Multiway calibration in 3D QSAR

Abstract

We have introduced multilinear PLS in 3D QSAR and applied it to GRID descriptors from a set of benzamides with affinity to the dopamine D3 receptor subtype, synthesized as potential drugs against schizophrenia. The key issue in 3D QSAR modelling is to obtain a predictive model that is easy to interpret. Each component in the multilinear PLS model explains clearly defined details, e.g. substituent positions, while the bilinear PLS solution is general and more difficult to interpret. The best models were obtained after four components with multilinear PLS (Q2=51%) and after only one component with bilinear PLS (Q2=50%). The external test set was predicted better with multilinear PLS (Q2=31%) than with bilinear PLS (Q2=25%). With multilinear PLS one loses in fit and gains in stability and simplicity owing to the fewer parameters that need to be estimated as compared with bilinear PLS. Finally, multilinear PLS is also less influenced by insignificant variation in the descriptor block, which is an advantage in 3D QSAR modelling © 1997 John Wiley & Sons, Ltd.