QSAR and Docking Studies of Thiazolidine-4-carboxylic Acid Derivatives as Neuraminidase Inhibitors

In order to understand the chemical-biological interactions governing their activities toward neuraminidase(NA), QSAR models of 28 thiazolidine-4-carboxylic acid derivatives with inhibitory influenza A virus were developed. Here a quantitative structure activity relationship(QSAR) model was built by three-dimensional holographic atomic vector field(3 D-HoVAIF) and multiple linear regression(MLR). The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations. The correlation coefficient(R2) of established MLR model was 0.984, and the cross-validated correlation coefficient(Q2) of MLR model was 0.947. Furthermore, the cross-validated correlation coefficient for the test set(Qext2) was 0.967. The binding mode pattern of the compounds to the binding site of integrase enzyme was confirmed by docking studies. The results of present study indicated that this model can aid in designing more potent neuraminidase inhibitors.     

A Quantitative Structure–Activity Relationship Study of Calpeptin (Calpain Inhibitor) as an Anticancer Agent

Calpeptin analogs show anticancer properties with inhibition of calpain. In this work, we applied a quantitative structure–activity relationship (QSAR) model on 34 calpeptin derivatives to select the most appropriate compound. QSAR was employed to generate the models and predict the more significant compounds through a series of calpeptin derivatives. The HyperChem, Gaussian 09, and Dragon software programs were used for geometry optimization of the molecules. The 2D and 3D molecular structures were drawn by ChemDraw (Ultra 16.0) and Chem3D (Pro16.0) software. The Unscrambler program was used for the analysis of data. Multiple linear regression (MLR‐MLR), partial least‐squares (MLR‐PLS1), principal component regression (MLR‐PCR), a genetic algorithm‐artificial neural networks (GA‐ANN), and a novel similarity analysis‐artificial neural network (SA‐ANN) method were used to create QSAR models. Among the three MLR models, MLR‐MLR provided better statistical parameters. The R² and RMSE of the prediction were estimated as 0.8248 and 0.26, respectively. Nevertheless, the constructed model using GA‐ANN revealed the best statistical parameters among the studied methods (R² test = 0.9643, RMSE test = 0.0155, R² train = 0.9644, RMSE train = 0.0139). The GA‐ANN model is found to be the most favorable method among the statistical methods and can be employed for designing new calpeptin analogs as potent calpain inhibitors in cancer treatment.     

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.     

Three-dimensional quantitative structure activity relationship (QSAR) of cytotoxic active 3,5-diaryl-4,5-dihydropyrazole analogs: a comparative molecular field analysis (CoMFA) revisited study

ABSTRACT: In vitro antitumor evaluation of the synthesized 46 compounds of 3,5-diaryl-4,5-dihydropyrazoles against EAC cell lines and 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described. CoMFA derived QSAR model shows a good conventional squared correlation coefficient r2 and cross validated correlation coefficient r2 cv 0.896 and 0.568 respectively. In this analysis steric and electrostatic field contribute to the QSAR equation by 70% and 30% respectively, suggesting that variation in biological activity of the compounds is dominated by differences in steric (van der Waals) interactions. To visualize the CoMFA steric and electrostatic field from partial least squares (PLS) analysis, contour maps are plotted as percentage contribution to the QSAR equation and are associated with the differences in biological activity. BACKGROUND: Pyrazole derivatives exhibit a wide range of biological properties including promising antitumor activity. Furthermore, Aldol condensation assisted organic synthesis has delivered rapid routes to N-containing heterocycles, including pyrazoles. Combining these features, the use of chalconisation-assisted processes will provide rapid access to a targeted dihydropyrazoles library bearing a hydrazino 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described for evaluation of antioxidant properties. RESULTS: Chalcones promoted 1 of the 2 steps in a rapid, convergent synthesis of a small library of hydrazinyl pyrazole derivatives, all of which exhibited significant antitumor activity against Ehrlich Ascites Carcinoma (EAC) human tumor cell line comparable to that of the natural anticancer doxorubicin, as a reference standard during this study. In order to understand the observed pharmacological properties, quantitative structure-activity relationship (3D QSAR) study was initiated. CONCLUSIONS: Chalcones heating provides a rapid and expedient route to a series of pyrazoles to investigate their chracterization scavenging properties. Given their favorable properties, in comparison with known anticancer, these pyrazole derivatives are promising leads for further development and optimization.     

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.     

A comparative QSAR analysis and molecular docking studies of phenyl piperidine derivatives as potent dual NK1R antagonists/serotonin transporter (SERT) inhibitors

Depression is a critical mood disorder that affects millions of patients. Available therapeutic antidepressant agents are associated with several undesirable side effects. Recently, it has been shown that Neurokinin 1 receptor (NK₁R) antagonists can potentiate the antidepressant effects of serotonin-selective reuptake inhibitors (SSRIs). In this study, a series of phenyl piperidine derivatives as potent dual NK₁R antagonists/serotonin transporter (SERT) inhibitors were applied to quantitative structure–activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis–based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and NK₁R antagonism/SERT inhibitory of these compounds. The best multiple linear regression equation was obtained from GA-PLS and MLR for NK₁R and SERT, respectively. Based on the resulted model, an in silico-screening study was also conducted and new potent lead compounds based on new structural patterns were designed for both targets. Molecular docking studies of these compounds on both targets were also conducted and encouraging results were acquired. There was a good correlation between QSAR and docking results. The results obtained from validated docking studies indicate that the important amino acids inside the active site of the cavity that are responsible for essential interactions are Glu33, Asp395 and Arg26 for SERT and Ala30, Lys7, Asp31, Phe5 and Tyr82 for NK₁R receptors.     

