Abstract
In this article, the application of Multivariate Adaptive Regression Splines (MARS) for modelling the biological activity of Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) is described. The studied data consist of the biological activities of 208 NNRTIs evaluated against wild-type HIV virus (HIV-1) and four mutant strains (181C, 103N, 100I, 188L), and the computed interaction energies with the amino acids forming the NNRTI binding pocket. The NNRTIs belong to five different chemical classes of compounds, known as HEPT-like, TIBO, DATA, DAPY and ITU compounds. The MARS model obtained for the biological activity of NNRTIs yields acceptable prediction errors for this data set.
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