R基团搜索技术用于硼酸三肽蛋白酶体抑制剂的分子设计

本文采用Topomer CoMFA对44个Tyropeptin硼酸三肽类蛋白酶体抑制剂进行三维定量构效关系(3D-QSAR)分析。所得最优模型的拟合、交互验证、及外部验证的复相关系数分别为0.983、0.651、0.963。采用Topomer search对ZINC数据库进行R基团的虚拟筛选,得到具有特定活性贡献的R基团,以活性最高的分子为模板过滤,得到7个R1和5个R2基团。并以此设计得到活性优于模板分子的20个新化合物。结果表明,所建立的Topomer CoMFA模型具有良好的稳定性和预测能力,基于R集团的Topomer search技术可以有效筛选,并为设计出新的蛋白酶体抑制剂提供理论依据。     

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。     

A 3D-QSAR Study of HIV-1 Integrase Inhibitors Using RASMS and Topomer CoMFA

Acquired Immunodeficiency Syndrome(AIDS) is a significant human health threat around the world. Therefore, the study of anti-human immunodeficiency virus(HIV) drug design has become an important task for today's society. In this paper, a three-dimensional quantitative structure-activity relationships study(3 D-QSAR) was conducted on 53 HIV-1 integrase inhibitors(IN) using random sampling analysis on molecular surface(RASMS) and Topomer comparative molecular field analysis(Topomer CoMFA). The multiple correlation coefficients of fitting, cross-validation, and external validation of two models were 0.926, 0.815 and 0.908 and 0.930, 0.726 and 0.855, respectively. The results indicated that two models obtained had both favorable estimation stability and good prediction capability. Topomer Search was used to search appropriate R groups from ZINC database, and 28 new compounds were designed thereby. The Topomer CoMFA model was subsequently used to predict the biological activity of these compounds, showing that 24 of the new compounds were more active than the template molecule. Ligands of the template molecule and new designed compounds were used for molecular docking to study the interaction of these compounds with the protein receptor. The results show that the ligands would form hydrogen-bonding interactions with the residues LEU58, THR83, GLN62, MET155, LYS119 and ALA154 of the protein receptor generally, thereby providing additional insights for the design of even more effective HIV/AIDS drugs.     

R基团搜索技术用于PTH类Tau蛋白抑制剂的分子设计

对26个PTH类Tau蛋白抑制剂进行了Topomer CoMFA研究, 建立了拟合及预测能力良好的Topomer CoMFA模型, 获得的模型拟合、 交互验证及外部预测的复相关系数分别为0.976, 0.603和0.795, 估计标准偏差和Fisher验证值F分别为0.110和115.778. 使用ZINC化合物数据集作为结构片段源, 通过三维定量构效关系(3D-QSAR)模型搜索具有特定活性贡献的R基团. 以样本中活性最高的1号分子过滤, R₁和R₂贡献值均提高了20%的片段分别有9个与2个. 以此交替取代1号样本的R₁与R₂, 得到18个新颖化合物并预测其活性, 其中的15个预测活性值优于模板分子. 研究结果表明, Topomer search可有效地用于分子设计, 所设计的分子为阿尔茨海默病(AD)药物的研发提供了新的候选物.     

磺酰脲类乙酰羟基酸合成酶抑制剂Topomer CoMFA研究

磺酰脲类除草剂是一类高选择性、广谱、低毒的化合物,在世界范围内得到了广泛的应用。本文采用易位体-比较分子力场法（Topomer CoMFA）对75个磺酰脲类化合物与植物源野生型拟南芥AHAS酶的离体相互作用进行了三维定量构效关系研究,快速准确地构建了Topomer CoMFA模型,该模型具有较强的预测能力（交叉验证相关系数q2为0.890,非交叉验证相关系数r2为0.967）。此模型对测试集的10个化合物的pKi值进行预测,其预测值与实际值一致。     

