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A quantitative structure-activity relationship (QSAR) study is suggested for the prediction of anti-HIV activity of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives. The model was produced by using the support vector machine (SVM) technique to develop quantitative relationships between the anti-HIV activity and ten molecular descriptors of 89 TIBO derivatives. The performance and predictive capability of the SVM method were investigated and compared with other techniques such as artificial neural networks and multiple linear regression. The results obtained indicate that the SVM model with the kernel radial basis function can be successfully used to predict the anti-HIV activity of TIBO derivatives with only ten molecular descriptors that can be calculated directly from only molecular structure. The contribution of each descriptor to the structure-activity relationships was evaluated. Hydrophobicity of the molecule was thus found to take the most relevant part in the molecular description.

Human Immunodeficiency Virus type 1 reverse transcriptase is an important target for chemotherapeutic agents against the AIDS disease. 1-[2-Hydroxyethoxy-methyl]-6-(phenylthio) thymine] derivatives are potent nonnucleoside reverse transcriptase inhibitors. In the present work, quantitative structure-activity relationship analysis for a set of 79 HEPT derivatives has been investigated by means of support vector machines. The relationships between structure and activity were examined quantitatively using descriptors encoding the steric, hydrophobic, electronic and structural features of 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine] derivatives. The performance and predictive capability of support vector machines method are investigated and compared with other methods such as artificial neural network and multiple linear regression methods. The obtained results indicate that the support vector machines model with the kernel radial basis function can be employed as a forceful tool for quantitative structureactivity relationship studies. The contribution of each descriptor to the structure-activity relationships was evaluated.