Comparative Molecular Field Analysis （CoMFA） of Curcumin-related Compounds for Anticancer Activity

Three-dimensional （3D） quantitative structure-activity relationship （QSAR） studies of 44 curcumin-related compounds have been carried out based on our previously reported result for their anticancer activity against pancreas cancer Panc-I cells and colon cancer HT-29 cells. The established 3D-QSAR models from the comparative molecular field analysis （CoMFA） in training set showed not only significant statistical quality, but also satisfying predictive ability, with high correlation coefficient values （R12= 0.911, R22= 0.985） and cross-validation coefficient values （q2= 0.580, q22= 0.722）. Based on the CoMFA contour maps, some key structural factors responsible for anticancer activity of these series of compounds were revealed. The results provide some useful theoretical references for understanding the mechanism of action, designing new curcumin-related compounds with anticancer activity and predicting their activities prior to synthesis.     

DFT‐based QSAR study and molecular design of AHMA derivatives as potent anticancer agents

A quantitative structure–activity relationship (QSAR) of 3‐(9‐acridinylamino)‐5‐hydroxymethylaniline (AHMA) derivatives and their alkylcarbamates as potent anticancer agents has been studied using density functional theory (DFT), molecular mechanics (MM+), and statistical methods. In the best established QSAR equation, the energy (E_NL) of the next lowest unoccupied molecular orbital (NLUMO) and the net charges (Q_FR) of the first atom of the substituent R, as well as the steric parameter (MR₂) of subsituent R₂ are the main independent factors contributing to the anticancer activity of the compounds. A new scheme determining outliers by “leave‐one‐out” (LOO) cross‐validation coefficient (q) was suggested and successfully used. The fitting correlation coefficient (R²) and the “LOO” cross‐validation coefficient (q²) values for the training set of 25 compounds are 0.881 and 0.829, respectively. The predicted activities of 5 compounds in the test set using this QSAR model are in good agreement with their experimental values, indicating that this model has excellent predictive ability. Based on the established QSAR equation, 10 new compounds with rather high anticancer activity much greater than that of 34 compounds have been designed and await experimental verification. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

取代喹啉类化合物抗菌活性的定量构效关系及分子设计

采用密度泛函理论(DFT)和逐步回归分析法对15种新合成的取代喹啉类化合物进行了定量构效关系(QSAR)研究. 在B3LYP/6-31G(d,p)水平上计算了取代喹啉的量子化学参数, 通过逐步多元回归分析筛选出影响抗菌活性的主要因素, 建立了定量构效关系方程, 并用留一法交叉分析了模型的稳定性及预测能力. 结果表明, C5的亲核电子密度fNC5及C9-N1的键级BC9-N1是影响喹啉类化合物抗金黄色葡萄球菌活性的主要因素, 所得模型对该类化合物抗菌活性有较好的预测效果. 同时基于QSAR研究结果设计了4个活性较高的新喹啉衍生物.     

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.     

抗癌性吲哚喹唑啉衍生物的定量构效关系

用量子化学密度泛函理论(DFT)、分子力学(MM＋)及回归分析方法,对一系列抗癌性吲哚喹唑啉衍生物进行了定量构效关系(QSAR)的研究.通过回归分析,筛选了影响抗癌活性的主要因素,建立了定量构效关系方程.结果表明,化合物的最低未占据分子轨道(LUMO)与最高占据分子轨道(HOMO)之间的能量差(ΔεL-H)、分子的疏水性(lgP)以及环D上的总电荷(ΣQD)和环D上R1取代基的第一个原子的净电荷(QFR1)是影响化合物抗癌活性的主要因素.所得模型对化合物抗癌活性有较好的预测效果. 同时, 与ΔεL-H密切相关的LUMO轨道能量及共轭平面面积对药物的DNA-结合及其活性起着十分重要的作用,可通过选取具有较强的拉电子性质同时又能与本系列化合物的骨架形成更大共轭体系的取代基R1,设计抗癌活性较高的化合物.     

咪唑啉衍生物缓蚀剂的定量构效关系及分子设计

采用量子化学密度泛函理论(DFT)及线性回归分析方法, 对十一烷基咪唑啉衍生物缓蚀剂抗H2S、CO2腐蚀性能进行了定量构效关系(QSAR)研究. 通过回归分析, 筛选出了影响缓蚀剂缓蚀性能的主要因素, 建立了QSAR模型, 并使用留一法交叉验证对模型的稳定性及预测能力进行了分析. 结果表明, 电子转移参数△N、咪唑环上非氢原子静电荷之和∑Qring及分子极化率α对咪唑啉类缓蚀剂的缓蚀性能有很大的贡献, 所得模型的拟合相关系数(R2)和交叉验证相关系数(q2)分别为0.924 和0.917, 模型对此类缓蚀剂抗H2S、CO2腐蚀性能具有较好的预测效果. 应用QSAR研究结果进行了分子设计, 在理论上提出了一些具有较高抗H2S、CO2腐蚀性能的新型咪唑啉衍生物, 为实验工作者合成新型缓蚀剂提供理论参考.     