6-氮杂吲唑类Pim-1激酶抑制剂的3D-QSAR、药效团模型研究和分子设计

Pim-1 激酶通过作用于多种信号通路或靶点影响肿瘤的发生发展,近年来被认为是肿瘤治疗的良好靶标。本文采用SYBYL-X2. 1. 1软件中的TopomerCoMFA、GALAHAD模块建立计算机模型,研究39个基于6-氮杂吲唑环的Pim-1激酶抑制剂的三维定量构效关系及药效团特征元素。结果显示,TopomerCoMFA建模所得交叉验证系数（q2）和相关系数（r2）分别为0. 756和0. 951,结合外部验证表明此3D-QSAR模型具有较高预测能力及较好的统计学稳定性,同时,用等势图描述了R1、R2基团处立体场、静电场对活性的具体影响。药效团研究结果表明,含氢键受体的芳香杂环母核结构,以及侧链取代基中含有芳香杂环结构对化合物的活性贡献较大。最后根据上述模型信息新设计了15个Pim-1激酶抑制剂分子并完成活性预测及分子对接模式研究,其中4个分子的预测pIC50高于建模分子中活性最好的化合物17,Surflex-Dock分析显示新设计分子均与Pim-1激酶形成较强氢键相互作用。基于6-氮杂吲唑环的Pim-1激酶抑制剂的3D-QSAR模型以及药效团模型可用于指导新型抑制剂的结构优化,为设计和开发具有较高活性的新型Pim-1激酶抑制剂提供有效帮助。     

Topomer CoMFA,HQSAR Studies and Molecular Docking of 2,5-Diketopiperazine Derivatives as Oxytocin Inhibitors

Topomer comparative molecular field analysis(Topomer Co MFA) and holographic quantitative structure-activity relationship(HQSAR) for 130 2,5-diketopiperazine derivatives were used to build a three-dimensional quantitative structure-activity relationship(3D-QSAR) model. The results show that the models have high predictive ability. For Topomer CoMFA, the cross-validated q~2 value is 0.710 and the non-cross-validated r~2 value is 0.834. The most effective HQSAR model shows that the cross-validation q~2 value is 0.700, the non-cross-validated r~2 value is 0.815, and the best hologram length value is 353 using connections and bonds as fragment distinctions. 50 highly active 2,5-diketopiperazine derivatives were designed based on the three-dimensional equipotential map and HQSAR color code map. Finally, the molecular docking method was also used to study the interactions of these new molecules by docking the ligands into the diketopiperazine active site, which revealed the likely bioactive conformations. This study showed that there are extensive interactions between the new molecule and Arg156, Arg122 residues in the active site of diketopiperazine. These results provide useful insights for the design of potent of the new 2,5-diketopiperazine derivatives.     

含磷嘧啶类CDK9抑制剂的分子对接、3D-QSAR和分子动力学模拟

选取64个具有潜力的含磷嘧啶类细胞周期依赖性蛋白激酶(CDK9)小分子抑制剂,采用分子对接方法研究了该类小分子与CDK9的结合作用,结果表明,分子构象、氢键形成、疏水性和氨基酸残基Cys106在此类抑制剂与CDK9的结合过程中具有重要作用.在配体叠合的基础上,运用比较分子力场分析(Co MFA)、比较分子相似性指数分析(Co MSIA)和Topomer Co MFA(T-COMFA)研究了分子结构与抑制活性的关系,发现由训练集立体场、静电场和疏水场组合的Co MSIA模型为最优模型,其内部交叉验证相关系数(Q2=0.557)、非交叉验证相关系数(R2=0.959)和外部预测相关系数(r2=0.863)具有统计学意义,该模型的三维等值线图直观显示了化合物的活性与其三维结构的关系.根据这些结果设计了10个具有新结构的含磷嘧啶类化合物,分子对接和分子动力学模拟结果表明,新化合物和CDK9的结合模式与原化合物64相同,自由能分析从理论上证明了新化合物64d的CDK9抑制活性优于化合物64,并且显示含磷基团与残基Asp109的静电场能在化合物与CDK9作用过程中有重要作用.     

