Support vector machine applied to predicting the activity of HIV-1 IN inhibitors - 文章详情页

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摘要：

HIV　integrase　(IN)　catalyzes　the　integration　process　in　the　viral　life　cycle.　IN　helps　the　viral　reverse　transcription　product　cDNA　integrating　into　the　host　chromosome.　As　an　indispensable　enzyme,　IN　is　also　an　important　target　for　designing　and　developing　the　novel　anti-HIV　drugs.　Constructing　the　QSAR　model　of　the　HIV-1　IN　pyrimidones　inhibitors　can　help　for　understanding　of　the　structural　factors.　In　this　paper,　the　CoMFA　software　was　used　to　calculate　topological　descriptors,　polarizable　descriptors　and　hydrophilic　descriptors　and　other　structural　parameters　for　68　compounds.　The　structural　parameters　were　selected　as　inputs　of　support　vector　machine　(SVM)　to　establish　the　non-linear　regression　model.　Results　show　that　the　SVM　algorithm　combined　with　QSAR　can　establish　the　forecasting　model　for　inhibitors,　and　provide　biological　information　for　the　design　of　anti-HIV　drugs.

关键词：

HIV-1 integrase inhibitors; Pyrimidones; Quantitative structure activity relationship (QSAR); Support vector machine (SVM)

作者机构：

[ 1 ] [Liu, X.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Tan, J.-J.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Chen, W.-Z.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Liu, B.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Li, S.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China
[ 6 ] [Wang, C.-X.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China

通讯作者信息：

[Wang, C.-X.]College of Life Science and Bio-Engineering, Beijing University of Technology, Beijing 100124, China

电子邮件地址：

cxwang@bjut.edu.cn

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