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PLS regression and CoMFA

As an illustration of PLS regression (PLSl) we reconsider the inhibitory potencies of oxidative phosphorylation of 11 doubly substituted salicylanilides [ 17] in Table 37.1. An extended Hansch model is defined by the linear free energy relation  [Pg.410]

The most predictive PLS regression model for these data makes use of two PLS-components  [Pg.410]

The selection of the number of PLS-components to be included in the model was done according to the PRESS criterion (Section 36.3). Note that the result is comparable to the one which we obtained earlier by means of the simple Hansch analysis (Section 37.1.1). Hence, in this case, there is no obvious benefit to include a quadratic term of log P in the model. [Pg.410]

It has been shown that PLS regression fits better to the observed activities than principal components regression [53]. The method is non-iterative and, hence, is relatively fast, even in the case of very large matrices. [Pg.410]

A group of compounds is selected which possess a common three-dimensional pharmacophore, i.e. a configuration of chemical groups that presumably interact with the target receptor or enzyme. The compounds are then aligned in space by translation and rotation, for example on the basis of their similarity with a known [Pg.410]


See other pages where PLS regression and CoMFA is mentioned: [Pg.409]   


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