类黄酮抑制P糖蛋白的三维定量构效关系与作用模式

采用基于R基团搜索技术的Topomer CoMFA建立了30个类黄酮类P糖蛋白抑制剂的三维定量构效关系(3D-QSAR)模型, 并用包括9个样本的测试集验证模型的外部预测能力. 所得模型的拟合、 交互验证以及外部验证的复相关系数分别为r²=0.971, q²=0.728和\begin{array}{c}{r}_{\mathit{pred}}^2\end{array}=0.816. 在此基础上, 运用Surflex-dock分子对接法研究了白杨素及其异戊烯化衍生物与P糖蛋白的作用模式. 结果表明, 异戊烯化修饰可显著提高类黄酮的亲脂性, 修饰产物能更好地与P糖蛋白的疏水性口袋契合, 二者结合程度高.     

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.     

Molecular modeling studies of human immunodeficiency virus type 1 protease inhibitors using three‐dimensional quantitative structure‐activity relationship,virtual screening,and docking simulations

In this paper, two 3‐dimensional quantitative structure‐activity relationship models for 60 human immunodeficiency virus (HIV)‐1 protease inhibitors were established using random sampling analysis on molecular surface and translocation comparative molecular field vector analysis (Topomer CoMFA). The non–cross‐validation (r²), cross‐validation (q²), correlation coefficient of external validation (Q²_ext), and F of 2 models were 0.94, 0.80, 0.79, and 198.84 and 0.94, 0.72, 0.75, and 208.53, respectively. The results indicated that 2 models were reasonable and had good prediction ability. Topomer Search was used to search R groups in the ZINC database, 20 new compounds were designed, and the Topomer CoMFA model was used to predicate the biological activity. The results showed that 18 new compounds were more active than the template molecule. So the Topomer Search is effective in screening and can guide the design of new HIV/AIDS drugs. The mechanism of action was studied by molecular docking, and it showed that the protease inhibitors and Ile50, Asp25, and Arg8 sites of HIV‐1 protease have interactions. These results have provided an insight for the design of new potent inhibitors of HIV‐1 protease.     

3D-QSAR Analysis of Naphthyltriazole(Lesinurad) Analogs as Potent Inhibitors of Urate Transporter 1

To obtain useful information for identifying inhibitors of urate transporter 1(URAT1), three-dimensional quantitative structure-activity relationship(3 D-QSAR) analysis was conducted for a series of lesinurad analogs via Topomer comparative molecular field analysis(CoMFA). A 3 D-QSAR model was established using a training set of 51 compounds and externally validated with a test set of 17 compounds. The Topomer CoMFA model obtained(q^2 = 0.976, r2 = 0.990) was robust and satisfactory. Subsequently, seven compounds with significant URAT1 inhibitory activity were designed according to the contour maps produced by the Topomer CoMFA model.     

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.     

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.     

Molecular Docking and 3D QSAR Research of Indolocarbazole Series as Cyclin-Dependent Kinase Inhibitors

Fifty indolocarbazole series as cyclin-dependent kinase inhibitors (CDKs) are used to establish a threedimensional quantitative structure-activity relationship (3D QSAR) model based on docking conformations resulting from the Topomer comparative molecular field analysis (Topomer CoMFA). The statistic parameters show that the cross-validation (q²), the multiple correlation coefficient of fitting (r²), and external validation statistic (Q_ext²) are 0.953, 0.968, and 0.954, respectively. It is demonstrated that this Topomer CoMFA model has good stability and prediction ability. The methodology of the fragment-based drug design (FBDD) was also used to virtually screen new CDKs by the Topomer Search technology. Four similar substitutional groups selected from the ZINC database were added to the basic scaffold. As a result, 18 new CDKs with high activities were obtained. The template molecule and new designed compounds are used to study the binding relationship between the ligands and the receptor protein with Surflex-Dock. The docking results suggest good binding interactions of the designed compounds with protein. There are several hydrogen bondings between CDKs with amino acid residues of LYS33, LYS89, ASP86, LEU83, GLU81.