3D－QSAR Study on Diindolylmethane and Its Analogues with Comparative Molecular Field Analysis(CoMFA)

Comparative molecular field analysis (CoMFA),a three dimensional quantitative structure-activity relationship (3D-QSAR) method was applied to a series of diindolylmethane(DIM) analogs to study the relationship between their structure and their induction of CYP 1A1-associated ethoxyresorufin-O-deethylase(EROD) activity.A DISCO model of pharmacophore was derved to guide the superposition of the compounds.The coefficient of cross-validation (q^2) and non cross-validation(r^2) for the model established by the study are 0.827 and 0.988 respectively,the value of variance ratio (F) is 103.53 and standard error estimate (SEE)is 0.044.These values indicate that the CoMFA model derived is significant and might have a good prediction for the catalytic activity of DIM compounds.As a consequence,the predicted activity values of new designed compounds were all higher than that of the reported value.     

CoMFA 3D-QSAR Analysis of Epothilones Based on Docking Conformation and Alignment

Epothilones belong to a class of novel microtubule stabilizing and anti-mitotic agents, which have a paclitaxel-like mechanism of action. A three-dimensional quantitative structure-activity relationship （3D-QSAR） model was built for epothilones by the method of comparative molecular field analysis （CoMFA） combined with the flexible docking technology. The docking CoMFA model gave a good cross-validated value of q2=0.784 with an optimized component of 6 and the conventional correlation coefficient of r^2=0.985. The statistical results show that the model has good ability to predict the activity of the studied compounds. At last, the docking CoMFA model was analyzed through contour maps complemented with MOLCAD-generated active site potential surface in the α,β-tubulin receptor, which can provide important information for the structure-based drug design.     

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…     

靛玉红类CDK1抑制剂的同源模建、分子对接及3D-QSAR研究

细胞周期蛋白依赖性激酶1的异常表达会导致G2期的停滞及多种肿瘤的发生,故CDK1近年来已成为一个理想的治疗靶点. 本文以细胞分裂调控蛋白2的同源体为模板,同源模建了CDK1的结构,并与靛玉红类小分子抑制剂进行分子对接. 分别运用三种叠合方法进行分子叠合,并在此基础上采用Sybyl 7.1中的比较分子场分析(CoMFA)模块及Discovery Studio 3.0中的三维定量构效关系(3D-QSAR)模块(以下简称为DS)分别建立了3D-QSAR模型. 其中,将分子对接叠合与公共骨架叠合联合运用的叠合方法所得3D-QSAR模型的评价参数是最佳的(CoMFA：q²=0.681,r²=0.909,r_pred.²=0.836; DS：q²=0.579,r²=0.971,r_pred.²=0.795,其中q²为交叉验证系数,r²为非交叉验证系数). 本文的研究结果在对靛玉红类小分子进行结构修饰设计出新的CDK1抑制剂方面,可提供重要的理论基础.     

楝酰胺(Rocaglamide)类化合物的三维定量构效关系

采用比较分子力场分析(CoMFA)和比较分子相似因子分析(CoMSIA)方法,对训练集中的26个楝酰胺(Rocaglamide)类化合物进行了三维定量构效关系(3D-QSAR)研究,最终建立的CoMFA模型和CoMSlA模型的q<'2>分别为0.593和0.656.并对测试集中的5个化合物的生物活性进行了预测,结果表明...     

3D-QSAR study of hallucinogenic phenylalkylamines by using CoMFA approach

The three-dimensional quantitative structure–activity relationship (3D-QSAR) has been studied on 90 hallucinogenic phenylalkylamines by the comparative molecular field analysis (CoMFA). Two conformations were compared during the modeling. Conformation I referred to the amino group close to ring position 6 and conformation II related to the amino group trans to the phenyl ring. Satisfactory results were obtained by using both conformations. There were still differences between the two models. The model based on conformation I got better statistical results than the one about conformation II. And this may suggest that conformation I be preponderant when the hallucinogenic phenylalkylamines interact with the receptor. To further confirm the predictive capability of the CoMFA model, 18 compounds with conformation I were randomly selected as a test set and the remaining ones as training set. The best CoMFA model based on the training set had a cross-validation coefficient q ² of 0.549 at five components and non cross-validation coefficient R ² of 0.835, the standard error of estimation was 0.219. The model showed good predictive ability in the external test with a coefficient R _pre² of 0.611. The CoMFA coefficient contour maps suggested that both steric and electrostatic interactions play an important role. The contributions from the steric and electrostatic fields were 0.450 and 0.550, respectively.     

