Enantioselectivity of epoxide hydrolase catalysed oxirane ring opening: a 3D QSAR study

A 3D QSAR analysis (quantitative structure activity relationships) of a set of 2,2-disubstituted epoxides, substrates for epoxide hydrolases originating from four different organisms, was conducted by CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis), with respect to the enantioselective ring opening to the corresponding vicinal diol. Structural variations of the substrates include alkyl chains of different lengths, unsaturated moieties ((E)- and (Z)-alkenyl, alkinyl, aryl) and electronegative groups (ether oxygens, halogen atoms) at different locations within the 2-substituent group. Generally, all four organisms, namely Rhodococcus ruber NCIMB 11216, Rhodococcus ruber DSM 43338, Rhodococcus ruber DSM 44540 and Rhodococcus ruber DSM 44539, preferentially react with the (S)-enantiomer of the epoxide. Enantioselectivities (enantiomeric ratio, lnE values) show a rather large variation, ranging from almost no (lnE<1) to nearly complete selectivity (lnE>5.3). In addition, the response of the epoxide hydrolases stemming from the four organisms towards structural modifications of the substrate is different. Models for the enantioselectivity (enantiomeric ratio, ln E values) obtained by CoMFA and CoMSIA are of different but reasonable predictive power, e.g., q² _CV=0.701 and r²=0.937 for the CoMFA model of Rhodococcus ruber DSM 43338. Enantiomeric ratios for the test molecules can be well predicted. Plots of steric and electrostatic CoMFA (CoMSIA) fields allow conclusions to be drawn for the choice of the most suitable organism for a specific type of substrate.     

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.     

两类促肾上腺皮质释放激素(CRH)拮抗剂的分子场分析

采用比较分子相似性指数分析方法(CoMSIA)及比较分子场分析方法(CoMSIA)研究了两组CRH拮抗剂结构与活性的关系。在两种方法中,都考虑了静电场、立体场以及氢键场对构效关系的影响,结果表明采用CoMSIA得到构效关系模型要明显优于采用CoMFA得到的构效关系模型,在CoMSIA计算中,当引入疏水场时,三维构效关系模型能得到明显的改善,通过这个三维构效关系模型,可以较为精确地预测化合物的活性。通过分析分子场等值面图在空间的分布,可以观察到叠合分子周围的立体、静电以及疏水特征对化合物活性的影响。     

二氢吡啶类化合物的三维定量构效关系

通过分子力学和量子化学计算,得出两种二氢吡啶衍生物的低能构象,再应用比较分子力场分析方法(CoMFA)和比较分子相似性指数分析方法(CoMSIA)分别对两种构象的43个二氢吡啶衍生物进行3D-QSAR研究. 计算结果表明,用两种方法建立的两种构象的构效关系模型均有较好的预测能力.通过分析CoMFA和CoMSIA的系数等势图,直观地了解二氢吡啶衍生物的结构对生物活性的影响,为进一步设计高活性的二氢吡啶衍生物提供一定的理论依据.     

肿瘤血管阻断剂黄酮-8-乙酸类衍生物的三维定量关系研究

选择了肿瘤血管阻断剂黄酮-8-乙酸类衍生物, 采用比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法进行三维定量构效关系的研究. 33个化合物建立了预测模型, 6个化合物作为训练集进行模型验证. 其中CoMFA模型的交叉验证系数q²＝0.621, 最佳主成分数为4, 标准偏差s_press＝0.345, 非交叉相关系数r²＝0.945, 标准偏差s＝0.131, F＝120.455. CoMSIA模型的交叉验证系数q²＝0.700, 最佳主成分数为5, 标准偏差s_press＝0.312, 非交叉相关系数r²＝0.946, 标准偏差s＝0.133, F＝94.193. 计算结果表明, 构建的CoMFA和CoMSIA模型具有良好的预测能力, 可用于指导该类化合物的设计.     

