Hologram Quantitative Structure-Activity Relationships Investigations of Non-nucleoside Reverse Transcriptase Inhibitors

Pornpan      Pungpo; Supa      Hannongbua; Peter      Wolschann

doi:10.2174/0929867033457106

Abstract

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) such as TIBO, HEPT and dipyridodiazepinone are effective against HIV-1 RT. These NNRTIs are chemically and structurally diverse, but they all bind to a common allosteric site of HIV-1 RT. These inhibitors exhibit high potency, low cytotoxicity and produce few side effects. However, the emergency of drug-resistance viral strain has limited the therapeutic efficiency of the NNRTIs. Several different QSAR studies were reported to identify important structural features responsible for the inhibitory activity of these NNRTIs. In this study, hologram quantitative structure-activity relationships (HQSAR) was applied to three different data sets, 70 TIBO, 101 HEPT and 125 dipyridodiazepinone derivatives. Starting geometries of compounds were taken from available X-ray crystallographic data. Modification and full geometry optimization of all derivatives were performed, based on quantum chemical calculations at the HF / 3-21G level of theory. All derived HQSAR models produce satisfying predictive ability and yield r2 cv values ranging from 0.62-0.84. Moreover, it was also found that the quality of models enhances as the size of fragments increases. The obtained HQSAR results indicate the similarity of the interactions of these three different NNRTIs with the inhibition pocket of the enzyme. Comparisons of different QSAR methods on these NNRTIs data sets were also considered and it could be shown that HQSAR results yield superior predictive models than other 2D-QSAR approaches. In particular, the predictive ability of the models derived from dipyridodiazepinone analogues was significantly improved and apparently revealed differentiating structural requirements between WT and Y181C HIV RT inhibition. Additionally, the quality of QSAR models constructed by CoMFA and HQSAR methods are comparable and the interpretations of the models reinforce each other. It suggests an advantage of HQSAR as a useful tool in designing new potent inhibitors with enhanced HIV-1 RT inhibition activity, especially against mutant enzyme.

Keywords: hqsar, reverse transcriptase inhibitors, tibo, hept, dipyridodiazepinone, quantum chemical calculations

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