantitative structure-activity relationship (QSAR) studies a three-dimensional model of a DNA-quinoIone complex was built using molecular modeling techniques. It was based on the intercalation of quinolone into the double helix of DNA. It was concluded that the intercalation model is consistent with most available data on the structure of the quinolone complex. This predicted... 

Hansch analysis and other classical QSAR approaches evaluate the QSAR model based on the correlation of rows of compounds with known activities (dependent variables) to columns of parameters (independent variables). For this reason, classical QSAR is sometimes called 2D QSAR. CoMFA is an example of 3D QSAR because lead analogues are modeled and analyzed in a virtual three-dimensional space. The value of both methods ultimately hinges on how well experimental and calculated activities correlate (Figure 12.2) and how well the model predicts the activity of compounds not included in the training set. 

The next step was made by Klebe et al. [50]. Two 3D-QSAR methods were applied to get three-dimensional quantitative structure-activity relationships using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities toward Factor Xa to yield statistically reliable models of good predictive power [51-54] the widely used CoMFA method (for steric and electrostatic properties) and the comparative molecular similarity index analysis (CoMSlA) method (for steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor properties). These methods allowed the consideration of various physicochemical properties, and the resulting contribution maps could be intuitively interpreted. 

Yu SJ, Keenan SM, Tong W, Welsh WJ. Influence of the structural diversity of data sets on the statistical quality of three-dimensional quantitative structure-activity relationship (3D-QSAR) models predicting the estrogenic activity of xenoestrogens. Chem Res Toxicol 2002 15 1229-34. 

Akahori Y, Nakai M, Yakabe Y, Takatsuki M, Mizutani M, Matsuo M, et al. Two-step models to predict binding affinity of chemicals to the human estrogen receptor a by three-dimensional quantitative structure-activity relationships (3D-QSARs) using receptor-ligand docking simulation. SAR QSAR Environ Res 2005 16 323-37. 

In addition, traditional quantitative structure-activity relationship (QSAR) models were reported. Gozalbes et al. attempted to predict the blood-brain barrier permeabilities of four arylacetamides using linear discriminant analysis [65], while Medina-Franco et al. discriminated between active and inactive BCG compounds using two-dimensional (2D) and three-dimensional (3D) structural-similarity methods [66]. 

Apex-3D is an expert system for investigating structure-activity relationships (SARs). The software is able to derive S AR and QSAR models for three-dimensional (3D) structures, which can be used for activity classification and prediction. The... 

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