Statistical models comparative molecular field analysis

We have evaluated three different techniques to generate QSAR models, namely Comparative Molecular Field Analysis (CoMFA), Comprehensive Descriptors for Structural and Statistical Analysis (CODESSA), and Hologram QSAR (HQSAR). More specifically they were evaluated for their utility (predictivity, speed, accuracy, and reproducibility) to predict ER binding activity quantitatively (Tong et al., 1998 Shi et al., 2001). Common to the three QSAR methods is the... 

The studies described above revealed that BE values can be reliable predictors of ligand binding affinities for target proteins. The BE value can also serve as an additional descriptor to supplement QSAR models. A recent example demonstrated that the statistical quality of a 3D-QSAR model based on comparative molecular field analysis (CoMFA) improved dramatically—from R2 = 0.65 to R2 = 0.93—by inclusion of calculated BE values [86,87]. 

Since drugs and their targets are three-dimensional objects, it is of course appropriate to consider 3D molecular propeities. This is the objective of several approaches, combining statistical and modelling techniques, referred to as 3D-QSAR. The comparative molecular field analysis (CoMFA) method has been widely used and will be discussed elsewhere in this book (see Chapter 25). 

Spherical harmonics provide a parameterization of three-dimensional shape which is especially useful for protein structure description (4). Overlap volume comparisons are the basis for the Molecular Shape Analysis (MSA) method of Hopfinger (5,6). TTiis technique has been extended to include a quantification of the steric and electrostatic fields surrounding a molecule (7). A further refinement of field analysis, which merges statistical and molecular modeling techniques, is the COMparative Molecular Field Analysis method (COMFA) of Cramer (8). These latter approaches seek to encode information about more than just steric bulk or form. They express multivariate information about the structure, so they might be considered multidimensional shape descriptors. 

Whereas such qualitative approaches are valuable, it would be useful if they could be augmented with techniques that quantitatively link the binding models with ligand binding data. Recent progress in QSAR methodology has provided tools to allow us to do just that. With the advances in statistical techniques applied to QSAR problems in the late 1980s," the technique of Comparative Molecular Field Analysis (CoMFA) was developed.The... 

Statistical characteristics of CMF models obtained for these data sets were compared with the same characteristics built for corresponding data sets using the common 3D-QSAR methods, CoMFA (Comparative Molecular Fields Analysis) [18] and CoMSIA (Comparative Molecular Similarity Index Analysis) [24], based on the use of molecular fields. Data on CoMFA and CoMSIA models were taken from Ref. [25]. 

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