Pharmacophore mapping of flavone derivatives for aromatase inhibition

Aromatase, which catalyses the final step in the steroidogenesis pathway of estrogen, has been target for the design of inhibitor in the treatment of hormone dependent breast cancer for postmenopausal women. The extensive SAR studies performed in the last 30 years to search for potent, selective and less toxic compounds, have led to the development of second and third generation of non-steroidal aromatase inhibitors (AI). Besides the development of synthetic compounds, several naturally occurring and synthetic flavonoids, which are ubiquitous natural phenolic compounds and mediate the host of biological activities, are found to demonstrate inhibitory effects on aromatase. The present study explores the pharmacophores, i.e., the structural requirements of flavones (Fig. 1) for inhibition of aromatase activity, using quantitative structure activity relationship (QSAR) and space modeling approaches. The classical QSAR studies generate the model (R (2) = 0.924, Q (2) = 0.895, s = 0.233) that shows the importance of aromatic rings A and C, along with substitutional requirements in meta and para positions of ring C for the activity. 3D QSAR of Comparative Molecular Field Analysis (CoMFA, R (2) = 0.996, [Formula: see text]) and Comparative Molecular Similarity Analysis (CoMSIA, R (2) = 0.992, [Formula: see text]) studies show contour maps of steric and hydrophobic properties and contribution of acceptor and donor of the molecule, suggesting the presence of steric hindrance due to ring C and R'-substituent, bulky hydrophobic substitution in ring A, along with acceptors at positions 11, and alpha and gamma of imidazole ring, and donor in ring C favor the inhibitory activity. Further space modeling (CATALYST) study (R = 0.941, Delta( cost ) = 96.96, rmsd = 0.876) adjudge the presence of hydrogen bond acceptor (keto functional group), hydrophobic (ring A) and aromatic rings (steric hindrance) along with critical distance among features are important for the inhibitory activity.     

STAT3环烷烃并噻吩类衍生物抑制剂的三维定量构效关系研究

本文对STAT3抑制剂的化学结构与生物活性之间的关系进行研究。采用三维定量构效关系(3D-QSAR)中的比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法针对52个STAT3抑制剂建立3D-QSAR模型,阐明了抑制剂化学结构与其生物活性之间的关系。所构建的CoMFA模型交叉验证系数为0.548,非交叉验证系数为0.754,标准偏差为0.278,显著系数为58.297;所构建的CoMSIA模型交叉验证系数为0.892,非交叉验证系数为0.597,标准偏差为0.192,显著系数为57.794。结果显示CoMFA和CoMSIA模型具有良好的稳定性和预测能力。3D-QSAR模型等势图提供的相关场信息对新型STAT3抑制剂的设计具有指导意义。     

橙酮类DRAK2抑制剂的3D-QSAR及分子对接研究

本文对橙酮类DRAK2抑制剂的化学结构与生物活性之间的关系进行研究。采用三维定量构效关系（3D-QSAR）中的比较分子力场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）方法针对59个DRAK2抑制剂建立3D-QSAR模型,阐明了抑制剂化学结构与其生物活性之间的关系。所构建的CoMFA模型交叉验证系数（q²）为0.625,非交叉验证系数（r²）为0.811,标准偏差（S）为0.365,Fisher检验值（F）为59.971;所构建的CoMSIA模型q²为0.62,r²为0.846,S为0.333,F值为56.453。内部和外部验证参数表明,生成的3D-QSAR模型均具有良好的预测能力和显著的统计学可靠性。分子对接实验与等势图的一致性,进一步表明本次分子模拟是可靠的。本研究对发现新型的潜在的更高活性的橙酮类DRAK2抑制剂具有指导意义。     

Use of 3D QSAR to investigate the mode of binding of pyrazinones to HIV-1 RT

Abstract  Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on the docked conformation were performed for 24 pyrazinone derivatives. All compounds were docked into the wild-type HIV-1 RT binding pocket and the lowest-energy docked configurations were used to construct the 3D QSAR models. The CoMFA and CoMSIA models enable good prediction of inhibition by the pyrazinones, with  = 0.703 and 0.735. Results obtained from CoMFA and CoMSIA based on the docking conformation of the pyrazinones are, therefore, powerful means of elucidating the mode of binding of pyrazinones and suggesting the design of new potent NNRTIs. Graphical Abstract