苯并嗪酮衍生物的3D-QSAR分析

苯并嗪酮衍生物是近年来发现的一类抗血小板聚集化合物, 在前人研究的基础上利用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)对23个苯并嗪酮衍生物进行了三维定量构效关系(3D-QSAR)研究. 其中CoMFA模型交叉验证系数Q2=0.703, 回归系数R2=0.994, 计算值与实验值的平均方差SEE=0.053, 统计方差比F=184.773; CoMSIA模型Q2=0.847, R2=0.992, SEE=0.058, F=171.670. 两种方法得到的模型都具有较好的预测能力. 结果表明, 标题化合物中8-位取代基R1静电效应起主要作用; 2-位取代基R2立体效应占主导作用, 但官能团大小要适中. 根据研究结果设计了六种活性较高的化合物.     

比较分子场分析研究哒嗪酮的体系的三维构效关系

用比较分子场分析（CoMFA）法对两个体系的化合物进行了研究，得到了预报能力较强的模型. 初步的研究表明，作为一种三维定量构效（3D-QSAR）方法，它能够揭示分子三维结构对活性的贡献，有较广阔的应用前景．     

3D-QSAR Study on Apicidin Inhibit Histone Deacetylase

For Histone Deacetylase (HDAC) Inhibitor, four 3D-QSAR models for four types of different activities, were constructed.The cross-valldated q^2 value of CoMFA Model 1 is 0.624 and the noncross-validated r2 value is 0.939. The cross-validated q^2 value of Model 2 for training set is 0.652 and the noncross-validated r^2 value is 0.963. The cross-validated q^2 value for Model 3 is 0.713, with noncross-validated r^2 value 0.947. The crossvalidated q2 value for Model 4 is 0.566 with noncross-validated r^2 value 0.959. Their predicted abilities were validated by different test sets which did not include in training set. Then the relationship between substituents and activities was analyzed by using these models and the main influence elements in different positions (positions 8 and 14) were found. The polar donor electron group of position 8 could increase the activity of inhibition of HDAC, because it could form chelation with the catalytic Zn. Suitable bulk and positive groups at position 14 are favorable to anti-HDAC activity. These models could web interpret the relationship between inhibition activity and apicidin structure affording us important information for structurebased drug design.     

带有分子轨道能量的3D-QSAR对N-氨基咪唑的研

N-氨基咪唑(NAIMs)能通过三种不同的作用方式抑制HIV-1的复制. 用比较分子场（CoMFA）方法对一系列有共同骨架的NAIM分子建立3D-QSAR模型. 与以往模型不同的是，在偏最小二乘（PLS）分析中尝试引入分子轨道能量的信息来研究生物活性与分子轨道能量的关系. 结果得到了几个模型，分子轨道能量对模型的贡献能为21.7%，轨道HOMO5对模型的贡献最大.     

光系统II(PSII)抑制剂的比较分子场研究

以光系统II抑制剂DISCO(DIStance COmparisons)模型的活性构象分子作为模板,利用比较分子场分析方法对三类结构不同的化合物进行了三维构效关系的研究.研究结果有助于对DISCO重叠模型的评估和新型PSII抑制剂的设计与合成.     

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.     

比较分子场分析方法研究的最新进展*

比较分子场分析方法(CoM FA ) 是目前在三维定量构效关系(3D2Q SAR) 中应用最为广泛的方法之一。但传统的比较分子场分析方法在具体的实现过程中还存在着一些缺陷和不足, 包括分子场势能函数的选择, 活性构象的确定, 分子的叠合以及分子场变量的选取等等。本文结合我们科研组的工作, 就近几年CoM FA 方法的最新进展做了较为详细的阐述, 同时对CoM FA 的发展前景及其在药物设计中的应用进行了展望。     

