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.     

3D-QSAR studies of dihydropyrazole and dihydropyrrole derivatives as inhibitors of human mitotic kinesin Eg5 based on molecular docking

Human mitotic kinesin Eg5 plays an essential role in mitoses and is an interesting drug target against cancer. To find the correlation between Eg5 and its inhibitors, structure-based 3D-quantitative structure-activity relationship (QSAR) studies were performed on a series of dihydropyrazole and dihydropyrrole derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Based on the LigandFit docking results, predictive 3D-QSAR models were established, with cross-validated coefficient values (q2) up to 0.798 for CoMFA and 0.848 for CoMSIA, respectively. Furthermore, the CoMFA and CoMSIA models were mapped back to the binding sites of Eg5, which could provide a better understanding of vital interactions between the inhibitors and the kinase. Ligands binding in hydrophobic part of the inhibitor-binding pocket were found to be crucial for potent ligand binding and kinases selectivity. The analyses may be used to design more potent EG5 inhibitors and predict their activities prior to synthesis.     

Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1

3-Phosphoinositide-dependent protein kinase-1 (PDK1) is a promising target for developing novel anticancer drugs. In order to understand the structure-activity correlation of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The study has resulted in two types of satisfactory 3D-QSAR models, including the CoMFA model (r(2)=0.907; q(2)=0.737) and CoMSIA model (r(2)=0.991; q(2)=0.824), for predicting the biological activity of new compounds. The detailed microscopic structures of PDK1 binding with inhibitors have been studied by molecular docking. We have also developed docking-based 3D-QSAR models (CoMFA with q(2)=0.729; CoMSIA with q(2)=0.79). The contour maps obtained from the 3D-QSAR models in combination with the docked binding structures help to better interpret the structure-activity relationship. All of the structural insights obtained from both the 3D-QSAR contour maps and molecular docking are consistent with the available experimental activity data. This is the first report on 3D-QSAR modeling of PDK1 inhibitors. The satisfactory results strongly suggest that the developed 3D-QSAR models and the obtained PDK1-inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and in future drug design.     

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of thiazolone derivatives as hepatitis C virus NS5B polymerase allosteric inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a series of thiazolone derivatives as novel inhibitors bound to the allosteric site of hepatitis C virus (HCV) NS5B polymerase were developed based on CoMFA and CoMSIA analyses. Two different conformations of the template molecule and the combinations of different CoMSIA field/fields were considered to build predictive CoMFA and CoMSIA models. The CoMFA and CoMSIA models with best predictive ability were obtained by the use of the template conformation from X-ray crystal structures. The best CoMFA and CoMSIA models gave q (2) values of 0.621 and 0.685, and r (2) values of 0.950 and 0.940, respectively for the 51 compounds in the training set. The predictive ability of the two models was also validated by using a test set of 16 compounds which gave r (pred) (2) values of 0.685 and 0.822, respectively. The information obtained from the CoMFA and CoMSIA 3D contour maps enables the interpretation of their structure-activity relationship and was also used to the design of several new inhibitors with improved activity.     

Docking and 3D-QSAR Analysis on a Series of Pyridone-based EZH2 Inhibitors

Enhancer of Zeste homolog 2(EZH2) is closely correlated with malignant tumor and regarded as a promising target to treat B-cell lymphoma. In our research, the molecular docking and three-dimensional quantitative structure-activity relationships(3D-QSAR) studies were performed on a series of pyridone-based EZH2 compounds. Molecular docking allowed us to study the critical interactions at the binding site of EZH2 protein with inhibitors and identify the practical conformations of ligands in binding pocket. Moreover, the docking-based alignment was applied to derive the reliable 3D-QSAR models. Comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) provided available ability of visualization. All the derived 3D-QSAR models were considered to be statistically significant with respect to the internal and external validation parameters. For the CoMFA model, q~2 = 0.649, r~2 = 0.961 and r~2 pred = 0.877. For the CoMSIA model, q~2 = 0.733, r~2 = 0.980 and r~2 pred = 0.848. With the above arguments, we extracted the correlation between the biological activity and structure. Based on the binding interaction and 3D contour maps, several new potential inhibitors with higher biological activity predicted were designed, which still awaited experimental validation. These theoretical conclusions could be helpful for further research and exploring potential EZH2 inhibitors.     

Docking-based CoMFA and CoMSIA study of azaindole carboxylic acid derivatives as promising HIV-1 integrase inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed based on a series of azaindole carboxylic acid derivatives that had previously been reported as promising HIV-1 integrase inhibitors. Docking studies to explore the binding mode were performed based on the highly active molecule 36. The best docked conformation of molecule 36 was used as template for alignment. The comparative molecular field analysis (CoMFA) model (including steric and electrostatic fields) yielded the cross validation q ² = 0.655, non-cross validation r ² = 0.989 and predictive r ² _pred = 0.979. The best comparative molecular similarity indices analysis (CoMSIA) model (including steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields) yielded the cross validation q ² = 0.719, non-cross validation r ² = 0.992 and predictive r ² _pred = 0.953. A series of new azaindole carboxylic acid derivatives were designed and the HIV-1 integrase inhibitory activities of these designed compounds were predicted based on the CoMFA and CoMSIA models.     

