黄酮类化合物对P糖蛋白外泵作用的抑制效果越来越引起人们的关注.使用偏最小二乘法(PLS)和M o lconnZ分子参数计算程序,首次成功地构建了特异性地结合到P糖蛋白NBD 2位点的黄酮类抑制剂的二维定量构效关系(2D-Q SAR)模型.所得到的模型(尤其是模型D)表现出良好的可靠性和预测性,较好地关联了该类化合物结构特点和其对P糖蛋白抑制活性.这些模型对进一步合成和开发黄酮类P糖蛋白抑制剂有指导作用.
The purpose of this work is to illustrate the relationship between genotype and phenotype in the complex cellular network of saccharomyces cerevisiae. As a structure-oriented method, using elementary flux mode(EFM) analysis can obtain its popularity in analysis of the robustness of the central metabolism, as well as network function of some organisms. However, this method has not been widely used for modeling gene deletion phenotype. By enumerating all the metabolic pathways, the EFM analysis presented herein can be used to identify the functional features and predict the growth phenotype of the S.cerevisiae. In comparison with the flux balance analysis(FBA), the performance of EFM analysis was superior to FBA in prediction of gene deletion phenotype. EFM analysis is demonstrated to be an effective tool for bridging the gap between metabolic network and growth phenotype.