核因子κB活性抑制剂定量构效关系

The electronic structures, geometric structures and some molecular properties (generalized structural indexes) of quinazoline derivatives were computed by using density functional theory and molecular mechanism methods to investigate the quantitative structure-activity relationship (QSAR) of the inhibitory activity toward the nuclear factor kappa B. Via a stepwise regression analysis, some main factors affecting the activity of the compounds were factored out, and then the QSAR equation was effectively established. It was found that the hydrophobic parameter of the substituent on ring D is the main factor affecting the inhibitory activity of the compound. The analysis indicated, the larger the hydrophobic parameter, the higher the inhibitory activity of the compound. In addition, the net charge of the first atom and the stereoscopic parameter (MR1) of the substituent R1 on A-ring as well as the net charge of C3 are closely correlated with the inhibitory activity of the compound. In order to test the predicted results of the QSAR equation, we adopted the “leave one out” cross-validation , and found that the calculated coefficient q2 was rather high and the predicted results were both accurate and reliable. Such facts show that the obtained equation has great predictive ability. The above results can offer an important theoretical guide in the search for new quinazoline derivatives with higher inhibitory activity, and in an analysis of their action mechanisms. It is noteworthy that this scheme would be very advantageous in factoring out precursors with excellent inhibitory activity via the computer ADDIT molecule-design, since all parameters in the QSAR equation are computable and controllable.     

2D/3D-QSAR Studies of [1,2,4]Triazolo[1,5-a]pridinylpyridine Derivatives as Potent Anticancer Agents

By using a combined method of density functional theory(DFT), molecular mechanics(MM2) and statistics for two-dimensional(2D), as well as the comparative molecular field analysis(Co MFA) and comparative molecular similarity index analysis(Co MSIA) methods for three-dimensional(3D), theoretical studies on 2D/3D quantitative structure-activity relationships(QSAR) of 22 novel compounds of [1,2,4]triazolo[1,5-a] pyridinylpyridines acting as PI3 K inhibitors against the human colon carcinoma cell line(HCT-116) have been performed. Both the 2D- and 3D-QSAR models established from the random 18 compounds in training set show significant statistical quality and satisfactory predictive ability(R2 = 0.821, q2 = 0.773 for 2D-QSAR, R2 = 0.966, q2 = 0.668 for Co MFA, R2 = 0.979, q2 = 0.753 for Co MSIA). The combined 2D- and 3D-QSAR studies suggest that the moderate-size, hydrophilic and electron-withdrawing group at R1 position, the bulky and hydrophobic group at R2 position, and the minor, hydrophobic, H-bond donor and electron-donating group at R3 position would enhance the anticancer activities. These obtained results help to insight into the action mechanism, and will serve as a basis for the design of new potent anticancer agents.     

苯环己胺类药物的QSAR研究

采用量子化学密度泛函DFT/B3LYP方法,计算了30个苯环己胺(PCA)类化合物的电子结构参数,结合Chemoffice8.0软件计算的基于距离的拓扑参数,用逐步多元线性回归法建立了其结构参数与药物活性之间的定量结构-活性关系(QSAR).所建模型的复相关系数R=0.9250;用留一法(leave-one-out,L...     

用拓扑指数和神经网络研究有机污染物的生物富集因子

在修正Randic的分子连接性指数和连接矩阵的基础上, 定义新型分子连接性指数(mF), 并计算了239种有机污染物的分子连接性指数(mF). 用其1F构建了239种有机污染物生物富集因子(lgBCF)的QSAR模型, 该模型判定系数(R2)及逐一剔除法(LOO)的交互验证系数(Q2)分别为0.747和0.742. 而用1F和4个电性距离矢量(Mk)构建的五元QSAR模型的R2及Q2分别为0.829和0.819. 结果表明, 从统计学的角度, 该模型具有高度的稳定性及良好预测能力. 从此模型可知, 有机污染物BCF的主要影响因素是—C—, ＞C—, —O—, —S—, —X等分子结构碎片以及分子的柔韧性、折叠程度等空间因素. 将5个结构参数作为人工神经网络的输入层结点, 采用5∶26∶1的网络结构, 利用BP算法, 获得了一个令人满意的QSAR模型, 其R2和标准偏差s分别为0.987和0.157, 表明lgBCF与这5个参数具有良好的非线性关系. 从上可见, 新建的连接性指数1F以及电性距离矢量与有机物的生物富集因子具有良好的相关性, 可望在物质构效关系研究中获得广泛的应用.     