3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

胆固醇酯转运蛋白抑制剂的3D-QSAR模型

利用VolSurf参数和比较分子场分析(CoMFA)方法对N,N-二取代三氟-3-氨基-2-丙醇衍生物类胆固醇酯转运蛋白抑制剂进行了三维定量构效关系(3D-QSAR)模型研究, 均得到较好的结果, 训练集模型具有良好的预测能力. VolSurf参数分析表明抑制活性高的分子必须具有合适的亲水性、多的氢键给体和少的氢键受体; 在一定范围内, 分子量大、表面光滑且非球性高的分子抑制活性高; 高疏水性以及质量中心与疏水区中心的高不平衡性对活性是不利因素. CoMFA结果表明, 立体作用对活性的影响较静电作用稍强, N-苯基取代基苯氧基的间位体积大且正电性强的基团对活性有利, N-苄基取代基的间位体积大且合适的电负性对活性有利, 而苄基的对位立体位阻的增加则对活性不利. VolSurf参数提供了分子整体性质信息, CoMFA提供了取代基信息, 两者互为补充, 对该类抑制剂新化合物的设计具有指导意义.     

酪氨酸蛋白磷酸酯酶1B抑制剂的分子对接和三维定量构效关系研究

用一种柔性分子对接方法(FlexX)将12个2-草酰胺苯甲酸类抑制剂和酪氨酸蛋白磷酸酯酶(PTP1B)活性口袋进行分子对接,对接程序预测的抑制剂和酶之间的相互作用能与抑制活性之间有很好的相关性(非线性相关系数R²达0.859),这说明对接结果可以比较准确地预测抑制剂和PTP1B之间的结合模式.然后,将33个同类抑制剂的骨架叠合在分子对接预测的结合构象上,用比较分子力场分析方法(CoMFA)对其进行三维定量活性构效关系研究,得到的CoMFA模型具有很好的统计相关性(交互验证回归系数q²为0.650),并可以准确地预测测试集6个化合物的活性(平均标准偏差为0.177).同时,由CoMFA模型得出的抑制剂改造信息与用FlexX预测的结合模式是一致的,进一步证明我们预测的结合模式是正确的.为研究这类抑制剂和PTP1B的结合模式及对抑制剂进行结构改造提供了信息.     

酪氨酸激酶抑制剂的比较分子场分析

采用比较分子场分析(CoMFA)方法研究了一组嘧啶类衍生物酪氨酸激酶抑制剂活性与结构的关系.所得模型不仅能够很好地预报训练集中的化合物的活性,而且还可以准确地预报预报集中的化合物活性.通过分析分子场等值面图在空间的分布,可以观察到叠加分子周围的立体和静电特征对化合物活性的影响.     

异喹啉类化合物抑制肥大细胞脱颗粒活性的3D-QSAR研究

对一组抑制肥大细胞脱颗粒的异喹啉类化合物的活性及毒性进行了3D-QSAR研究,采用距离比较法(DISCO)得到了它们的药效团模型,通过选择不同的叠合方式,建立了相关性很好的比较分子力场分析(CoMFA)模型,其交叉验证参数R^2~cv分别为0.654和0.662,非交叉验证的相关系数分别为0.990与0.983,通过查阅统计量F表,表明活性及毒性模型的置信度都大于99%,显示模型具有较强的预测能力,并在此基础上进行了新活性先导化合物的设计,得到了预测活性高以及预测毒性低的新结构,合成实验正在进行之中。     

Molecular docking and 3D-QSAR study of pyranmycin derivatives against 16S rRNA A site

To understand pharmacophore properties of pyranmycin derivatives and to design novel inhibitors of 16S rRNA A site, comparative molecular field analysis (CoMFA) approach was applied to analyze three-dimensional quantitative structure–activity relationship (3D-QSAR) of 17 compounds. AutoDock 3.0.5 program was employed to locate the orientations and conformations of the inhibitors interacting with 16S rRNA A site. The interaction mode was demonstrated in the aspects of inhibitor conformation, hydrogen bonding and electrostatic interaction. Similar binding conformations of these inhibitors and good correlations between the calculated binding free energies and experimental biological activities suggest that the binding conformations of these inhibitors derived from docking procedure were reasonable. Robust and predictive 3D-QSAR model was obtained by CoMFA with q² values of 0.723 and 0.993 for cross-validated and non-cross-validated, respectively. The 3D-QSAR model built here will provide clear guidelines for novel inhibitors design based on the Pyranmycin derivatives against 16S rRNA A site.