A QSAR of the toxicity of amino-benzenes and their structures

The quantum chemical parameters and the topological indices have been calculated for the prediction of the toxicity of amino-benzenes in the environment, and work has been done on the multiple regression and neural networks. The combination of CoMFA with formation heat yields greatly improved results. A good model has been obtained which provides a basis for the studies of the toxic action mechanism.     

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.     

QSAR models of cytochrome P450 enzyme 1A2 inhibitors using CoMFA,CoMSIA and HQSAR

Quantitative structure–activity relationship (QSAR) studies were conducted on an in-house database of cytochrome P450 enzyme 1A2 inhibitors using the comparative molecular field analysis (CoMFA), comparative molecular similarity analysis (CoMSIA) and hologram QSAR (HQSAR) approaches. The database consisted of 36 active molecules featuring varied core structures. The model based on the naphthalene substructure alignment incorporating 19 molecules yielded the best model with a CoMFA cross validation value q² of 0.667 and a Pearson correlation coefficient r² of 0.976; a CoMSIA q² value of 0.616 and r² value of 0.985; and a HQSAR q² value of 0.652 and r² value of 0.917. A second model incorporating 34 molecules aligned using the benzene substructure yielded an acceptable CoMFA model with q² value of 0.5 and r² value of 0.991. Depending on the core structure of the molecule under consideration, new CYP1A2 inhibitors will be designed based on the results from these models.     

Superimposition evaluation of ecdysteroid agonist chemotypes through multidimensional QSAR

The EC₅₀ values for a training set of 66 ecdysteroids and 97 diacylhydrazines were measured in the ecdysteroid-responsive Drosophila melanogaster B_II cell line, a prototypical homologous inducible gene expression system. Each of eight superimposition hypotheses for the folded diacylhydrazine conformation was evaluated and ranked on the basis of CoMFA and 4D-QSAR Q² values for the training set and R² values for a 52-member test set comprising randomly-chosen diacylhydrazines and chronologically-chosen ecdysteroids for which data became available after model construction. Both 4D-QSAR and CoMFA rate a common superimposition as the preferred one. Two additional superimpositions, with somewhat weaker 4D-QSAR and CoMFA consensus, nonetheless share several important topological features. The resultant QSAR models address the question of relative binding orientation of the two ligand families and can be useful as a virtual screen for new chemotypes.     

毒蕈碱受体激动剂的三维定量构效关系研究

采用比较分子场分析法(CoMFA)研究了55个四氢吡啶类毒蕈碱受体激动剂的三维定量构效关系(3D-QSAR), 建立了具有较强预测能力的3D-QSAR模型. 所得模型的交叉验证相关系数(q²)为0.507, 常规相关系数(R²)为0.982 , 标准方差为0.218, 说明系列化合物分子周围立体场和静电场的分布与生物活性间存在良好的相关性. 模型不仅很好地预测了训练集和测试集化合物的活性, 而且为设计活性更高的受体激动剂提供了理论依据.     

Development of biologically active compounds by combining 3D QSAR and structure-based design methods

One of the major challenges in computational approaches to drug design is the accurate prediction of the binding affinity of novel biomolecules. In the present study an automated procedure which combines docking and 3D-QSAR methods was applied to several drug targets. The developed receptor-based 3D-QSAR methodology was tested on several sets of ligands for which the three-dimensional structure of the target protein has been solved – namely estrogen receptor, acetylcholine esterase and protein-tyrosine-phosphatase 1B. The molecular alignments of the studied ligands were determined using the docking program AutoDock and were compared with the X-ray structures of the corresponding protein-ligand complexes. The automatically generated protein-based ligand alignment obtained was subsequently taken as basis for a comparative field analysis applying the GRID/GOLPE approach. Using GRID interaction fields and applying variable selection procedures, highly predictive models were obtained. It is expected that concepts from receptor-based 3D QSAR will be valuable tools for the analysis of high-throughput screening as well as virtual screening data     

