3D-QSAR Analysis of a Series of 1,2,3-Triazole-chromenone Derivatives as an Acetylcholinesterase Inhibitor against Alzheimer's Disease

Chromenones have attracted much attention since they are excellent acetylcholinesterase inhibitor(AChEi). The 1,2,3-triazoles are multifunctional anti-acetylcholinesterase(AChE) agents. In this paper, we report the three-dimensional quantitative structure-activity relationship(3D-QSAR) study of 25 1,2,3-triazolechromenone derivatives based comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA). To construct CoMFA and CoMSIA models, the 25 active molecules were randomly divided into the training and test sets. The obtained cross-validation Q~2 of the CoMFA model, the coefficient of non-cross-validation R~2, and the test value F are 0.597, 0.994, and 396.726, respectively. The cross-validation Q~2 of the CoMSIA model, the coefficient of the non-cross-validation R~2, and the test value F are 0.721, 0.979, and 131.107, respectively. The predictive correlation coefficient(r_(pred)~2) is 0.728 for CoMFA and 0.805 for CoMSIA, which verifies that the model is predictable. Based on the potential maps of CoMFA and CoMSIA, a library containing a set of potent AChEi was designed. The inhibitory potential of the compounds in this library was found to be greater than the inhibitory potential of the most active compounds in the data set. The results obtained from this study laid the foundation for the development of effective drugs for AChEi.     

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.     

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.     

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。     

3D-QSAR Studies on a Series of Indoleamide Derivatives as Antiplasmodial Drugs

In this study, three-dimensional quantitative structure-activity relationship(3D-QSAR) was studied for the antiplasmodial activity of a series of novel indoleamide derivatives by comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(Co MSIA). 3D-QSAR model was established by a training set of 20 compounds and was externally validated by a test set of 4 compounds. The best prediction(Q~2 = 0.593 and 0.527, R~2 = 0.990 and 0.953, r_(pred)~2 = 0.967 and 0.962 for CoMFA and CoMSIA) was obtained according to CoMFA and CoMSIA. Those parameters indicated the model was reliable and predictable. We designed several molecules with high activities according to the contour maps produced by the CoMFA and CoMSIA models.     

Three-dimensional Quantitative Structure-Activity Relationship Analyses of a Series of Butenolide ETA Antagonists

Two kinds of Three-dimensional Quantitative Structure-activity Relationship(3D-QSAR) methods,comparative molecular filed analysis(CoMFA) and comparative molecular similarity indices analysis (CoMSIA) ,were applied to analyze the structure-activity relationship of a series of 63 butenolide ETA selective antagonists with respect to their inhibition against human ETA receptor,The CoMFA and CoMSIA models were developed for the conceivable alignment of the molecules based on a template structure from the crystallized data.The statistical results from the initial orientation of the aligned molecules show that the 3D-QSAR model from CoMFA(q^2=0.543) is obviously superior to that from the conventional CoMSIA(q^2=0.407).In order to refine the model,all-space search (ASS) was applied to minimize the field sampling process.By rotating and translating the molecular aggregate within the grid systematically,all the possible samplings of the molecular fields were tested and subsequently the one with the highest q^2 was picked out .The comparison of the sensitivity of CoMFA and CoMSIA to different space orientation shows that the CoMFA q^2 values are more sensitive to the translations and rotations of the aligned molecules with respect to the lattice than those of CoMSIA.The best CoMFA model from ASS was further refined by the region focused technique.The high quality of the best model is indicated by the high corss-validated correlation and the prediction on the external test set.The CoMFA coefficient contour plots identify several key features that explain the wide range of activities,which may help us to design new effective ETA selective antagonists.     

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.     

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.     

3D-QSAR Study on the Inhibitory Activity of Flavonoids on PIM-1 Kinase

20 Typical flavonoids were selected for study on the interaction between them and PIM-1 kinase with the comparative molecular field analysis method(CoMFA) as well as the comparative molecular similarity index analysis method(CoMSIA) based on molecule docking.3D-QSAR models between these flavonoids and receptor PIM-1 kinase were established.The obtained optimal cross-validation correlation coefficient Q2 for CoMFA model was 0.582,and the non-cross-validation correlation coefficient R2 was 0.955;the corresponding values for CoMSIA model were 0.790 and 0.974,respectively.These two models showed fairly fine stability and predictive ability.In addition,molecule docking results revealed the key residues in the receptor cavity and their specific action ways with flavonoids.     

