QSAR Studies of HEPT Derivatives Using Support Vector Machines

Abstract

Abstract 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 structure‐activity relationship studies. The contribution of each descriptor to the structure‐activity relationships was evaluated.