新磺酰脲类化合物除草活性的3D-QSAR分析

用比较分子力场分析 (CoMFA) 方法和比较分子相似性指数分析 (CoMSIA) 方法对所合成的新磺酰脲类化合物的除草活性进行了较为系统的3D-QSAR分析.两种方法所建立的模型对化合物的除草活性预测能力均较好,所得三维等值线图为合成高活性的化合物能提供指导作用     

二氢吡啶类化合物的三维定量构效关系

通过分子力学和量子化学计算,得出两种二氢吡啶衍生物的低能构象,再应用比较分子力场分析方法(CoMFA)和比较分子相似性指数分析方法(CoMSIA)分别对两种构象的43个二氢吡啶衍生物进行3D-QSAR研究. 计算结果表明,用两种方法建立的两种构象的构效关系模型均有较好的预测能力.通过分析CoMFA和CoMSIA的系数等势图,直观地了解二氢吡啶衍生物的结构对生物活性的影响,为进一步设计高活性的二氢吡啶衍生物提供一定的理论依据.     

基于分子对接的6-萘甲基取代HEPT类HIV-1逆转录酶抑制剂构效关系研究

采用分子对接方法得到了一系列6-萘甲基取代HEPT类逆转录酶抑制剂分子与HIV-1逆转录酶复合物模型,从中抽取出抑制剂分子的活性构象,进一步应用CoMFA和CoMSIA方法建立了具有较好预测能力的3D-QSAR模型,深入探讨了这些化合物的定量构效关系,为进一步的药物设计奠定了良好的基础.另外,以化合物13及其相应的β异构体24为代表,结合量子化学从头算分子轨道理论方法考察了它们的前线轨道,为阐明α和β系列化合物的活性差异提供了理论依据.     

马来酰胺类糖原合成酶激酶-3β抑制剂的分子对接和三维定量构效关系

通过分子对接和三维定量构效关系(3D-QSAR)两种方法来确定两类马来酰胺类的糖原合成酶激酶-3β(GSK-3β)抑制剂的结合方式. 首先, 用分子对接确定抑制剂与GSK-3β结合模式及其相互作用; 然后用比较分子力场分析法(CoMFA)与比较分子相似性指数分析法(CoMSIA)对48个化合物做三维定量构效关系的分析. 两种方法得出的交互验证回归系数分别为0.669(CoMFA)和0.683(CoMSIA), 证明该模型具有很好的统计相关性, 同时也说明该模型具有较高的预测能力.根据该模型提供的信息, 设计出9个预测活性较好的分子.     

马来酰胺类糖原合成酶激酶-3β抑制剂的分子对接和三维定量构效关系

通过分子对接和三维定量构效关系(3D-QSAR)两种方法来确定两类马来酰胺类的糖原合成酶激酶-3β(GSK-3β)抑制剂的结合方式.首先,用分子对接确定抑制剂与GSK-3β的结合模式及其相互作用;然后用比较分子力场分析法(CoMFA)与比较分子相似性指数分析法(CoMSIA)对48个化合物做三维定量构效关系的分析.两种方法得出的交互验证回归系数分别为0.669(CoMFA)和0.683(CoMSIA),证明该模型具有很好的统计相关性,同时也说明该模型具有较高的预测能力.根据该模型提供的信息,设计出9个预测性较好的分子.     

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...     

N-硝基脲类化合物除草活性的3D-QSAR研究

经活性测试,N-硝基脲类化合物对反枝苋(A. retroflexus L)和苏丹草(S. sudanenses)呈现除草活性。为进一步设计高活性的目标化合物,采用比较分子力场(CoMFA)对38个N-硝基脲类化合物进行三维定量构效关系(3D-QSAR)分析,建立了相关性显著、预测能力强的3D-QSAR模型(反枝苋：q2=0.674, r2=1.000, R2pred=0.9989,苏丹草：q2=0.635, r2=1.000, R2pred=0.9958)。根据CoMFA模型的立体场和静电场三维等势线图,在N’-苯环2, 5位引入体积大的正电荷取代基;3位引入负电荷基团;4, 6位引入体积大的负电荷基团有利于提高目标化合物对双子叶杂草反枝苋的除草活性,而在2位引入体积大的负电荷基团;3位引入体积小的负电荷基团;4位引入体积大的正电荷基团;5位引入体积大的取代基有利于提高目标化合物对单子叶杂草苏丹草的除草活性。     

毒蕈碱受体激动剂的三维定量构效关系研究

采用比较分子场分析法(CoMFA)研究了55个四氢吡啶类毒蕈碱受体激动剂的三维定量构效关系(3D-QSAR), 建立了具有较强预测能力的3D-QSAR模型. 所得模型的交叉验证相关系数(q²)为0.507, 常规相关系数(R²)为0.982 , 标准方差为0.218, 说明系列化合物分子周围立体场和静电场的分布与生物活性间存在良好的相关性. 模型不仅很好地预测了训练集和测试集化合物的活性, 而且为设计活性更高的受体激动剂提供了理论依据.     