Molecular Modeling Studies of Vascular Endothelial Growth Factor Receptor Tyrosine Kinase Inhibitors Combining Molecular Docking and 3D-QSAR Methods

The vascular endothelial growth factor (VEGF) and its receptor tyrosine kinases VEGFR-2 or kinase insertdomain receptor (KDR) have emerged as attractive targets for the design of novel anticancer agents. In the present work, molecular docking method combined with three dimensional quantitative structure-activity relationships (comparative molecular field analysis (CoMFA) and comparative molecular similarity indice analysis (CoMSIA)) to analyze the possible interactions between KDR and those derivatives which acted as selective inhibitors. The CoMFA and CoMSIA models gave a cross-validated coefficient Q2 of 0.713 and 0.549, non-cross-validated R2 values of 0.974 and 0.878, and predicted R2 values of 0.966 and 0.823, respectively. The 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. The information obtained from 3D-QSAR and docking studies were very helpful to design novel selective inhibitors of KDR with desired activity and good chemical property.     

含呋喃环双酰脲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27个新型双酰基脲类化合物的杀蚊幼虫(Aedes aegypti L.)活性进行三维定量构效关系(3D-QSAR)研究. 在CoMFA研究中, 考察了网格点步长对统计结果的影响. 在CoMSIA研究中, 系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响, 发现立体场和氢键供体场的组合得到最佳模型. 所建立的CoMFA和CoMSIA模型的非交叉验证相关系数r2值分别为0.828和0.841, 并都具有较强的预测能力. CoMFA和CoMSIA模型的三维等值图不仅直观地解释了结构与活性的关系, 而且为后续优化该系列化合物提供了理论依据.     

新型三唑类抗真菌化合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), 系统研究了40个新型三唑类化合物抗真菌活性的三维定量构效关系. 在CoMFA研究中, 研究了两种药效构象对模型的影响, 并考察了网格点步长对统计结果的影响. 在CoMSIA研究中, 系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响, 发现立体场、静电场、疏水场和氢键受体场的组合得到最佳模型. 所建立CoMFA和CoMSIA模型的交叉相关系数q²值分别为0.718和0.655, 并都具有较强的预测能力. CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯环上各位置取代基对抗真菌活性的影响, 为进一步结构优化提供了重要依据.     

Computer-aided molecular design of (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule targeted agents in prostate cancer

Microtubules are tube-shaped, filamentous and cytoskeletal proteins that are essential in all eukaryotic cells. Microtubule is an attractive and promising target for anticancer agents. In this study, three-dimensional quantitative structure activity relationships (3D-QSAR) including comparative molecular field analysis, CoMFA, and comparative molecular similarity indices analysis, CoMSIA, were performed on a set of 45 (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule-targeted anti-prostate cancer agents. Automated grid potential analysis, AutoGPA module in Molecular Operating Environment 2009.10 (MOE) as a new 3D-QSAR approach with the pharmacophore-based alignment was carried out on the same dataset. AutoGPA-based 3D-QSAR model yielded better prediction parameters than CoMFA and CoMSIA. Based on the contour maps generated from the models, some key features were identified in (E)-N-Aryl-2-arylethene-sulfonamide analogues that were responsible for the anti-cancer activity. Virtual screening was performed based on pharmacophore modeling and molecular docking to identify the new inhibitors from ZINC database. Seven top ranked compounds were found based on Gold score fitness function. In silico ADMET studies were performed on compounds retrieved from virtual screening in compliance with the standard ranges.     

