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.     

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.     

两类促肾上腺皮质释放激素(CRH)拮抗剂的分子场分析

采用比较分子相似性指数分析方法(CoMSIA)及比较分子场分析方法(CoMSIA)研究了两组CRH拮抗剂结构与活性的关系。在两种方法中,都考虑了静电场、立体场以及氢键场对构效关系的影响,结果表明采用CoMSIA得到构效关系模型要明显优于采用CoMFA得到的构效关系模型,在CoMSIA计算中,当引入疏水场时,三维构效关系模型能得到明显的改善,通过这个三维构效关系模型,可以较为精确地预测化合物的活性。通过分析分子场等值面图在空间的分布,可以观察到叠合分子周围的立体、静电以及疏水特征对化合物活性的影响。     

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.     

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...     

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.     

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.     

A ligand-based molecular modeling study on some matrix metalloproteinase-1 inhibitors using several 3D QSAR techniques

Some three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) for a series of 84 proline-based plus 12 structurally more diversified nonproline matrix metalloproteinase inhibitors. The structures of these inhibitors were built from a structure template extracted from the crystal structure of stromelysin. The structures built were divided into the training and test sets for both the CoMFA and CoMSIA analyses for each being composed of 60 and 24 inhibitors, respectively. The structures in the training set were aligned using some alignment rules derived from the analysis of the Ligplot program on a recent crystal structure of ligand-collagenase-1 complex. Some stepwise CoMSIA's were performed on the aligned training set on which the best CoMFA result was obtained. The best CoMSIA model was identified from the stepwise results, and the corresponding pharmacophore features were used for the construction of a pharmacophore hypothesis by the Catalyst 4.9 program. The training set was extended to include 11 structurally more diversified and nonproline inhibitors. To construct a pharmacophore hypothesis, the conformation of 60 structurally aligned proline-based inhibitors was fixed, while that of the 11 structurally more diversified nonproline inhibitors was allowed to vary during the hypothesis construction process. It was found that the predicted activities by the top hypothesis constructed for both the training and test sets were as good in statistics as those predicted by the best CoMSIA model from which the hypothesis was derived. The top hypothesis was mapped onto the structures of several highly active inhibitors selected from both the training and test sets. The goodness of mapping on each inhibitor was found to be correlated well with the activity of each inhibitor.     

香水百合香气成分的气相色谱保留指数三维定量构效关系研究

采用比较分子场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）方法,研究了香水百合中38种香气成分分子结构与气相色谱保留指数值之间的定量构效关系。用外部测试集验证法和留一交叉验证法对模型的稳健性和预测能力进行了检验,并通过CoMSIA模型和CoMFA模型的分子场三维等势图研究了这些化合物分子中不同化学结构对保留指数值的影响。检验结果表明,所建立的CoMSIA模型和CoMFA模型都具有较好的稳健性和预测能力,且能够合理解释结构对保留指数值的影响,可应用于对香水百合香气成分的色谱保留指数值的预测。与CoMFA模型相比,CoMSIA模型的预测准确度更高,在香水百合香气成分的色谱定量构效关系研究中,显然有更好的应用前景。     

DATA类逆转录酶抑制剂的三维定量构效关系

采用对接方法得到HIV-1抑制剂DATA(二芳基三嗪类)分子的活性构象, 进一步用比较分子场分析(CoMFA)和比较分子相似性分析(CoMSIA)法对DATA类逆转录酶抑制剂(RTIs)的三维定量构效关系(3D-QSAR)进行了研究, 建立3D-QSAR模型, 以指导进一步结构修饰. 用此模型预测了5个DATA类似物, 预测偏差较小, 表明了所建立的模型具有较强的预测能力.     

五味子素类抑制HIV活性的三维定量构效关系研究

建立了五味子活性成分木脂素类和联苯类化合物抑制HIV活性的三维定量构效 方程。采用联苯环原子和苯环质心两种叠合方式，并区分联苯化合物的不同构型， 共建立了四类CoMSIA模型，其中训练集中联苯类为S构型并叠合联苯环原子建立的 CoMSIA模型相关性最好，交叉验证相关系数q~2为0.71，非交叉验证相关系数r~2 = 0.99，标准偏差SE = 0.051, F = 1000.6。CoMSIA方法采用Gaussian函数计算 场能，并在CoMFA方法的立体和静电场基础上加入疏水场，PLS分析结果更为准确。 该模型三维等势图证实了某些结构和活性规律，如联苯基共面性越好，活性越高， 同时给出了苯环上取代基的体积、电性和疏水性要求，为该类化合物的结构改造提 供了依据。     

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: <Emphasis Type="Italic">Plasmodium Falciparum</Emphasis> cysteine proteases inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q ² = 0.696 and r ² = 0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q ² = 0.711 and r ² = 0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r ² _pred values of 0.76 and 0.74, respectively. CoMFA and CoMSIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.     

一类吡唑衍生物的3D-QSAR研究

通过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),系统研究了30个2-烷基（烷硫基）-5-吡唑基-1,3,4-噁二唑（噻二? 颉⑷颍├嗷衔镆种扑疚瓶莶【锘钚缘娜酆隙抗剐Ч叵怠６杂? CoMFA,研究了不同移动步长对考虑静电场和立体场作用时构效关系的影响;对于 CoMSIA,研究了移动步长、场的组合、衰减因子α等参数变化对构效关系的影响, 发现当考虑立体场、疏水场、氢键受体场的贡献时能得到较好的结果。分别得到了 两种方法最为理想的3D-QSAR模型,所得三维等值线图为发现更高活性化合物提供 了有力的指导作用。     

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.     

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.     

Strategies to design pyrazolyl urea derivatives for p38 kinase inhibition: a molecular modeling study

The p38 protein kinase is a serine–threonine mitogen activated protein kinase, which plays an important role in inflammation and arthritis. A combined study of 3D-QSAR and molecular docking has been undertaken to explore the structural insights of pyrazolyl urea p38 kinase inhibitors. The 3D-QSAR studies involved comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The best CoMFA model was derived from the atom fit alignment with a cross-validated r ² (q ²) value of 0.516 and conventional r ² of 0.950, while the best CoMSIA model yielded a q ² of 0.455 and r ² of 0.979 (39 molecules in training set, 9 molecules in test set). The CoMFA and CoMSIA contour maps generated from these models provided inklings about the influence of interactive molecular fields in the space on the activity. GOLD, Sybyl (FlexX) and AutoDock docking protocols were exercised to explore the protein–inhibitor interactions. The integration of 3D-QSAR and molecular docking has proffered essential structural features of pyrazolyl urea inhibitors and also strategies to design new potent analogues with enhanced activity.     

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.