N-(4-取代嘧啶-2-基)苄基磺酰脲和苯氧基磺酰脲的3D-QSAR研究

采用比较分子力场分析(CoMFA)方法,对两类单取代嘧啶类似物、6个N-(4-取代嘧啶-2-基)-2-甲氧羰基苄基磺酰脲(1a～1f)和14个N-(4-取代嘧啶-2-基)-2-取代苯氧基磺酰脲(2a～2n)进行三维定量构效关系(3D-QSAR)研究.建立了一个较为可靠的预测模型.结果表明,分子中苯环邻位、嘧啶环形成氢键的N原子处以及嘧啶环4位和6位附近负电荷增加;苯环邻位乙氧基的CH₂CH₃附近选择带正电的原子;苯环邻位乙氧基附近空间体积增加,而嘧啶环4位甲氧基稍远处取代基的立体位阻不超过此位置,将有利于提高活性.最后解释了修饰磺酰脲的除草剂仍具有较高活性的原因.     

3D-QSAR Studies of Dimethoxyphenoxyphenoxy pyrimidines and Analogues

1　 INTRODUCTIONPhotosynthesis is special and important physiology and biochemistry phe-nomenon for plant,so itisnecessary to selectphotosynthesis as a herbicidal targetinorder to get nontoxic pesticides. Recently,a number of 6 - ( 4- phenoxyphenoxy)pyrimidines and triazines which showed a strong Hill reaction inhibition were synthe-sized and their herbicidal activity was measured〔1〕. General structural formulas ofthese compounds are shown in Table1 .In this paper,we examined the three…     

QSAR and Pharmacophore Studies of Thiazolidine-4-carboxylic Acid Derivatives as Novel Influenza Neuraminidase Inhibitors Using HQSAR, Topomer CoMFA and CoMSIA

In order to understand the chemical-biological interactions governing their activities toward neuraminidase (NA), QSAR models of 28 thiazolidine-4-carboxylic acid derivatives with inhibitory influenza A virus were developed. The obtained HQSAR (hologram quantitative structure activity relationship), Topomer CoMFA and CoMSIA (comparative molecular similarity indices analysis) models were robust and had good exterior predictive capabilities. Moreover, QSAR modeling results elucidated that hydrogen bonds highly contributed to the inhibitory activity, then electrostatic and hydrophobic factors. Squared multiple correlation coefficients (R2) of HQSAR, Topomer CoMFA and CoMSIA models were 0.994, 0.978 and 0.996, respectively. Squared cross-validated correlation coefficients (Q2) of HQSAR, Topomer CoMFA and CoMSIA models were in turn 0.951, 919 and 0.820. Furthermore, squared multiple correlation coefficients for the test set (R2test) of HQSAR, CoMFA and CoMSIA models were 0.879, 0.912 and 0.953, respectively. Squared cross-validated correlation coefficients for the test set (Q2ext) of HQSAR, Topomer CoMFA and CoMSIA models were 0.867, 0.884 and 0.899, correspondingly.     

Triple-layered QSAR studies on substituted 1,2,4-trioxanes as potential antimalarial agents: superiority of the quantitative pharmacophore-based alignment over common substructure-based alignment

This study reports the utilization of three approaches – pharmacophore, CoMFA/CoMSIA and HQSAR studies – to identify the essential structural requirements in 3D chemical space for the modulation of the antimalarial activity of substituted 1,2,4-trioxanes. The superiority of quantitative pharmacophore-based alignment (QuantitativePBA) over global minima energy conformer-based alignment (GMCBA) has been reported in CoMFA and CoMSIA studies. The developed models showed good statistical significance in internal validation (q ², group cross-validation and bootstrapping) and performed very well in predicting the antimalarial activity of test set compounds. Structural features in terms of their steric, electrostatic and hydrophobic interactions in 3D space have been found to be important for the antimalarial activity of substituted 1,2,4-trioxanes. Further, the HQSAR studies based on the same training and test set acted as an additional tool to find the sub-structural fingerprints of substituted 1,2,4-trioxanes for their antimalarial activity. Together, these studies may facilitate the design and discovery of new substituted 1,2,4-trioxanes with potent antimalarial activity.     

Insight into the Structural Requirements of Protoporphyrino- gen Oxidase Inhibitors： Molecular Docking and CoMFA of Di- phenyl Ether, Isoxazole Phenyl, and Pyrazole Phenyl Ether

Protoporphyrinogen oxidase （PPO, EC 1.3.3.4） is one of the most significant targets for a large family of in- hibitors that may be used as herbicide, bactericide, fungicide, or photosensitizing activator to treat cancer through photodynamic therapy （PDT）. Molecular docking and CoMFA were combined in a multistep framework with the ultimate goal of identifying important factor contributing to the activity of PPO inhibitors. As a continuation of the previous research work on the development of new PPO inhibitors, the bioassay results indicated that good PPO in- hibitors were discovered in all of the three chemical series with ICs0 values ranging from 0.010 to 0.061 pmol·L ^-1. Using the crystal structure of tobacco mitochondrial PPO （mtPPO） as template, all the compounds were docked into the enzyme active site. The docking pose of each compound was subsequently used in a receptor-based alignment, leading to the development of a significant CoMFA model with r^2 value of 0.98 and q^2 （cross validation r^2） value of 0.63. This novel multistep framework gives insight into the and it can be extended to other classes of PPO inhibitors. In be particularly applicable in virtual screening procedures. structural characteristics for the binding of inhibitors, addition, the simplicity of the proposed approach may     

QSAR studies on hepatitis C virus NS5A protein tetracyclic inhibitors in wild type and mutants by CoMFA and CoMSIA

ABSTRACT

Several 3D-QSAR models were built based on 196 hepatitis C virus (HCV) NS5A protein inhibitors. The bioactivity values EC₉₀ for three types of inhibitors, the wild type (GT1a) and two mutants (GT1a Y93H and GT1a L31V), were collected to build three datasets. The programs OMEGA and ROCS were used for generating conformations and aligning molecules of the dataset, respectively. Each dataset was randomly divided into a training set and a test set three times to reduce the contingency of only one random selection. QSAR models were computed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the datasets GT1a, GT1a Y93H, and GT1a L31V, the best models CoMFA-INDX, CoMSIA-SEHA, and CoMSIA-SEHA showed an r² value of 0.682 ± 0.033, 0.779 ± 0.036, and 0.782 ± 0.022 on the test sets, respectively. From the contour maps of the three best models, we summarized the favourable and unfavourable substituents on the tetracyclic core, the Z group, the proline group, and the valine group of inhibitors. We guessed the mutants could change the electrostatic surfaces of the wild type active pocket. In addition, we used ECFP analyses to find important substructures and could intuitively understand the results from QSAR models.     

Design,synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II–AT1 receptor antagonists based on predictive 3D QSAR models

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII–AT₁ receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII–AT₁ receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q²) of 0.630 and 0.623, respectively, cross-validated coefficients (r²_cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r²) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r²_pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT₁ receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II–AT₁ receptor antagonism.