Combined 3D-QSAR, molecular docking, and molecular dynamics study on piperazinyl-glutamate-pyridines/pyrimidines as potent P2Y12 antagonists for inhibition of platelet aggregation

An unusually large data set of 397 piperazinyl-glutamate-pyridines/pyrimidines as potent orally bioavailable P2Y(12) antagonists for inhibition of platelet aggregation was studied for the first time based on the combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD) methods. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) studies have been performed with a training set of 317 compounds, estimating three superimposition methods. The best CoMFA and CoMSIA models, derived from superimposition I, shows leave-one-out cross-validation correlation coefficients (Q(2)) of 0.571 and 0.592 as well as the conventional correlation coefficients (R(2)(ncv)) of 0.814 and 0.834, respectively. In addition, the satisfactory results, based on the bootstrapping analysis and 10-fold cross-validation, further indicate the highly statistical significance of the optimal models. The external predictive abilities of these models were evaluated using a prediction set of 80 compounds, producing the predicted correlation coefficients (R(2)(pred)) of 0.664 and 0.668, respectively. The key amino acid residues were identified by molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good concordance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the rational modification of molecules in order to design more potent P2Y(12) antagonists. We hope the developed models could provide some instructions for further synthesis of highly potent P2Y(12) antagonists.     

3D CoMFA,CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

Molecular modelling studies [comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), topomer CoMFA and hologram quantitative structure–activity relationship (HQSAR)] have been performed on the series of 28 molecules belonging to the series of aromatic acid ester derivatives for their carbonic anhydrase inhibitory activity. The model exhibited good correlation coefficient (r²) and cross‐validated correlation coefficient (q²) for CoMFA, CoMSIA and HQSAR methods. On the basis of the findings from all these studies, a structure–activity relationship was established. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

3D-QSAR Study of Melittin and Amoebapore Analogues by CoMFA and CoMSIA Methods

Peptides are one of the indispensable substances in life. The use of computer aided drug design(CADD) methods to design peptides and peptiodmimetics can short the design cycle, save research funding, improve the level of whole research to a large extent and guide the discovery of new drugs. In this paper, Melittin and amoebapore three-dimensional quantitative structureactivity relationship(3D-QSAR) models were established by using comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) method. The result shows that, the correlation coefficient(q~2) was 0.583 and non-cross-validation correlation coefficient(r~2) was 0.972 for the melittin CoMFA model. The q~2 and r~2 were 0.630 and 0.995 for the best CoMSIA model, 0.645 and 0.993 for the amoebapore CoMFA model, and 0.738 and 0.996 for the best CoMSIA model. The statistical parameters demonstrated that the CoMFA and CoMSIA models had both good predictive ability and high statistical stability, and can provide theoretical basis for designing new high activity polypeptide drugs.     

3D QSAR and molecular docking studies of benzimidazole derivatives as hepatitis C virus NS5B polymerase inhibitors

The urgent need for novel HCV antiviral agents has provided an impetus for understanding the structural requisites of NS5B polymerase inhibitors at the molecular level. Toward this objective, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of 67 HCV NS5B polymerase inhibitors were performed using two methods. First, ligand-based 3D QSAR studies were performed based on the lowest energy conformations employing the atom fit alignment method. Second, receptor-based 3D QSAR models were derived from the predicted binding conformations obtained by docking all NS5B inhibitors at the allosteric binding site of NS5B (PDB ID: 2dxs). Results generated from the ligand-based model were found superior (r2cv values of 0.630 for CoMFA and 0.668 for CoMSIA) to those obtained by the receptor-based model (r2cv values of 0.536 and 0.561 for CoMFA and CoMSIA, respectively). The predictive ability of the models was validated using a structurally diversified test set of 22 compounds that had not been included in a preliminary training set of 45 compounds. The predictive r2 values for the ligand-based CoMFA and CoMSIA models were 0.734 and 0.800, respectively, while the corresponding predictive r2 values for the receptor-based CoMFA and CoMSIA models were 0.538 and 0.639, respectively. The greater potency of the tryptophan derivatives over that of the tyrosine derivatives was interpreted based on CoMFA steric and electrostatic contour maps. The CoMSIA results revealed that for a NS5B inhibitor to have appreciable inhibitory activity it requires hydrogen bond donor and acceptor groups at the 5-position of the indole ring and an R substituent at the chiral carbon, respectively. Interpretation of the CoMFA and CoMSIA contour maps in context of the topology of the allosteric binding site of NS5B provided insight into NS5B-inhibitor interactions. Taken together, the present 3D QSAR models were found to accurately predict the HCV NS5B polymerase inhibitory activity of structurally diverse test set compounds and to yield reliable clues for further optimization of the benzimidazole derivatives in the data set.