2D and 3D‐QSAR studies on antiproliferative thiazolidine analogs

Two‐dimensional (2D) and three‐dimensional (3D) quantitative structure–activity relationships (QSARs) of 22 thiazolidine analogs with antiproliferative activity expressed as pIC₅₀, which is defined as the negative value of the logarithm of necessary molar concentration of these compounds to cause 50% growth inhibition against melanoma cell lines WM‐164, have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) method for 3D. The established 2D‐QSAR model in training set comprised of random 18 compounds shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient (R = 0.832) and the square of the cross‐validation coefficient (q² = 0.803). The same model was further applied to predict pIC₅₀ values of the four compounds in the test set, and the resulting R reaching 0.784, further confirms that this 2D‐QSAR model has high predictive ability. The 3D‐QSAR model also shows good correlative and predictive capabilities in terms of R² (0.956) and q² (0.615) obtained from CoMFA model. Further, the robustness of the CoMFA model was verified by bootstrapping analysis (100 runs) with R (0.979) and SD_bs (0.056). It is very interesting to find that the results from 2D‐ and 3D‐QSAR analyses accord with each other, and they all show that the steric interaction plays a crucial role in determining the cytotoxicities of the compounds, and that selecting a moderate‐size or appropriate‐hydrophobicity substituent R as well as increasing the negative charges of C₄ on phenyl ring at the same time are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with antiproliferative activity. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008     

Theoretical studies on QSAR and mechanism of 2‐indolinone derivatives as tubulin inhibitors

The theoretical studies on three‐dimensional quantitative structure activity relationship (3D‐QSAR) and action mechanism of a series of 2‐indolinone derivatives as tubulin inhibitors against human breast cancer cell line MDA‐MB‐231 have been carried out. The established 3D‐QSAR model from the comparative molecular field analysis (CoMFA) shows not only significant statistical quality but also predictive ability, with high correlation coefficient (R² = 0.986) and cross‐validation coefficient (q² = 0.683). In particular, the appropriate binding orientations and conformations of these 2‐indolinone derivatives interacting with tubulin are located by docking study, and it is very interesting to find that the plot of the energy scores of these compounds in DOCK versus the corresponding experimental pIC₅₀ values exhibits a considerable linear correlation. Therefore, the inhibition mechanism that 2‐indolinone derivatives were regarded as tubulin inhibitors can be theoretically confirmed. Based on such an inhibition mechanism along with 3D‐QSAR results, some important factors improving the activities of these compounds were discussed in detail. These factors can be summarized as follows: the H atom adopted as substituent R₁, the substituent R₂ with higher electropositivity and smaller bulk, the substituents R₄–R₆ (on the phenyl ring) with higher electropositivity and larger bulk, and so on. These results can offer useful theoretical references for understanding the action mechanism, designing more potent inhibitors, and predicting their activities prior to synthesis. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2009     

Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of −OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.     

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.     

以ALS为靶标的新型除草剂的分子设计、合成及生物活性研究Ⅷ.Hansch方法与CoMFA方法相结合研究稠杂磺酰胺类除草剂的构效关系

采用Hansch方法和CoMFA方法从二维及三维空间上对三唑并嘧啶磺酰胺类除草剂的结构与活性关系进行了系统研究,结果发现化合物的立体及电学性质对除草活性有重要影响.化合物要保持高活性需满足合适的立体要求及酸性.此外,研究工作表明Hansch方法和CoMFA方法在一起使用可以更好地反映出药物分子的构效关系.     

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     

Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors

The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q² _LOO=0.937, q² _{L50% O}=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model.     

3D－QSAR Study on Diindolylmethane and Its Analogues with Comparative Molecular Field Analysis(CoMFA)

Comparative molecular field analysis (CoMFA),a three dimensional quantitative structure-activity relationship (3D-QSAR) method was applied to a series of diindolylmethane(DIM) analogs to study the relationship between their structure and their induction of CYP 1A1-associated ethoxyresorufin-O-deethylase(EROD) activity.A DISCO model of pharmacophore was derved to guide the superposition of the compounds.The coefficient of cross-validation (q^2) and non cross-validation(r^2) for the model established by the study are 0.827 and 0.988 respectively,the value of variance ratio (F) is 103.53 and standard error estimate (SEE)is 0.044.These values indicate that the CoMFA model derived is significant and might have a good prediction for the catalytic activity of DIM compounds.As a consequence,the predicted activity values of new designed compounds were all higher than that of the reported value.     

A 3D‐QSAR Study of Celebrex‐Based Pdk1 Inhibitors Using Comfa Method

A 3D‐QSAR study of celebrex‐based compounds of PDK1 inhibitors using comparative molecular field analysis (CoMFA) was carried out. The structures of the compounds were obtained using quantum chemistry calculation. CoMFA calculations for a number of grouped subsets of compounds gave q² values of correlation in the range from 0 to 0.8. The low q² values should be mainly due to the narrow span of biological activity. Calculations for several subsets of 11–13 compounds gave high q² values, with 0.5–0.8. Factors affecting the results of the calculations are discussed. Calculated results with high q² values suggest that further chemical modifications of the compounds could lead to enhanced activity and could be an aid in the design of celebrex‐based cancer drugs.