新型二芳基三嗪类抗锥体虫病化合物的三维定量构效关系研究

目的 建立具有预测能力的新型二芳基三嗪类抗锥体虫病化合物三维定量构效关系（3D-QSAR）模型。方法 通过对具有抗锥体虫活性的二芳基三嗪类化合物库进行结构分析,利用比较分子场分析法（CoMFA）和比较分子相似性指数分析法（CoMSIA）,建立3D-QSAR模型。结果 模型具有较高q²（q_CoMFA²=0.697,q_CoMSIA²=0.561）和r²（r_CoMFA²=0.998,r_CoMSIA²=0.966）值,表明2组模型具有较高的拟和能力及预测能力。结论 建立的CoMFA和CoMSIA模型均具有良好的预测能力,为设计更高活性的新型二芳基三嗪类抗锥体虫病化合物提供了理论依据和研究方向。     

噻嗪类11β-羟类固醇脱氢酶抑制药三维定量构效关系研究

摘 要 目的：通过构建噻嗪类11β-羟类固醇脱氢酶（11β-HSD）抑制药的三维定量构效关系(3D QSAR)模型,用于其结构改造及发现具有更高生物活性的11β-HSD抑制药。方法: 基于骨架叠合的模式,采用比较分子力场分析（CoMFA）的方法,构建噻嗪类衍生物定量构效关系模型,并用分子对接的方法对已构建的3D QSAR模型进行验证。结果: 得到了高精度的11β-HSD抑制药的3D-QSAR模型（CoMFA:q²=0.346,r²=0.850;其中q²为交叉验证系数,r²为非交叉验证系数）。结论:本文构建的3D QSAR模型可为11β-HSD抑制药骨架各个位点的化学修饰,实施定向合理设计,为开发新型抗2型糖尿病药物提供理论基础。     

喹啉酮类小分子p53-MDM2结合抑制剂3D-QSAR研究

目的 设计、合成高活性的小分子p53-MDM2结合抑制剂,建立具有预测能力的3D-QSAR模型。方法 采用分子模拟软件Sybyl,利用比较分子场方法(CoMFA)、比较分子相似性指数法(CoMSIA),选择已报道的具有p53-MDM2结合抑制活性的一类有相同母核的21个异喹啉酮衍生物作为训练集,7个作为预测集进行3D-QSAR模型的建立和验证。结果 模型具有较高q²(q²_CoMFA=0.545,q²_CoMSIA=0.528)和r2(r²_CoMFA=0.984,r²_CoMSIA=0.972)值,表明2组模型具有较高的拟和能力及预测能力。结论 该模型具有较高的预测能力,为设计、合成高活性的小分子p53-MDM2结合抑制剂提供了理论依据。     

阿片类药物透过血脑屏障的三维构效研究

目的:建立药物透过血脑屏障的三维构效模型,为药物分子设计提供理论依据。方法与结果:利用比较分子力场分析方法建立了阿片类药物透过血脑屏障的三维定量构效模型,该模型有较高的预测能力,交叉验证系数r²_cv=0.718,相关系数r²=0.978,F₃,7=67.902,标准偏差SE=0.209。结论:根据CoMFA模型系数等势图,解释了该类药物透过血脑屏障的构效关系。     

噻唑-吡唑啉衍生物作为EGFR抑制剂的3D-QSAR和分子对接模型研究

目的 建立EGFR抑制剂结构和活性之间的关系模型,基于对分子活性产生影响的重要结构性因素的信息,设计新的抑制剂分子并预测其活性,为抑制剂分子的设计提供依据。方法 使用Discovery Studio 2019软件进行3D-QSAR的研究以及偏最小二乘的计算;利用Autodock进行分子对接;使用LigPlot研究二维相互作用。结果 模型具有较高的q²(0.521),和r²(r²_training=0.993,r²_test=0.916,r²_blind=0.940),表明模型具有较高的预测能力和拟合能力。结论 预测结果表明,新设计的化合物活性较高,为EGFR抑制剂分子的设计提供了参考。     

2-苯氧茚酮类乙酰胆碱酯酶抑制剂的3D-QSAR研究

目的研究2-苯氧茚酮类乙酰胆碱酯酶抑制剂的三维定量构效关系。方法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)对结构与活性的关系进行研究。结果CoMFA模型表明立体场和静电场对活性的贡献分别为0.805和0.195;CoMSIA模型阐明疏水场和氢键场对活性也有一定的影响。结论两种3D-QSAR模型都显示出相当高的预测能力,CoMFA和CoMSIA的交叉验证值q2分别为0.881和0.918,通过对两种3D-QSAR模型等势图的分析,可为开展进一步的药物设计和结构优化提供理论指导和依据。     

