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.     

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.     

HIV-1逆转录酶抑制剂的3D-QSAR研究及分子设计

采用Topomer Co MFA方法对24个二芳基苯胺衍生物进行三维定量构效关系研究,建立了3DQSAR模型,所得优化模型的非交叉相关系数、交互验证系数以及外部验证的复相关系数分别为0.928,0.654和0.940,结果表明该模型具有良好的稳定性和预测能力。采用分子对接技术对药物与受体的作用机制进行了研究,结果显示,药物与HIV-1逆转录酶的LYS172,GLU138,LYS101等位点作用明显。运用这些信息进行分子设计,在理论上获得了一些具有较高活性的新的二芳基苯胺类抗艾滋病药物,该QSAR的研究结果可为新药合成提供理论参考。     

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.     

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.     

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

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趋化因子CCR2的同源模建,分子对接和3D-QSAR研究

趋化因子CCR2参与炎症反应、免疫移植排斥和肿瘤的发生,已成为新的研究热点。本文以CCR5的晶体结构为模板,同源模建CCR2的结构,并用CCR2小分子抑制剂与其进行分子对接以得到小分子的最优构象。在对接叠合的基础上建立了QSAR模型,采用比较分子场分析(Co MFA)以及比较分子相似性分析(Co MSIA)研究得到Co MFA和Co MSIA模型最佳评价参数分别为q2=0.743,r2=0.968和q2=0.68,r2=0.978。3D-QSAR模型的等势图分析表明,改造配体R3基团可提高化合物活性。所建模型稳定性好、预测性强,对基于CCR2的小分子抑制剂的设计、优化和改造提供了参考。     

皂甙的三维定量构效关系研究

针对目标分子柔性大的特点,在比较分子场分析(CoMFA)方法中采用交叉验证相关系数平方R^2引导的构象选择法。对12个皂甙分子的生物活性进行了三维定量构效关系研究。探讨了几种探针对构效关系结果的影响,并选择了一种较合理的“复合”探针方案。应用该复合探针构建CoMFA模型,发现影响药效的立体场与静电场的贡献分别为40%和40%,其它能量项的贡献为20%。该模型交叉验证的相关系数平方R^2为0.653,非交叉验证的R^2为0.991,方差比F(4,7)值130.195(即置信度99%以上),活性预计的标准偏差与极差比(s/△γ)为4.2%,表明模型具有较好的预测能力。根据该模型,预计在指定位置添加位阻较大的基团活性值提高将会比较明显。     

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.     

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…     

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。     

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.     

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.     

Molecular modelling studies on cinnoline-based BTK inhibitors using docking and structure-based 3D-QSAR

ABSTRACT

BTK inhibitors have been proved as an effective target for B-cell malignancies. Ibrutinib is the most advanced irreversible BTK inhibitor for treating mantle cell lymphoma/chronic lymphocytic leukaemia but with existing drug resistance and adverse effects. To design novel effective and safety reversible BTK inhibitors, 115 newly cinnoline analogues were selected to perform molecular docking and 3D-QSAR study because of the main scaffold similarity to Ibrutinib. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions are preferred at R₁ and R₃ positions, and introducing hydrophilic and negative electrostatic substitutions at R₁ positions is important for improving BTK inhibitory activities. These results will be useful to provide clues for rationally designing novel and high potency BTK inhibitors.     

q~2引导构象选择CoMFA方法研究HIV－1RT抑制剂

对未知受体结构的药物设计其主导方法CoMFA来说，柔性目标分子的多种构象 造成了问题的复杂性。本文介绍交叉验证参数R~2(q~2)引导的构象选择CoMFA方法 ，选择化合物的最佳构象。将一组47个HIV－1 RT抑制剂进行有、无构象选择的 CoMFA分析来作评价。根据化合物的活性、毒性、选择性指数（毒性／活性比）等 实验数据得到的模型，其交叉验证参数q~2为0.7以上，非交叉验证的相应参数为0. 94以上，最后，还经过试验集化合物验证该模型的预测能力，置信度（1－α）＞ 0.99。     

三维定量结构-活性关系研究的近况*

本文介绍并综述了以CoMFA, APEX-3D, Ludi和Leapfrog为代表的三维定量结构一活性关系研究方法的近况。作为药物分子设计的新方法,它们在新药设计和先导化合物的产生中起着越来越重要的作版。     

A combined CoMFA and CoMSIA 3D-QSAR study of benzamide type antibacterial inhibitors of the FtsZ protein in drug-resistant Staphylococcus aureus

A major problem today is bacterial resistance to antibiotics and the small number of new therapeutic agents approved in recent years. The development of new antibiotics capable of acting on new targets is urgently required. The filamenting temperature-sensitive Z (FtsZ) bacterial protein is a key biomolecule for bacterial division and survival. This makes FtsZ an attractive new pharmacological target for the development of antibacterial agents. There have been several attempts to develop ligands able to inhibit FtsZ. Despite the large number of synthesized compounds that inhibit the FtsZ protein, there are no quantitative structure–activity relationships (QSAR) that allow for the rational design and synthesis of promising new molecules. We present the first 3D-QSAR study of a large and diverse set of molecules that are able to inhibit the FtsZ bacterial protein. We summarize a set of chemical changes that can be made in the steric, electrostatic, hydrophobic and donor/acceptor hydrogen-bonding properties of the pharmacophore, to generate new bioactive molecules against FtsZ. These results provide a rational guide for the design and synthesis of promising new antibacterial agents, supported by the strong statistical parameters obtained from CoMFA (r²_pred = 0.974) and CoMSIA (r²_pred = 0.980) analyses.