N—亚硝基化合物的结构／致癌活性的三维构效关系研究

用比较力场分析研究了Ｎ－亚硝基化合物的结构与致癌活性的关系，考察了网络结构和探针原子对结果的影响。结果表明，立体效应和静电作用场是描述其致癌活性和进行结构性能关系研究的最重要的结构参数。     

句法模式识别研究芳烃致癌(一)——计算方法和经验规律

用句法模式识别研究多环芳烃分子图形与致癌活性的关系,总结出它包含致癌信息的特征曲线,并研究了分子伸展度和角品度对致癌活性的影响。     

N-亚硝基化合物结构-致癌活性的相关性研究

Ｎ－亚硝基化合物结构－致癌活性的相关性研究许禄,姚瑜元（中国科学院长春应用化学研究所应用谱学开放实验室,长春,１３００２２）关键词Ｎ－亚硝基化合物,半经验量化方法,构效关系目前已发现的Ｎ－亚硝基化合物约３００种中多数具有致癌活性。化学家和生物学家对该...     

致癌有机化合物分子片段致癌机理的研究

以有机物的分子连接性指数和微扰分子轨道指数作结构、能量参数,从分析致癌有机物分子片段与生物遗传基因DNA链互补碱基对发生共价交联的构效角度出发,首次得出产生碱基移码型或碱基置换型化学致癌的主要过程是化合物分子片段中活性原子与DNA互补碱基对间氢键的共价结合,显示致癌活性的充分必要条件是碱基对G≡C间有两个氢键与致癌分子片段发生特异交联.对100余种已知致癌物的致癌分子片段进行计算分析,成功地获得了有机物分子片段定量结构-致癌活性的估测模式.     

对称二烷基亚硝胺第二活性区对DNA烷化作用机理的AM1研究

多年来的实验结果表明,多数亚硝基化合物(NCC)是明显致癌的,有些是强烈致癌的。NCC是一种间接致癌剂,需要通过代谢而发挥致癌作用。一般认为NCC在混合功能氧化酶作用下经代谢α-位羟基化,脱去一侧烃基形成具有亲电活性中心的烷基重 氮化合物作为"最终致癌剂"并烷化DNA而引发癌症^[1]。但是单纯用α-位代谢的活性未能满意地解释NCC的结构变化对其致癌活性的影响。我们实验室将"双区理论"的观点应用于NCC致癌机理的研究,提出了NCC经代谢形成具有两个亲电活性中心的最终致癌剂,在DNA互补碱基对间形成横向交联而发挥致癌作用的观点,用模式识别方法对153种当时已有动物致癌活性试验数据的NCC进行5级致癌强度分类,得到了判对率为97.3%的良好一致性。并且提出,在单氧酶作用下,NCC羟基化的β-位或有邻基参与作用的γ-位可以作为第二个亲电活性中心^[2-3]。这一观点不仅在结构致癌活性关系研究中发挥了重要作用,而且正在被越来越多的实验结果所证实^[4]。     

句法模式识别研究芳烃致癌(二)——特征曲线的理论解释

从M区键级、超离域能和致癌活性的对应关系,结合致癌反应湾区历程对用句法模式识别方法找出的多环芳烃强致癌信息特征曲线进行了理论解释。     

芳胺结构致癌活性关系的双区理论定量阐释

本文将双区理论定量地推广到63种芳胺的定量结构致癌活性关系上,借氨基亚氮阳离子与环上环氧化物的双官能烷化作用的观点,建立了芳胺结构与致癌性能间的定量关系式,计算与实验的一致达98％。从而将芳胺类难以捉摸的致癌性能变化,表达为可以理解的结构化学活性关系。     