QSAR and 3D-QSAR studies of the diacyl-hydrazine derivatives containing furan rings based on the density functional theory

QSAR studies of 27 diacyl-hydrazine derivatives containing furan rings were conducted and compared with the DFT method and AM1-MOPAC method. q ² values of 0.61 and 0.40 validated the predictability and reliability of eq. (5) from the DFT method were higher than those of eq. (6) from the AM1-MOPAC method. The DFT-optimized conformations and ESP-fitting charges of the target compounds were also used for 3D-QSAR analysis, including CoMFA and CoMSIA. The leave-one-out cross-validation correlation coefficient and the good correlation between the predicted and experimental activities of excluded test compounds revealed that CoMFA and CoMSIA models were robust. The QSAR results were consistent with the 3D-QSAR results, indicating that the electrostatic and hydrophobic properties of the target compounds were significant to the biological activity. These models are useful tools for predicting the larvicidal activities of new compounds and designing new specific insect growth regulators.     

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.     

Investigation of anticancer activity of macrocyclic Schiff bases by means of 4D-QSAR based on simplex representation of molecular structure

Influence of the molecular structure of macrocyclic pyridinophanes, their analogues and some other compounds on anticancer activity (Leukemia, central nervous system (CNS) cancer, prostate cancer, breast cancer, melanoma, non-small cell lung cancer, colon cancer, ovarian cancer, renal cancer) was investigated by means of a new 4D-QSAR approach based on the simplex representation of molecular structures (SiRMS). For all the investigated molecules, the 3D structural models were first created and the set of conformers (fourth dimension) was used. Each conformer was represented as a system of different simplexes (tetratomic fragments of fixed structure, chirality and symmetry). Statistic characteristics of the QSAR partial least squares (PLS) models were satisfactory (correlation coefficient r=0.990-0.861; cross-validation coefficient CVR=0.914-0.633). The molecular fragments increasing and decreasing anticancer activity were defined. This information may be useful for the design and direct synthesis of novel anticancer agents.     

氟喹诺酮三唑酮衍生物抗增殖活性的CoMFA模型

应用比较分子力场分析法(CoMFA)研究了18种氟喹诺酮三唑啉酮衍生物对人白血病HL60细胞的体外抗增殖活性(pH)。建立的模型在高相关系数值(R2=0.969)和交叉验证系数值(R2cv=0.473)方面显示出良好的相关和预测能力。空间场和静电场对pH的贡献分别为58.5%和41.5%。基于CoMFA等高线图,揭示了该系列化合物抗增殖活性的一些关键结构因素,如疏水作用、空穴契合、库仑力及氢键等。这些结果为理解其作用机制、设计具有高抗增殖活性的新型氟喹诺酮三唑啉酮类化合物以及预测其活性提供了有益的理论参考。     

Application of Density Functional Theoretic Descriptors to Quantitative Structure-Activity Relationships with Temperature Constrained Cascade Correlation Network Models of Nitrobenzene Derivatives

IntroductionNitrobenzene derivatives have been used as organ-ic chemical materials and intermediates for many yearsin the chemical industry. Many of those chemicals arereleased into environment and especially into aquaticsystems, and thus have a high pote…     

一种新的氨基酸描述符及其在肽QSAR中的应用

从20种天然氨基酸的41个randic molecular profiles非零描述符、44个eigenvalue based indices非零描述符和47个walk and path counts非零描述符分别进行主成分分析,得出一种新的氨基酸描述符-SVREW。将其应用于血管紧张素转化酶(ACE)抑制二肽和ACE抑制三肽、苦味二肽和苦味四肽、后叶催产素类似物、HLA-A*0201限制性CTL表位肽的结构表征,应用多元线性回归(MLR)建立定量构效关系模型,同时采用内部与外部双重验证的方法验证模型的稳定性。所建ACE抑制二肽、ACE抑制三肽、苦味二肽、苦味四肽、后叶催产素类似物、HLA-A*0201限制性CTL表位肽的模型复相关系数(R2cum)分别为0.994,0.797,0.948,0.878,0.686,0.720;留一法交互校验复相关系数(R2cv)分别为0.955,0.859,0.879,0.958,0.796,0.843;外部样本校验相关系数(Q2ext)分别为0.990,0.954,0.890,0.950,0.748,0.773。经研究表明SVREW描述符用于肽分子结构表征所建模型的稳定性与预测能力均较好,有望成为多肽定量构效关系研究中一种有效的结构表征方法,可对新药物的发现和研究提供指导。