顺式新烟碱类衍生物的三维定量构效关系研究

采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)对34个顺式新烟碱类衍生物的杀虫活性进行三维定量构效关系(3D-QSAR)研究.构建的CoMFA和CoMSIA模型的交叉验证系数rc2v分别为0.877和0.862,非交叉验证系数r2分别为0.970和0.961,表明建立的3D-QSAR模型具有较好的统计相关性和预测能力.一系列的研究结果指出:立体场、静电场和氢键受体场是描述顺式新烟碱类衍生物的化学结构与杀虫活性关系的重要参数;在咪唑啉环的3,4位不宜引入较大的取代基,提高咪唑啉环的电负性或增强硝基一个端氧的氢键受体特征有利于提高顺式新烟碱类衍生物的杀虫活性.     

五元杂环并嘧啶类胸苷酸合成酶抑制剂的构效关系和分子对接

用比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)研究了38个五元杂环并嘧啶衍生物类胸苷酸合成酶抑制剂的三维定量构效关系(3D-QSAR), 建立了相关预测模型. CoMFA和CoMSIA模型的交互验证相关系数q²分别为0.662和0.672、非交互验证相关系数R²分别为0.921和0.884、外部交互验证相关系数Q_ext²分别为0.85和0.81. 分子对接得到的结合模式与三维定量构效关系得到的结果一致. 结果表明这两种模型都具有良好的预测能力, 可应用于指导化合物的设计和结构修饰, 为进一步设计新型胸苷酸合成酶抑制剂提供了理论依据.     

Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure–activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure–activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class.     

Homology model-guided 3D-QSAR studies of HIV-1 integrase inhibitors

In the present study, we report the exploration of binding modes of potent HIV-1 integrase (IN) inhibitors MK-0518 (raltegravir) and GS-9137 (elvitegravir) as well as chalcone and related amide IN inhibitors we recently synthesized and the development of 3D-QSAR models for integrase inhibition. Homology models of DNA-bound HIV-1 IN were constructed on the basis of the X-ray crystal structure of the foamy virus IN-DNA complex (PDB ID: 3L2T ) and used for docking. The binding modes of raltegravir and elvitegravir in our homology models are in accordance with those in the foamy virus structure revealing interactions important for inhibitor-IN binding. To gain further insights into the structural requirements for IN inhibition, three-dimensional quantitative structure activity relationship (3D-QSAR) studies were conducted using raltegravir, elvitegravir, and their analogs; our synthesized 3-keto salicylic acid IN inhibitor series; as well as other structurally related HIV-1 IN inhibitors. In the first part of the study with 103 compounds, atom-fit alignments, I and II, and docking-based alignment, III, were used to develop 3D-QSAR models 1, 2, and 3, respectively, each comprising comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSARs. This initial analysis indicated that the docking-based (structure-based) model 3 performed better than the atom-fit (ligand-based) models 1 and 2, in terms of statistical significance and robustness. Thus, the docking-based alignment was then subsequently used with an expanded data set of 296 compounds for building a more comprehensive 3D-QSAR, model 4. Model 4 afforded good q2 values of 0.70 and 0.75 for CoMFA and CoMSIA 3D-QSARs, respectively, and showed good predictive performance on an external validation test set of 59 compounds with predictive r2 values up to 0.71. The HIV IN-DNA homology model of biological relevance and the comprehensive 3D-QSAR models developed in the present study provide insights and new predictive tools for structure-based design and optimization of IN inhibitors.     

Three-dimensional Quantitative Structure-activity Relationship Models of HIV-1 Integrase Inhibitors of DKAs

As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds (DKAs) are one kind of potent and selective inhibitors of HIV-1 IN. In the present work, two three-dimensional QSAR techniques (CoMFA and CoMSIA) were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search (AOS) and all-placement search (APS) were used to optimize the CoMFA model. The diketo and keto-enol tautomers of DKAs were also used to establish the CoMFA models. The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favorable internal validation. A comparative analysis with the three models demonstrated that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models would give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors.     

HEPT类逆转录酶抑制剂的三维定量构效关系

利用比较分子力场分析(CoMFA)方法对32个HEPT类HIV-1逆转录酶抑制剂(RTIs)的三维定量构效关系(3D-QSAR)进行了分析,建立了HIV-1逆转录酶抑制剂的3种3D-QSAR模型,发现影响其生物活性的主要因素为立体场因素,这与HIV-1RT的非底物结合部位(NNBS)的疏水性环境相吻合.进一步分析表明,适当长度的1-位侧链对保持化合物的抗病毒活性致关重要;增大5-位取代基的体积可增强生物活性;在1-位苄氧甲基的对位引入大体积基团有利于提高活性.同时考察立体场、静电场与生物活性的关系,表明,CoMFA模型为最佳预测模型,其交叉验证系数R_CV²=0.870,传统相关系数R²=0.986,标准偏差SE=0.146,F=294.546.用此模型预测了检验组3个HEPT类化合物的-lgEC₅₀,R_pred²=0.850,表明模型具有很好的预测能力,可为HEPT类HIV-1逆转录酶抑制剂的结构优化提供理论指导.     

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.