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 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.     

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.     

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.     

Microscopic binding of butyrylcholinesterase with quinazolinimine derivatives and the structure–activity correlation

Butyrylcholinesterase (BChE) is not only an important protein for development of anti-cocaine medication but also an established drug target to develop new treatment for Alzheimer’s disease (AD). The molecular basis of interaction of a new series of quinazolinimine derivatives as BChE inhibitors has been studied by molecular docking and molecular dynamics (MD) simulations. The molecular docking and MD simulations revealed that all of these inhibitors bind with BChE in similar binding mode. Based on the similar binding mode, we have carried out three-dimensional quantitative structure–activity relationship (3D-QSAR) studies on these inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), to understand the structure–activity correlation of this series of inhibitors and to develop predictive models that could be used in the design of new inhibitors of BChE. The study has resulted in satisfactory 3D-QSAR models. We have also developed ligand-based 3D-QSAR models. The contour maps obtained from the 3D-QSAR models in combination with the simulated binding structures help to better interpret the structure–activity relationship and is consistent with available experimental activity data. The satisfactory 3D-QSAR models strongly suggest that the determined BChE-inhibitor binding modes are reasonable. The identified binding modes and developed 3D-QSAR models for these BChE inhibitors are expected to be valuable for rational design of new BChE inhibitors that may be valuable in the treatment of Alzheimer’s disease.     

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.     

苯并呋喃类N-肉豆蔻酰基转移酶抑制剂的三维定量构效关系研究

摘要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), 系统地研究了40个苯并呋喃类N-肉豆蔻酰基转移酶(NMT)抑制剂的三维定量构效关系. 在CoMFA研究中, 考察了网格点步长对模型统计结果的影响. 在CoMSIA研究中, 研究了各种分子场组合、 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可得到最佳模型. 所建立的CoMFA和CoMSIA模型的交叉相关系数q2值分别为0.759和0.730, 均具有较强的预测能力. 利用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并呋喃环上各位置取代基对抑酶活性的影响, 为进一步结构优化提供了重要依据.     

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.     

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.     

Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.     

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...     

A selectivity study of benzenesulfonamide derivatives on human carbonic anhydrase II/IX by 3D-QSAR,Molecular Docking and Molecular Dynamics Simulation

Nowadays, different approaches have been pursued with the intent to develop sulfonamide-like carbonic anhydrase inhibitors that possess better selectivity profiles toward the different human isoforms of the enzyme. Here, we used conventional 3D-QSAR methods, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA, to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models for benzenesulfonamide derivatives as human carbonic anhydrase (hCA) II/IX inhibitors. The theoretical models had good reliability (R²>0.75) and predictability (Q²>0.55), and the contour maps could graphically present the contributions of the force fields for activity and identify the structural divergence between human carbonic anhydrase II inhibitors and human carbonic anhydrase IX inhibitors. Consequently, we explored the selectivity of inhibitor for human carbonic anhydrase II and IX through molecular docking, and the difference of activity coincides with the potential binding mode well. According to the results of the predicted values and the molecule docking, we found that the inhibitors published in the literature had stronger inhibition on the hCA IX; based on the theoretical models, we designed seven new compounds with good potential activity and reasonably good ADMET profile, which could selectively inhibit hCA IX. Molecular Dynamics Simulation showed that newly-designed compound D7 had good selectivity on hCA IX. The findings from 3D-QSAR and docking studies maybe helpful in the rational drug design of isoform-selective 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.     

Molecular description of pyrimidine-based inhibitors with activity against FAK combining 3D-QSAR analysis,molecular docking and molecular dynamics

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R²_cv = 0.528, R²_pred = 0.7557) and CoMSIA model (R²_cv = 0.757, R²_pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.     

3D-QSAR and Docking Studies of Pyrido[2,3-d]pyrimidine Derivatives as Wee1 Inhibitors

In order to investigate the inhibiting mechanism and obtain some helpful information for de-signing functional inhibitors against Wee1, three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies have been performed on 45 pyrido[2,3-d] pyrim-idine derivatives acting as Wee1 inhibitors. Two optimal 3D-QSAR models with significant statistical quality and satisfactory predictive ability were established, including the CoMFA model (q²=0.707, R²=0.964) and CoMSIA model (q²=0.645, R²=0.972). The external val-idation indicated that both CoMFA and CoMSIA models were quite robust and had high predictive power with the predictive correlation coefficient values of 0.707 and 0.794, essen-tial parameter r²_m values of 0.792 and 0.826, the leave-one-out r²_m(LOO) values of 0.781 and 0.809, r²_m(overall) values of 0.787 and 0.810, respectively. Moreover, the appropriate binding orientations and conformations of these compounds interacting with Wee1 were revealed by the docking studies. Based on the CoMFA and CoMSIA contour maps and docking analyses, several key structural requirements of these compounds responsible for inhibitory activity were identified as follows: simultaneously introducing high electropositive groups to the sub-stituents R1 and R5 may increase the activity, the substituent R2 should be smaller bulky and higher electronegative, moderate-size and strong electron-withdrawing groups for the substituent R3 is advantageous to the activity, but the substituent X should be medium-size and hydrophilic. These theoretical results help to understand the action mechanism and design novel potential Wee1 inhibitors.     

In silico design novel (5-imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine derivatives as inhibitors for glycogen synthase kinase 3 based on 3D-QSAR,molecular docking and molecular dynamics simulation

Glycogen Synthase Kinase 3 (GSK-3) is a member of cellular kinase with various functions, such as glucose regulation, cellular differentiation, neuronal function and cell apoptosis. It has been proved as an important therapeutic target in type 2 diabetes mellitus and Alzheimer's disease. To better understand their structure–activity relationships and mechanism of action, an integrated computational study, including three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD), was performed on 79 (5-Imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine GSK-3 inhibitors. In this paper, we constructed 3D-QSAR using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) method. The results showed that the CoMFA model (q ² = 0.743, r² = 0.980) and the CoMSIA model (q² = 0.813, r² = 0.976) had stable and reliable predictive ability. The electrostatic and H-bond donor fields play important roles in the models. The contour maps of the model visually showed the relationship between the activity of compounds and their three-dimensional structure. Molecular docking was used to identify the key amino acid residues at the active site of GSK-3 and explore its binding mode with ligands. Based on 3D-QSAR models, contour maps and the binding feature between GSK-3 and inhibitor, we designed 10 novel compounds with good potential activity and ADME/T profile. Molecular dynamics simulation results validated that Ile62, Val70 and Lys85 located in the active site play a key role for GSK-3 complexed with inhibitors. These results might provide important information for designing GSK-3 inhibitors with high activity.     

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.     

雌激素β受体喹啉类配体的分子对接及3D-QSAR研究

对33个喹啉衍生物的雌激素β受体活性进行了分子对接以及比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA). 对接结果显示氢键和疏水作用是配体与受体结合的主要因素,同时结果亦显示对接结合能与观测值pIC50具有极显著的线性相关性. 根据对接后各优势构象将33个样本进行叠合并进行CoMFA与CoMSIA研究,均得到了较优的结果,其中以选用立体场、静电场和疏水场建立的CoMSIA模型结果最优,其主成分数,r2,q2（LOO）和r2pred分别为2, 0.894, 0.708和0.802. 构效关系模型分析显示基团的空间位阻、电性及疏水作用是影响活性的主要因素