Quantitative structure-activity relationship of 2-alkyl-4-（biphenylylmethoxy） pyridine derivatives with AT1 receptor antagonistic activity

The quantitative structure-activity relationship (QSAR) of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives was studied. Three different alignment methods were used to get the models of the comparative molecular field analysis (CoMFA), the comparative molecular similarity indices analysis (CoMSIA), and the hologram quantitative structure-activity relationship (HQSAR). The statistical results from the established models show believable predictivity based on the cross-validated value (q ²>0.5) and the non-validated value (r ²>0.9). The analysis on contour maps of CoMFA and CoMSIA models suggests that hydrophobic and hydrogen-bond acceptor fields are important factors that affect the AT1 antagonistic activity of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives besides the steric and electrostatic fields. The structural modification information from different atom contributions in the HQSAR model is in agreement with that in the 3D-QSAR models.     

HEPT类HIV-1逆转录酶衍生物的CoMFA、CoMSIA及HQSAR研究

采用比较分子力场分析法（CoMFA）、比较分子相似因子分析法（CoMSIA）和分子全息定量结构关系（HQSAR）对1-[(2-羟乙氧)甲基]-6-苯硫基胸腺嘧啶(HEPT)类衍生物进行了分子活性构象选择、分子叠合、空间力场范围建立以及相应3D-QSAR模型建立。结果表明，该法所建模型对此类化合物具有良好的预测能力。CoMFA模型显示，交叉验证系数（q2）为0.565，非交互验证系数（r2）为0.892；CoMSIA模型显示，最佳q2为0.636， r2为0.953；最佳的HQSAR模型显示， q2为0.876， r2为0.929，最佳全息长度为97。根据三维等势图和HQSAR色码图设计了7个有较高活性的HEPT类化合物。     

Hologram QSAR Models of a Series of 6-Arylquinazolin-4-Amine Inhibitors of a New Alzheimer’s Disease Target: Dual Specificity Tyrosine-Phosphorylation-Regulated Kinase-1A Enzyme

Dual specificity tyrosine-phosphorylation-regulated kinase-1A (DYRK1A) is an enzyme directly involved in Alzheimer’s disease, since its increased expression leads to β-amyloidosis, Tau protein aggregation, and subsequent formation of neurofibrillary tangles. Hologram quantitative structure-activity relationship (HQSAR, 2D fragment-based) models were developed for a series of 6-arylquinazolin-4-amine inhibitors (36 training, 10 test) of DYRK1A. The best HQSAR model (q² = 0.757; SE_cv = 0.493; R² = 0.937; SE = 0.251; R²pred = 0.659) presents high goodness-of-fit (R² > 0.9), as well as high internal (q² > 0.7) and external (R²pred > 0.5) predictive power. The fragments that increase and decrease the biological activity values were addressed using the colored atomic contribution maps provided by the method. The HQSAR contribution map of the best model is an important tool to understand the activity profiles of new derivatives and may provide information for further design of novel DYRK1A inhibitors.