STAT3环烷烃并噻吩类衍生物抑制剂的三维定量构效关系研究

本文对STAT3抑制剂的化学结构与生物活性之间的关系进行研究。采用三维定量构效关系(3D-QSAR)中的比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法针对52个STAT3抑制剂建立3D-QSAR模型,阐明了抑制剂化学结构与其生物活性之间的关系。所构建的CoMFA模型交叉验证系数为0.548,非交叉验证系数为0.754,标准偏差为0.278,显著系数为58.297;所构建的CoMSIA模型交叉验证系数为0.892,非交叉验证系数为0.597,标准偏差为0.192,显著系数为57.794。结果显示CoMFA和CoMSIA模型具有良好的稳定性和预测能力。3D-QSAR模型等势图提供的相关场信息对新型STAT3抑制剂的设计具有指导意义。     

3D-QSAR Analysis of a Series of Dihydroquinolizinone Derivatives as a Hepatitis B Virus Expression Inhibitor

In this study, we explored a three-dimensional quantitative structure-activity relationship(3D-QSAR) model of 63 HBV viral gene expression inhibitors containing dihydroquinolizinones. Two high predictive QSAR models have been built, including comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA). The internal validation parameter(CoMFA, q~2 = 0.701, r~2 = 0.999; CoMSIA, q~2 = 0.721, r~2 = 0.998) and external validation parameter(CoMFA, r~2_(pred = 0.999); CoMSIA, r~2_(pred = 0.999)) indicated that the models have good predictive abilities and significant statistical reliability. We designed several molecules with potentially higher predicted activity on the basis of the result of the models. This work might provide useful information to design novel HBV viral gene expression inhibitors.     

苯并咪唑类缓蚀剂的3D-QSAR研究及分子设计

采用比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA), 对苯并咪唑衍生物抗盐酸腐蚀的缓蚀性能进行了三维定量构效关系研究, 并使用留一法交叉验证手段对3D-QSAR模型的稳定性及预测能力进行了分析. 结果表明, 立体场、静电场和氢键供体场(电子给体)是影响苯并咪唑缓蚀剂缓蚀性能的主要因素; 所构建的CoMFA模型(q2=0.541, R2=0.996)和CoMSIA模型(q2=0.581, R2=0.987)均具有较好的统计学稳定性和预测能力. 基于3D-QSAR等势图设计出了几种具有较好缓蚀性能的苯并咪唑化合物, 为油气田新型缓蚀剂的研发提供了一种新思路.     

CoMFA 3D-QSAR analysis of HIV-1 RT nonnucleoside inhibitors, TIBO derivatives based on docking conformation and alignment

HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as nonnucleoside RT inhibitors (NNRTIs) and nucleoside analogues. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTI category, there is a set of inhibitors commonly referred to as TIBO inhibitors. Fifty TIBO inhibitors were used in the work to build 3-D QSAR models. The two known crystal structures of complexes are used to investigate and validate the docking protocol. The results show that the docking simulations reproduce the crystal complexes very well with RMSDs of approximately 1 A and approximately 0.6 A for 1REV and 1COU, respectively. The alignment of molecules and "active" conformation selection are the key to a successful 3D-QSAR model by CoMFA. The flexible docking (Autodock3) was used on determination of "active" conformation and molecular alignment, and CoMFA and CoMSIA were used to develop 3D-QSAR models of 50 TIBOs in the work. The 3D-QSAR models demonstrate a good ability to predict the activity of studied compounds (r2 = 0.972, 0.944, q2 = 0.704, 0.776). It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the binding structure of the complex. The results demonstrate that the combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models.     

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.     

Pharmacophore and Docking-based 3D-QSAR Studies on HIV-1 Integrase Inhibitors

Integrase（IN） plays an essential role in the process of HIV-1 replication.IN inhibitors of diketo acid derivatives（DKAs） were analysed by the Comparative Molecular Field Analysis（CoMFA） and Comparative Molecular Similarity Induces Analysis（CoMSIA） methods.A set of 42 compounds were randomly selected as the training set（35） and test set（7）.Firstly,a good pharmacophore（goodness of hit=0.787） was obtained and used to align ligands.Then,predictive models were constructed with the CoMFA and CoMSIA methods based on the pharmacophore alignment.As a result,the CoMS1A method yielded the best model with an r2 of 0.955 and a q2 of 0.665,which can predict the activities of the tested DKAs very well（r2=0.559）.Finally,DKAs were docked into IN,and the predicit modes were superimposed on the contour maps obtained from the best CoMSIA model.The superimposed maps gave a visualized and meaningful insight into the inhibitory behaviors,providing significantly useful information for the rational drug design of anti-IN agents.     

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.     

CBP/P300溴结构域联芳基类抑制剂三维定量构效关系研究

CREB结合蛋白(CBP)和与其高度同源的P300蛋白是组蛋白乙酰化酶的两个亚型,两者通过它们的溴结构域(bromodomain,BRD)与染色质结合,目前,CBP/P300已经成为人类在肿瘤靶点领域中的研究热点。本研究基于CBP/P300溴结构域联芳基类抑制剂建立三维定量构效关系,采用比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(Co MSIA)分别建立35个已知活性抑制剂的3D-QSAR模型,以确定CBP/P300溴结构域联芳基类抑制剂分子结构与生物活性之间的定量关系。Co MFA和Co MSIA模型活性数据p IC50的预测值与实验值基本一致,说明这两个模型具有较高的预测能力和统计学意义。根据Co MFA和Co MSIA模型所提供的立体场、静电场、疏水场、氢键给体场、氢键供体场等信息提出了改善此类抑制剂活性的药物设计思路,为指导设计具有更高活性的新分子和预测更加有效的CBP/P300溴结构域抑制剂提供理论依据。     

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.