张小轶, 侯琤斐, 邱木子, 杜晓艳, 王存新. 基于改进的CoMFA方法研究新生霉素抑制剂的定量构效关系[J]. 北京工业大学学报, 2017, 43(12): 1865-1871. DOI: 10.11936/bjutxb2017040047
    引用本文: 张小轶, 侯琤斐, 邱木子, 杜晓艳, 王存新. 基于改进的CoMFA方法研究新生霉素抑制剂的定量构效关系[J]. 北京工业大学学报, 2017, 43(12): 1865-1871. DOI: 10.11936/bjutxb2017040047
    ZHANG Xiaoyi, HOU Chengfei, QIU Muzi, DU Xiaoyan, WANG Cunxin. QSAR Research of Novobiocin Inhibitors Based on Modified CoMFA[J]. Journal of Beijing University of Technology, 2017, 43(12): 1865-1871. DOI: 10.11936/bjutxb2017040047
    Citation: ZHANG Xiaoyi, HOU Chengfei, QIU Muzi, DU Xiaoyan, WANG Cunxin. QSAR Research of Novobiocin Inhibitors Based on Modified CoMFA[J]. Journal of Beijing University of Technology, 2017, 43(12): 1865-1871. DOI: 10.11936/bjutxb2017040047

    基于改进的CoMFA方法研究新生霉素抑制剂的定量构效关系

    QSAR Research of Novobiocin Inhibitors Based on Modified CoMFA

    • 摘要: 为了改善药物开发过程中由于候选分子类药性差而导致药物开发失败的现状,通过克服比较分子场分析(CoMFA)自身描述符的局限性,对70个新生霉素小分子进行大量的描述符计算,每个小分子得到6 122个描述符,并对所得描述符进行筛选,将最终获得的4个关键描述符引入标准CoMFA模型中,以获得有助于判断目标小分子是否具有类药性的改进的CoMFA模型.结果显示,所得最优模型是同时添加了POS_05_-O-和极性可及面积(polar surface area,PSA)两个描述符的.通过对该改进的CoMFA模型进行统计分析,发现该模型的Q2Rncv2Rpre2均比标准CoMFA模型提高.所得模型的等高线图为分子改造提供了建议,并验证了模型的可靠性.分析POS_05_-O-和PSA描述符在70个小分子中的分布,发现有20个小分子既含有POS_05_-O-描述符,且PSA在90~110,占高活性分子的91%,表明这2个描述符的确有利于提高小分子活性,同时也有利于分子的口服生物利用度.

       

      Abstract: In order to reduce the high failure rate of drug development caused by the poor drug-like properties of candidate compounds, it is helpful to improving the limitation of the descriptors in CoMFA table. By calculating the descriptors of 70 novobiocin compounds, 6122 descriptors of per compound were obtained, while only 4 critical descriptors after screening were remained. Then by adding the screened descriptors into standard CoMFA models, the best modified model was obtained by adding descriptor POS_05_-O-and PSA simultaneously. The modified model exhibit satisfying results with higher Q2, Rncv2, Rpre2 than that of the standard CoMFA. Moreover, the contour maps suggest the improvement for compounds, and also verifies the reliability of the model. By analyzing the distribution of the descriptor POS_05_-O-and PSA in 70 compounds, the results show that there are 20 compounds containing the descriptor POS_05_-O-and with PSA from 90 to 110, which is 90% of the active compounds. This indicates that the two descriptors are indeed significant for improving compounds activities and bioavailability.

       

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