Molecular descriptors partial least squares

After an alignment of a set of molecules known to bind to the same receptor a comparative molecular field analysis CoMFA) makes it possible to determine and visuahze molecular interaction regions involved in hgand-receptor binding [51]. Further on, statistical methods such as partial least squares regression PLS) are applied to search for a correlation between CoMFA descriptors and biological activity. The CoMFA descriptors have been one of the most widely used set of descriptors. However, their apex has been reached. 

Ekins et al. (163) used the rat ortholog 2B6 to generate a pharmacophore model and compared these findings with a partial least squares (PLS) model using MS-WHIM descriptors. The model was constructed using 16 B-lymphoblastoids and yielded a good cross-validated r2 of 0.607. The analysis included molecular surface properties (size) together with positive elec-... 

Partial least squares regression analysis (PLS) has been used to predict intensity of sweet odour in volatile phenols. This is a relatively new multivariate technique, which has been of particular use in the study of quantitative structure-activity relationships. In recent pharmacological and toxicological studies, PLS has been used to predict activity of molecular structures from a set of physico-chemical molecular descriptors. These techniques will aid understanding of natural flavours and the development of synthetic ones. 

Very recently, new descriptors have successfully been derived from 3-D molecular fields. These descriptors were correlated with the experimental permeation data by discriminant partial least-squares methods. The training set consisted of 44 compounds. The authors were able to deduce a simple mathematical model that allows external prediction. More than 90% of blood-brain permeation data were correctly predicted [77]. 

Although there is a strong negative correlation between partition coefficient and aqueous solubility (Hansch et al., 1968 Chiou et al., 1977), and a strong positive correlation between % and molecular volume (Dearden et al., 1988), the use of the partial least squares (PLS) method in this study allows the simultaneous use of intercorrelated descriptors. Nevertheless, the use of four descriptors to model the bioconcentration factor of only 11 compounds contravenes the Topliss and Costello (1972) rule, and renders the QSAR of dubious validity. 

Kim, K.H. and Martin, Y.C. (1991c). Evaluation of Electrostatic and Steric Descriptors for 3D-QSAR the H and CH3 Probes Using Comparative Molecular Field Analysis (CoMFA) and the Modified Partial Least Squares Method. In QSAR Rational Approaches to the Design of Bioactive Compounds (Silipo, C. and Vittoria, A., eds.), Elsevier, Amsterdam (The Netherlands), pp. 151-154. 

Partial least squares (PLS) is similar to MLR in that it also assumes a linear relationship between a vector x and a target property y. However, it avoids the problems of collinear descriptors by calculating the principal components for the molecular descriptors and target property separately. The scores for the molecular descriptors are used as the feature vector x and are also used to predict the scores for the target property, which can in turn be used to predict y. An important consideration in PLS is the appropriate number of principal components to be used for the QSAR model. This is usually determined by using cross-validation methods like fivefold cross validation and leave-one-out. PLS has been applied to the prediction of carcinogenicity [19], fathead minnow toxicity [20], Tetrahymena pyriformis toxicity [21], mammalian toxicity [22], and Daphnia magna toxicity [23],... 

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