3,5-二甲基-亚硝基哌嗪代谢物对DNA烷化作用的理论研究

用从头计算法在MP2/6-311＋G(d,p)水平上对3,5-二甲基-亚硝基哌嗪(DMNP)及其类似物经代谢生成DNA烷化剂的机理进行了研究. 探讨了N’原子上取代基的变化对DMNP代谢物生成α-位和γ-位两个烷化中心的影响, 解释了两个烷化中心的生成活性与化合物的致癌性之间的关系. 结果表明, α-位和γ-位代谢物越容易生成活泼亲电中间体, 其母体化合物的致癌活性越高. 但如果有一个烷化中心丧失活性, 就会明显减弱化合物的致癌活性. 因此, DMNP类化合物的致癌性取决于其α-位和γ-位的协同烷化作用, 在评价DMNP的致癌强度时需同时考虑两个烷化中心的烷化能力以及二者之间的关系.     

苯甲酰胺类化合物的结构/活性的定量构效关系研究

用分子连接性指数及比较分子力场分析分别研究了苯甲酰胺类化合物的结构与抗炎活性的关系，结果表明，三维空间上立体效应是描述该类化合物的抗炎活性和进行结构与性能关系研究的最重要的结构参数。     

基于配体结构的Grb2-SH2抑制剂的结构优化:更高的活性、更少的电荷、更低的肽性

生长因子受体结合蛋白2(Grb2)在致癌基因Ras活化的信号传导通路中起着关键作用,目前被广泛认为是抗肿瘤药物设计的优秀靶标.对Grb2-SH2抑制剂的研究进展进行了综述,主要针对关键残基磷酸酪氨酸的高电荷性和多肽结构的低生物相容性两个缺陷,基于天然配体与Grb2-SH2相互作用的结构特征,围绕提高活性和简化结构开展的系统构效关系和合理结构优化研究,为进一步开发磷酸酪氨酸介导的Grb2-SH2抑制剂成为新型抗肿瘤药物提供结构和理论基础.     

化合物的空间取向对CoMFA结果的影响

Our work shows that different compound orientations have different results in Comparative Molecular Field Analysis(CoMFA).For three analyzed compound series, the squared correlation coefficients of cross-validation(q2)could vary as largely as 0.30～0.40 among all possible orientations. The reason for this comes from the routine adopted by CoMFA which uses discrete, regularly arrayed grids to represent the molecular field. Therefore, different orientations may map their molecular fields differently onto the grid and accordingly give different results from partial least square (PLS)analyses. We have developed a method all-orientation searching, to seek for the orientation with the best CoMFA result. And ,we suggest that all-orientation searching should be incorporated into the standard CoMFA procedure.     

新型三唑类抗真菌化合物的三维定量构效关系研究

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), 系统研究了40个新型三唑类化合物抗真菌活性的三维定量构效关系. 在CoMFA研究中, 研究了两种药效构象对模型的影响, 并考察了网格点步长对统计结果的影响. 在CoMSIA研究中, 系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响, 发现立体场、静电场、疏水场和氢键受体场的组合得到最佳模型. 所建立CoMFA和CoMSIA模型的交叉相关系数q²值分别为0.718和0.655, 并都具有较强的预测能力. CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯环上各位置取代基对抗真菌活性的影响, 为进一步结构优化提供了重要依据.     

Improved CoMFA modeling by optimization of settings

The possibility of improving the predictive ability of comparative molecular field analysis (CoMFA) by settings optimization has been evaluated to show that CoMFA predictive ability can be improved. Ten different CoMFA settings are evaluated, producing a total of 6120 models. This method has been applied to nine different data sets, including the widely used benchmark steroid data set, as well as eight other data sets proposed as QSAR benchmarking data sets by Sutherland et al. (J. Med. Chem. 2004, 47, 5541-5554). All data sets have been studied using training and test sets to allow for both internal (q(2)) and external (r(2)(pred)) predictive ability assessment. CoMFA settings optimization was successful in developing models with improved q(2) and r(2)(pred) as compared to default CoMFA modeling. Optimized CoMFA is compared with comparative molecular similarity indices analysis (CoMSIA) and holographic quantitative structure-activity relationship (HQSAR) models and found to consistently produce models with improved or equivalent q(2) and r(2)(pred). The ability of settings optimization to improve model predictive ability has been validated using both internal and external predictions, and the risk of chance correlation has been evaluated using response variable randomization tests.     

