Hansch analysis CoMFA

The same assumptions apply to CoMFA as to ordinary Hansch analysis. These are additivity of effects and the availability of structurally similar (congeneric) molecules. The method does not account for pharmacokinetic effects, such as distribution, elimination, transport and metabolization. A prospective drug may appear to bind well to the receptor or enzyme, but may not reach the target site due to undesirable pharmacokinetic properties [8]. 

Comparative molecular field analysis (CoMFA) is a modern, powerful extension of the classical QSAR methods that were developed in the 1960s.14 While Hansch analysis is simple to understand and fairly easy for any medicinal chemist to perform, CoMFA requires specialized software and an understanding of statistics. Since CoMFA is outside the experience of most synthetic chemists, pharmaceutical companies have dedicated computational chemistry groups to handle advanced QSAR tasks. 

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 following Case Study demonstrates how Hansch analysis and CoMFA can both correlate the same structure-activity data. CoMFA, however, can more easily be extended to include a broad range of structural variations. 

In 1993, Martin and colleagues performed a follow-up study on the same 15 compounds using CoMFA. CoMFA does not produce a simple equation in the manner of Hansch analysis, but CoMFA does calculate activities for the training set compounds. Comparing the predicted and experimental activities allows determination of the model s correlation coefficient. The CoMFA performed by Martin gave an r-value of 0.96. Martin s CoMFA model accounted... 

The data in Table 12.8 do not represent a resounding victory for CoMFA over Hansch analysis. However, a significant advantage of CoMFA is its flexibility. Martin continued his study by including an additional 30 compounds in his CoMFA model. The additional compounds are analogous to 12,18 but contain significantly more structural variability with R-group modifications at C-2,... 

Debnath, A.K., Hansch, C., Kim, K.H., and Martin, Y.C., Mechanistic interpretation of the genotoxicity of nitrofurans (antibacterial agents) using quantitative structure-activity relationships (QSAR) and comparative molecular field analysis (CoMFA), J. Med. Chem., 36, 1009-1116, 1993. 

The seminal work of Corwin Hansch initiated the field of QSAR. Two-dimensional and three-dimensional QSAR methods (2-D QSAR and 3-D QSAR) have been widely applied to problems of biological interest. The latter approach has increased in popularity with the introduction of the comparative molecular field analysis (CoMFA) and commercial availability of similar methods. 

The early use of 2D parameters and scalar values was described by Leo, Hansch, and Elkins [1] and has been predominately replaced with more rigorous fragment-based techniques and 3D-QSAR techniques. The fragment-based techniques are exemplified by HQSAR [2] while the most successful of the 3D-QSAR techniques is Comparative Molecular Field Analysis (CoMFA) [3]. 

The interactions of drugs with their biological counterparts are determined by intermolecular forces, i.e. by hydrophobic, polar, electrostatic, and steric interactions. Quantitative structure-activity relationships (QSAR) derive models which describe the structural dependence of biological activities either by physicochemical parameters (Hansch analysis), by indicator variables encoding different structural features (Free Wilson analysis), or by three-dimensional molecular property profiles of the compounds (comparative molecular field analysis, CoMFA). 

QSARs include statistical methods to relate biological activities (most often expressed by logarithms of equipotent molar activities) with structural elements (Free Wilson analysis), physicochemical properties (Hansch analysis), or fields (3D QSAR). The parameters used in a QSAR model are also called (molecular) descriptors. Classical QSAR analyses (Hansch and Free Wilson analyses) consider only 2D structures. Their main field of application is in substituent variation of a common scaffold. 3D-QSAR analysis (CoMFA) has a much broader scope. It starts from 3D structures and correlates biological activities with 3D-property fields (McKinney et al. 2000). 

A. K. Debnath, C. Hansch, K. H. Kim, and Y. C. Martin,/. Med. Chem., 36, 1007 (1993). Mechanistic Interpretation of the Genotoxicity of Nitrofurans as Antibaaerial Agents Using Quantitative Structure-Activity Relationships (QSAR) and Comparative Molecular Field Analysis (CoMFA). 

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