黄酮类化合物对细胞色素P450 CYP1A2的抑制作用及其构效关系研究

利用本实验室已建立的体外肝微粒体模型， 测定36个黄酮类单体化合物对人细胞色素P450 CYP1A2的抑制活性， 并使用三维定量构效关系方法研究化合物的分子结构参数与其抑制活性之间的关系。CoMSIA模型证实黄酮类化合物的结构参数与其CYP1A2抑制活性存在明显的相关性(模型的相关系数R²为0.948)， 且有良好的预测能力(交叉验证相关系数q²为0.630)， 同时使用“留五法”证实模型的稳定性和可靠性。结果表明， 相对于黄酮， α-萘黄酮的π-π共轭体系更有利于提高化合物的抑制活性。根据获得的模型的三维等势图， 在α-萘黄酮基础上， 6、3′、4′位引入带正电基团或是疏水基团，同时5位引入带负电基团，能有效改善化合物的CYP1A2抑制活性。     

噻唑烷二酮和芳酮酸类PPARγ激动剂三维定量构效关系研究

目的建立PPARγ激动剂-噻唑烷二酮和芳酮酸类化合物的三维定量构效关系,为设计高活性PPARγ激动剂提供结构信息。方法与结果用比较分子力场分析方法得到噻唑烷二酮和芳酮酸类化合物CoMFA模型,其交叉验证相关系数R²=0.656,非交叉验证相关系数R²=0.982,F_10,37=201.1,绝对误差SE=0.115。结论从CoMFA系数等势图中揭示芳酮酸类化合物较噻唑烷二酮类化合物活性更高的原因,提示芳酮酸类化合物与PPARγ结合时形成了不同于BRL-PPARγ复合物晶体的结合腔。     

蛋白酪氨酸磷酸酶1B抑制剂的分子对接及三维定量构效关系研究

目的对文献报道的一系列芳环取代噻唑类蛋白酪氨酸磷酸酶1B(PTP1B)抑制剂进行分子对接及三维定量构效关系(3D-QSAR)研究。方法应用Surflex-Dock进行分子对接结合模式研究,并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研究,建立具有良好预测能力的3D-QSAR模型。结果对接结果表明,该类结构可以很好地占据PTP1B的3个关键结合位点,大大提高了抑制剂与酶的亲和力。所建立的CoMFA模型交叉验证系数q~2为0.644,CoMSIA模型交叉验证系数q~2为0.719。结论获得的CoMFA和CoMSIA模型具有可靠的预测能力,可应用于指导该类化合物的设计。     

川芎嗪酯类衍生物的3D-QSAR研究

目的建立预测模型,进行合理的药物设计和修饰。方法应用构象系统搜索程序确定23个2-取代酰氧甲基-3,5,6-三甲基吡嗪衍生物的可能活性构象,并以此活性构象为模板构建了这23个小分子化合物的三维结构,采用CoMFA及CoMSIA法对衍生物进行系统的三维定量构效关系分析。结果与结论CoMFA模型交叉验证系数q2=0.694,回归系数R2=0.994,SEE=0.023,F=376.924。CoMSIA模型交叉验证系数q2=0.657,回归系数R2=0.987,SEE=0.034,F=166.815。两种方法得到的构效关系模型都具有较好的预测能力。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分子场特征对化合物活性的影响,为该类化合物进一步结构优化提供了有价值的参考。     

3D-QSAR study of pyrrolidine derivatives as matrix metalloproteinase-2 inhibitors

In order to develop potent inhibitors of matrix metalloproteinase-2(MMP-2) as anticancer agents, a three-dimensional quantitative structure–activity relationship (3D-QSAR) model was established by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. This study correlates the MMP-2 inhibitory activities of 67 pyrrolidine derivatives to steric, electrostatic, hydrophobic, and hydrogen-bond donor and acceptor fields. After using two different molecular alignments, both CoMFA and CoMSIA models resulted in good statistical predictions, a case in point being their high q ² values of between 0.757 and 0.843. The CoMFA and CoMSIA models established herein will be helpful in understanding the structure–activity relationship of pyrrolidine derivatives as well as in the design of novel derivatives with enhanced MMP-2 inhibitory activity.     