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of thiazolone derivatives as hepatitis C virus NS5B polymerase allosteric inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a series of thiazolone derivatives as novel inhibitors bound to the allosteric site of hepatitis C virus (HCV) NS5B polymerase were developed based on CoMFA and CoMSIA analyses. Two different conformations of the template molecule and the combinations of different CoMSIA field/fields were considered to build predictive CoMFA and CoMSIA models. The CoMFA and CoMSIA models with best predictive ability were obtained by the use of the template conformation from X-ray crystal structures. The best CoMFA and CoMSIA models gave q (2) values of 0.621 and 0.685, and r (2) values of 0.950 and 0.940, respectively for the 51 compounds in the training set. The predictive ability of the two models was also validated by using a test set of 16 compounds which gave r (pred) (2) values of 0.685 and 0.822, respectively. The information obtained from the CoMFA and CoMSIA 3D contour maps enables the interpretation of their structure-activity relationship and was also used to the design of several new inhibitors with improved activity.     

含呋喃环双酰脲类衍生物的三维定量构效关系研究

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27个新型双酰基脲类化合物的杀蚊幼虫(Aedes aegypti L.)活性进行三维定量构效关系(3D-QSAR)研究. 在CoMFA研究中, 考察了网格点步长对统计结果的影响. 在CoMSIA研究中, 系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响, 发现立体场和氢键供体场的组合得到最佳模型. 所建立的CoMFA和CoMSIA模型的非交叉验证相关系数r2值分别为0.828和0.841, 并都具有较强的预测能力. CoMFA和CoMSIA模型的三维等值图不仅直观地解释了结构与活性的关系, 而且为后续优化该系列化合物提供了理论依据.     

Three-dimensional quantitative structure--property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpy of sublimation

Three-dimensional quantitative structure--property relationship (3D-QSPR) models have been constructed using comparative molecular field analysis (CoMFA) to correlate the sublimation enthalpies at 298.15 K of a series of polychlorinated biphenyls (PCBs) with their CoMFA-calculated physicochemical properties. Various alignment schemes, such as atom fit, as is, and inertial were employed in this study. Separate CoMFA models were developed using different partial charge formalisms, namely, electrostatic potential (ESP) and Gasteiger-Marsili (GM) charges. Among the four different CoMFA models constructed for sublimation enthalpy (Delta(sub)H(m)(298.15 K)), the model that combined atom fit alignment and ESP charges yielded the greatest self-consistency (r(2) = 0.976) and internal predictive ability (r(cv)(2) = 0.750). This CoMFA model was used to predict Delta(sub)H(m)(298.15 K) of PCBs for which the corresponding experimental values are unavailable in the literature.     

Challenging the gold standard for 3D-QSAR: template CoMFA versus X-ray alignment

X-ray-based alignments of bioactive compounds are commonly used to correlate structural changes with changes in potencies, ultimately leading to three-dimensional quantitative structure–activity relationships such as CoMFA or CoMSIA models that can provide further guidance for the design of new compounds. We have analyzed data sets where the alignment of the compounds is entirely based on experimentally derived ligand poses from X-ray-crystallography. We developed CoMFA and CoMSIA models from these X-ray-determined receptor-bound conformations and compared the results with models generated from ligand-centric Template CoMFA, finding that the fluctuations in the positions and conformations of compounds dominate X-ray-based alignments can yield poorer predictions than those from the self-consistent template CoMFA alignments. Also, when there exist multiple different binding modes, structural interpretation in terms of binding site constraints can often be simpler with template-based alignments than with X-ray-based alignments.     

