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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/16523

    Title: Key Features for Designing Phosphodiesterase-5 Inhibitors
    Authors: ;Chang, Tung-Ti;Huang, Hung-Jin;李桂仁;Lee, Kuei-Jen;Yu, Hsin Wei;Chen, Hsin-Yi;蔡輔仁;Tsai, Fuu-Jen;Sun, Mao-Feng;陳語謙;Chen, Calvin Yu-Chian
    Contributors: 生物科技學系
    Keywords: Phosphodiesterase-5;Nitric oxide;Comparative molecular field analysis (CoMFA);Comparative molecular similarity indices analysis (CoMSIA);Docking;Traditional Chinese medicine (TCM)
    Date: 2010-12
    Issue Date: 2012-11-23 17:14:12 (UTC+8)
    Abstract: "Phosphodiesterase superfamily is the key regulator of 3′,5′-cyclic guanosine monophosphate (cGMP) decomposition in human body. Phosphodiesterase-5 (PDE-5) inhibitors, sildenafil, vardenafil and tadalafil, are well known oral treatment for males with erectile dysfunction. To investigate the inhibitory effects of traditional Chinese medicine (TCM) compounds to PDE-5, we performed both ligand-based and structure-based studies on this topic. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted to construct three dimensional quantitative structure-activity relationship (3D-QSAR) models of series of known PDE-5 inhibitors. The predictive models had cross-validated, q2, and non cross-validated coefficient, r2, values of 0.791 and 0.948 for CoMFA and 0.724 and 0.908 for CoMSIA. These two 3D-QSAR models were used to predict activity of TCM compounds. Docking simulations were performed to further analyze the binding mode of training set and TCM compounds. A putative binding model was proposed based on CoMFA and CoMSIA contour maps and docking simulations; formation of pi-stacking, water bridge and specific hydrogen bonding were deemed important interactions between ligands and PDE-5. Of our TCM compounds, engeletin, satisfied our binding model, and hence, emerged as PDE-5 inhibitor candidate.

    Using this study as an example, we demonstrated that docking should be conducted for qualitative purposes, such as identifying protein characteristics, rather than for quantitative analyses that rank compound efficacy based on results of scoring functions. Prediction of compound activity should be reserved for QSAR analyses, and scoring functions and docking scores should be used for preliminary screening of TCM database
    Appears in Collections:[生物科技學系] 期刊論文

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