苯并呋喃／噻吩联二苯类PTP1B抑制剂三维构效关系研究

主要采用比较分子力场分析方法（CoMFA）对苯并呋喃／噻吩联二苯类PTP1B (protein tyrosine phosphatase 1B)抑制剂进行了三维构效关系的研究，考察了 静电场、立体场和氢键场对构效关系的影响，交叉系数q^2的值达到0．58，表明 CoMFA得到的构效关系模型比较理想，同时test set中分子的预测活性也表明，模 型具有较好的预测能力，研究还表明，氢键场的加入不一定有利于模型的改善，通 过对分子场等值面图的分析，可以观察到叠合分子周围立体场和静电场对化合物活 性的影响，为改进原有化合物的结构，提高它们的活性提供了指导，还尝试采用比 较分子相似性指数分析方法（CoMFA）对这一系列化合物作了研究，结果表明虽然 CoMFA中加入了疏水场，但是对于研究的体系，CoMFA的模型质量并没有显著提高。     

A combined molecular modeling study on gelatinases and their potent inhibitors

Zinc‐dependent matrix metalloproteinase (MMP) family is considered to be an attractive target because of its important role in many physiological and pathological processes. In the present work, a molecular modeling study combining protein‐, ligand‐ and complex‐based computational methods was performed to analyze a new series of β‐N‐biaryl ether sulfonamide hydroxamates as potent inhibitors of gelatinase A (MMP‐2) and gelatinase B (MMP‐9). Firstly, the similarities and differences between the binding sites of MMP‐2 and MMP‐9 were analyzed through sequence alignment and structural superimposition. Secondly, in order to extract structural features influencing the activities of these inhibitors, quantitative structure‐activity relationship (QSAR) models using genetic algorithm‐multiple linear regression (GA‐MLR), comparative molecular field (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed. The proposed QSAR models could give good predictive ability for the studied inhibitors. Thirdly, docking study was employed to further explore the binding mode between the ligand and protein. The results from all the above analyses could provide the information about the similarities and differences of the binding mode between the MMP‐2, MMP‐9 and their potent inhibitors. The obtained results can provide very useful information for the design of new potential inhibitors. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

抗癌性吲哚喹唑啉衍生物3D-QSAR研究及其分子设计

吲哚喹唑啉衍生物是近年来发现的一类具有良好抗癌活性的化合物. 作者在最近报道的二维定量构效关系(2D-QSAR)的基础上, 采用比较分子力场方法(CoMFA)进一步对该系列化合物进行三维定量构效关系(3D-QSAR)研究, 建立了3D-QSAR的CoMFA模型, 其非交叉验证相关系数r2=0.986, 标准偏差SD=0.084, 统计方差比F=114.6, 交叉验证相关系数q2=0.695, 表明该模型合理、可信, 并具有良好的预测能力. 研究结果表明: (1) 取代基R1的部位上静电效应起主要作用, 并且确保取代基R1的第一个原子具有较大的净正电荷, 对提高化合物的抗癌活性十分重要. 这与2D-QSAR研究结果相一致. (2) 取代基R2的部位上立体效应起主要作用, R2的体积大小要适中. 应用这些规律进行了分子设计, 在理论上获得了一些具有较高抗癌活性的新的吲哚喹唑啉衍生物, 并期待实验证实. 该QSAR的研究结果可为实验工作者合成新药提供理论参考.     

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.     

In silico design,synthesis and activity of potential drug-like chrysin scaffold-derived selective EGFR inhibitors as anticancer agents

Background & objectiveEpidermal growth factor receptor (EGFR) signaling pathway is one of the promising and well-established targets for anticancer therapy. The objective of the present study was to identify new EGFR inhibitors using ligand and structure-based drug designing methods, followed by a synthesis of selected inhibitors and evaluation of their activity.MethodsA series of C-7-hydroxyproton substituted chrysin derivatives were virtually drawn to generate a small compound library that was screened using 3D QSAR model created from forty-two known EGFR tyrosine kinase inhibitors. Next, the obtained hits with fitness score ≥ 1.0 were subjected to molecular docking analysis. Based on the predicted activity and XP glide score, three EGFR inhibitors were synthesized and characterized using ¹H-NMR, ¹³C-NMR and MS. Finally, comparative in vitro investigation of the biological activity of synthesized inhibitors was performed with that of the parent molecule, chrysin.ResultsThe data depicted a 3.2–fold enhanced cytotoxicity of chrysin derivative, CHM-04 against breast cancer cells as compared with chrysin as well as its binding with EGFR protein. Furthermore, the biological activity of CHM-04 was comparable to the standard EGFR inhibitor, AG1478 in increasing apoptosis and decreasing the migratory potential of triple-negative breast cancer cells as well as significantly lowering the mammosphere forming ability of breast cancer stem cells.ConclusionThe present study suggests CHM-04, an EGFR inhibitor possessing drug-like properties as a plausible therapeutic candidate against breast cancer.     

类吗啡类拮抗物的结构与抑食活性的3D-QSAR研究

用比较力场分析研究了3,4-二甲基-4-(3-羟基苯基)哌啶及其衍生物类吗啡拮抗物的结构与抑食活性的关系,考察了网格结构和探针原子的影响.结果表明,立体效应和静电作用场是描述其抑食活性和进行结构性能关系研究的最重要的结构参数.