Sobańska Anna W, Żydek Grażyna, Włodno Piotr, Brzezińska Elżbieta
Department of Analytical Chemistry, Medical University of Lodz, Poland.
Department of Analytical Chemistry, Medical University of Lodz, Poland.
Eur J Med Chem. 2015 Jan 7;89:147-55. doi: 10.1016/j.ejmech.2014.10.045. Epub 2014 Oct 16.
211 compounds containing a benzodiazepine moiety (BZD) and belonging to 4 groups of different biological activity (H - inhibitors of reverse transcriptase of HIV-I virus, A - antiarrhythmic agents, G - ligands of benzodiazepine receptor in GABAergic system and C - cholecystokinin receptor antagonists) were subjected to structure-activity relationship (SAR) analysis. SAR investigations of all 211 BZD were based on Discriminant Function Analysis (DFA) of physicochemical data connected with BBB (blood-brain barrier) permeability of studied compounds. DFA was performed with STATISTICA 10.0 software by the stepwise method and resulted in 3 discriminant functions whose quality was assessed by Wilk's lambda parameter. Calculated discriminant functions (roots) were applied to draw the scatter diagram of canonical values that showed all 211 cases divided into 4 groups of different biological activity. The method was successfully validated with a set of 38 BZD derivatives expected to belong to groups H, A, G and C. The reliability of the obtained model was confirmed with a cross-validation test. Classification functions presented in this study may be used as a practical tool for predicting new BZD drugs activity.
对211种含有苯二氮䓬部分(BZD)且属于4种不同生物活性组(H - HIV-1病毒逆转录酶抑制剂、A - 抗心律失常剂、G - GABA能系统中苯二氮䓬受体配体和C - 胆囊收缩素受体拮抗剂)的化合物进行了构效关系(SAR)分析。对所有211种BZD的SAR研究基于与所研究化合物的血脑屏障(BBB)通透性相关的物理化学数据的判别函数分析(DFA)。使用STATISTICA 10.0软件通过逐步法进行DFA,得到3个判别函数,其质量通过威尔克斯λ参数进行评估。应用计算出的判别函数(根)绘制典型值的散点图,该图显示所有211个案例分为4种不同生物活性组。该方法通过一组预期属于H、A、G和C组的38种BZD衍生物成功得到验证。通过交叉验证测试证实了所得模型的可靠性。本研究中呈现的分类函数可作为预测新型BZD药物活性的实用工具。