Investigations and design of pyridine-2-carboxylic acid thiazol-2-ylamide analogs as methionine aminopeptidase inhibitors using 3D-QSAR and molecular docking

Methionine amino peptidases (MetAPs) are metalloproteases that remove co-translational N-terminal methionine from nascent polypeptide chains. Due to their essential role in protein synthesis, MetAPs are considered as potential targets for antibacterial drugs. In the present work, three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were carried out on a series of pyridine-2-carboxylic acid thiazol-2-ylamide-based MetAP inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models were developed using 30 training set molecules. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients (q ²) of 0.799 and 0.704 and conventional correlation coefficients (r ²) of 0.989 and 0.954, respectively. These inhibitors were docked into MetAP active site. The CoMFA and CoMSIA field contour maps correlate well with the structural characteristics of the binding pocket of MetAP active site. Using the knowledge of structure–activity relationship and receptor–ligand interactions from 3D-QSAR model and the docked complexes, four new pyridine-2-carboxylic acid thiazol-2-ylamide analogs were designed. These analogs exhibit significantly better predicted activity than the reported molecules. The present work has implications for the development of novel antibiotics as potent MetAP inhibitors.     

3-羧基香豆素类乳酸转运抑制剂的三维定量构效关系研究

目的 建立3-羧基香豆素类乳酸转运抑制剂三维定量构效关系(3D-QSAR)模型.方法 采用分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)来研究3-羧基香豆素类乳酸转运抑制剂的构效关系.结果 建立了合理、可靠的3-羧基香豆素类乳酸转运抑制剂CoMFA(q2=0.630,r2 =0.994,rpred2=0.909)和CoMSIA(q2=0.676,r2=0.972,rpred2 =0.574)模型.结论 构建的3D-QSAR模型揭示了3-羧基香豆素类化合物的结构和生物活性间的关系,可为该类乳酸转运抑制剂的进一步优化设计提供科学依据.     

3D-QSAR and docking studies on pyridopyrazinones as BRAF inhibitors

BRAF has become an important and exciting therapeutic target toward human cancer. 3D-QSAR and docking studies were performed to explore the interaction of the BRAF with a series of pyridopyrazinones. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were carried out in terms of their potential for predictability. The CoMFA and CoMSIA models using 71 compounds in the training set gave r _cv² values of 0.567 and 0.662, r ² values of 0.900 and 0.907, 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. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained by 3D-QSAR models may be useful to design novel potential BRAF inhibitors.     

Pharmacophore-based 3D-QSAR of HIF-1 inhibitors

(Aryloxyamino)benzoic acids and nicotinic/isonicotinic acids represent an important new class of small molecules that inhibit the activation of Hypoxia-Inducible Factor (HIF)-1. In order to understand the factors affecting inhibitory potency of HIF-1 inhibitors, 3 dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed. Since no receptor structure are available, the pharmacophore-based alignment was used for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The CoMFA and CoMSIA models gave reasonable statistics (CoMFA: q² = 0.564, r²=0.945; CoMSIA: q² = 0.575, r²=0.929). Both CoMFA and CoMSIA results indicate that the steric interaction is a major factor, while CoMSIA suggests importance of hydrogen bonding. These findings about steric and H-bonding effects can be useful to design new inhibitors. Equally contributed in this work.     

Cytotoxic Activity and Three-Dimensional Quantitative Structure Activity Relationship of 2-Aryl-1,8-naphthyridin-4-ones

A series of substituted 2-arylnaphthyridin-4-one analogues, which were previously synthesized in our laboratory, were evaluated for their in vitro cytotoxic activity against human lung cancer A549 and human renal cancer Caki-2 cells using MTT assay. Some compounds (11, 12, and 13) showed stronger cytotoxicity than colchicine against both tumor cell lines, and compound 13 exhibited the most potent activity with IC₅₀ values of 2.3 and 13.4 µM, respectively. Three-dimensional quantitative structure activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed. Predictive 3D-QSAR models were obtained with q² values of 0.869 and 0.872 and r²_ncv values of 0.983 and 0.993 for CoMFA and CoMSIA, respectively. These results demonstrate that CoMFA and CoMSIA models could be reliably used in the design of novel cytotoxic agents.     

3D-QSAR study using CoMFA and CoMSIA methods for a series of histone H3 phosphorylation inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis of inhibitory activities for a series of pyrrolotriazine derivatives against histone H3 phosphorylation (pHH3) was performed using comparative of molecular field analysis (CoMFA) and comparative of molecular similarities indices analysis (CoMSIA) techniques. 62 derivatives were used to establish and validate two models by considering a high deviation in biological activities and structural variations. Optimum CoMFA and CoMSIA models obtained from the training set were statistically significant with cross-validated correlation coefficients q ² of 0.551 and 0.621, and conventional correlation coefficients (r ²) of 0.999 and 0.995, respectively. The predicted correlation coefficients of test set (R ²) for CoMFA and CoMSIA were 0.835 and 0.918, respectively. Two models obtained provide guidelines to trace the features that really matter chiefly with respect to the design of novel pyrrolotriazine derivatives.