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.     

3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

3D-QSAR study,docking molecular and simulation dynamic on series of benzimidazole derivatives as anti-cancer agents

Benzimidazole is an important heterocyclic organic compound which has a structural analogy to nucleotides found in human body and hence is an important pharmacophore in medicinal chemistry. The anti-cancer activities for a diverse set of benzimidazole as anti-cancer agents against breast cancer cell line (MCF7) assay have been subjected to 3D-QSAR (3-Dimensional Quantitative Structural-Activity Relationship) studies. Both CoMFA and CoMSIA models exhibit significant results in terms of statistical parameters as determination coefficients R² > 0.9 and Leave One Out cross-validation determination coefficients Q²> 6. The predictive quality of both 3D QSAR models have been assessed by external validation and Y-randomization test. Five new compounds have been designed and predicted by in silico ADMET method. In the second part, we have used the docking molecular and simulation dynamics (MD) to investigate the bonding interactions and stability of the designed compounds into the Pin1. Then, we have compared them to Trastuzumab and Tamoxifen as a standard inhibitors drug of breast cancer. The designed compounds form stable hydrogen and hydrophobic bonding interactions with the residues Lys63, Gln131, Ser154, Arg 68 and Arg69 of Pin1 receptor during 100 ns as a time of the simulation. The obtained results showed that the new benzimidazole are useful as a template for future design of more potent inhibitors against breast cancer cell lines (MCF7).     

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 studies on indole and 7-azoindole derivatives as ROCK-2 inhibitors: An integrative computational approach

Rho Kinases (ROCK) has been found to regulate a wide range of fundamental cell functions such as contraction, motility, proliferation, and apoptosis. Recent experiments have defined new functions of ROCKs in cells, including centrosome positioning and cell-size regulation, which might contribute to various physiological and pathological states. In this study, we have performed pharmacophore modeling and 3D QSAR studies on a series of 36 indoles and 7-azoindoles derivatives as ROCK2 inhibitors to elucidate the structural variations with their inhibitory activities. Ligand based CoMFA and CoMSIA models were generated based on three different alignment methods such as systematic search, simulated annealing and pharmacophore. A total of 15 CoMFA models and 27 CoMSIA were generated using different alignments. One model from each alignment is selected based on the statistical values. Contour maps of the selected models were compared, analysed and reported. The 3D QSAR study revealed that electro positive group linked to the methoxy-benzene ring position of the structure will enhance the biological activity and bulkier substitutions are preferred in the methyl dihydroindole region. Also, it is found that the hydrogen bond donor substituted at the R₁ position enhances the inhibitory activity. In future, this study would give proper guidelines to further enhance the activity of novel inhibitors for ROCK2.     

Molecular modelling studies on cinnoline-based BTK inhibitors using docking and structure-based 3D-QSAR

ABSTRACT

BTK inhibitors have been proved as an effective target for B-cell malignancies. Ibrutinib is the most advanced irreversible BTK inhibitor for treating mantle cell lymphoma/chronic lymphocytic leukaemia but with existing drug resistance and adverse effects. To design novel effective and safety reversible BTK inhibitors, 115 newly cinnoline analogues were selected to perform molecular docking and 3D-QSAR study because of the main scaffold similarity to Ibrutinib. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions are preferred at R₁ and R₃ positions, and introducing hydrophilic and negative electrostatic substitutions at R₁ positions is important for improving BTK inhibitory activities. These results will be useful to provide clues for rationally designing novel and high potency BTK inhibitors.     

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.     

噁唑-苯甲酰胺类FtsZ受体抑制剂的3D-QSAR研究

FtsZ蛋白和细菌的繁殖过程有关,是药物设计理想的靶点。本文采用Sybyl分子模拟软件,利用比较分子场方法(CoMFA)及比较分子相似性指数的方法(CoMSIA)对已报道的33个噁唑-苯甲酰胺类FtsZ受体抑制剂进行了分析,建立了三维定量构效关系(3D-Qsar)模型。CoMFA模型的交互验证系数q2为0.619,线性回归系数r2为0.988;CoMSIA模型的q2为0.633,r2为0.936。模型具有较好的预测能力,为今后噁唑-苯甲酰胺类化合物的设计和改造提供了理论依据。     

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.     

A combined CoMFA and CoMSIA 3D-QSAR study of benzamide type antibacterial inhibitors of the FtsZ protein in drug-resistant Staphylococcus aureus

A major problem today is bacterial resistance to antibiotics and the small number of new therapeutic agents approved in recent years. The development of new antibiotics capable of acting on new targets is urgently required. The filamenting temperature-sensitive Z (FtsZ) bacterial protein is a key biomolecule for bacterial division and survival. This makes FtsZ an attractive new pharmacological target for the development of antibacterial agents. There have been several attempts to develop ligands able to inhibit FtsZ. Despite the large number of synthesized compounds that inhibit the FtsZ protein, there are no quantitative structure–activity relationships (QSAR) that allow for the rational design and synthesis of promising new molecules. We present the first 3D-QSAR study of a large and diverse set of molecules that are able to inhibit the FtsZ bacterial protein. We summarize a set of chemical changes that can be made in the steric, electrostatic, hydrophobic and donor/acceptor hydrogen-bonding properties of the pharmacophore, to generate new bioactive molecules against FtsZ. These results provide a rational guide for the design and synthesis of promising new antibacterial agents, supported by the strong statistical parameters obtained from CoMFA (r²_pred = 0.974) and CoMSIA (r²_pred = 0.980) analyses.     

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.     

CoMFA 3D-QSAR Analysis of Epothilones Based on Docking Conformation and Alignment

Epothilones belong to a class of novel microtubule stabilizing and anti-mitotic agents, which have a paclitaxel-like mechanism of action. A three-dimensional quantitative structure-activity relationship （3D-QSAR） model was built for epothilones by the method of comparative molecular field analysis （CoMFA） combined with the flexible docking technology. The docking CoMFA model gave a good cross-validated value of q2=0.784 with an optimized component of 6 and the conventional correlation coefficient of r^2=0.985. The statistical results show that the model has good ability to predict the activity of the studied compounds. At last, the docking CoMFA model was analyzed through contour maps complemented with MOLCAD-generated active site potential surface in the α,β-tubulin receptor, which can provide important information for the structure-based drug design.     

酪氨酸蛋白磷酸酯酶1B抑制剂的分子对接和三维定量构效关系研究

用一种柔性分子对接方法(FlexX)将12个2-草酰胺苯甲酸类抑制剂和酪氨酸蛋白磷酸酯酶(PTP1B)活性口袋进行分子对接,对接程序预测的抑制剂和酶之间的相互作用能与抑制活性之间有很好的相关性(非线性相关系数R²达0.859),这说明对接结果可以比较准确地预测抑制剂和PTP1B之间的结合模式.然后,将33个同类抑制剂的骨架叠合在分子对接预测的结合构象上,用比较分子力场分析方法(CoMFA)对其进行三维定量活性构效关系研究,得到的CoMFA模型具有很好的统计相关性(交互验证回归系数q²为0.650),并可以准确地预测测试集6个化合物的活性(平均标准偏差为0.177).同时,由CoMFA模型得出的抑制剂改造信息与用FlexX预测的结合模式是一致的,进一步证明我们预测的结合模式是正确的.为研究这类抑制剂和PTP1B的结合模式及对抑制剂进行结构改造提供了信息.     

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。