苯并呋喃类N-肉豆蔻酰基转移酶抑制剂的三维定量构效关系研究

摘要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), 系统地研究了40个苯并呋喃类N-肉豆蔻酰基转移酶(NMT)抑制剂的三维定量构效关系. 在CoMFA研究中, 考察了网格点步长对模型统计结果的影响. 在CoMSIA研究中, 研究了各种分子场组合、 网格点步长和衰减因子对模型统计结果的影响, 发现立体场、 静电场、 疏水场和氢键受体场的组合可得到最佳模型. 所建立的CoMFA和CoMSIA模型的交叉相关系数q2值分别为0.759和0.730, 均具有较强的预测能力. 利用CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯并呋喃环上各位置取代基对抑酶活性的影响, 为进一步结构优化提供了重要依据.     

基于5-芳基乙内酰脲类化合物的CoMFA和HQSAR研究

用CoMFA和HQSAR两种QSAR方法研究了50个乙内酰脲类分子的定量构效关系.本研究从构象搜索所得的低能结构出发构建化合物分子的构象, 建立CoMFA模型,并进行了全空间搜索. HQSAR本质上是一种二维的QSAR方法,与CoMFA方法相比,该方法在数据处理方面,比CoMFA方法快捷,并且可重复性好.两种方法均得到了较好分析结果, CoMFA的交叉验证相关系数q2 值为0.815, HQSAR的q2值为0.893.这些方程有力地说明了该类分子在(R,R)-N-3,5-dinitrobenzoyl-1,2-diamine型手性固定相上拆分过程中的影响因素,对今后类似拆分的实验研究提供了理论支持.     

Mapping the binding site of a large set of quinazoline type EGF-R inhibitors using molecular field analyses and molecular docking studies

In the current work, three-dimensional QSAR studies for one large set of quinazoline type epidermal growth factor receptor (EGF-R) inhibitors were conducted using two types of molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). These compounds belonging to six different structural classes were randomly divided into a training set of 122 compounds and a test set of 13 compounds. The statistical results showed that the 3D-QSAR models derived from CoMFA were superior to those generated from CoMSIA. The most optimal CoMFA model after region focusing bears significant cross-validated r(2)(cv) of 0.60 and conventional r(2) of 0.92. The predictive power of the best CoMFA model was further validated by the accurate estimation to these compounds in the external test set, and the mean agreement of experimental and predicted log(IC(50)) values of the inhibitors is 0.6 log unit. Separate CoMFA models were conducted to evaluate the influence of different partial charges (Gasteiger-Marsili, Gasteiger-Hückel, MMFF94, ESP-AM1, and MPA-AM1) on the statistical quality of the models. The resulting CoMFA field map provides information on the geometry of the binding site cavity and the relative weights of various properties in different site pockets for each of the substrates considered. Moreover, in the current work, we applied MD simulations combined with MM/PBSA (Molecular mechanics/Possion-Boltzmann Surface Area) to determine the correct binding mode of the best inhibitor for which no ligand-protein crystal structure was present. To proceed, we define the following procedure: three hundred picosecond molecular dynamics simulations were first performed for the four binding modes suggested by DOCK 4.0 and manual docking, and then MM/PBSA was carried out for the collected snapshots. The most favorable binding mode identified by MM/PBSA has a binding free energy about 10 kcal/mol more favorable than the second best one. The most favorable binding mode identified by MM/PBSA can give satisfactory explanation of the SAR data of the studied molecules and is in good agreement with the contour maps of CoMFA. The most favorable binding mode suggests that with the quinazoline-based inhibitor, the N3 atom is hydrogen-bonded to a water molecule which, in turn, interacts with Thr 766, not Thr 830 as proposed by Wissner et al. (J. Med. Chem. 2000, 43, 3244). The predicted complex structure of quinazoline type inhibitor with EGF-R as well as the pharmacophore mapping from CoMFA can interpret the structure activities of the inhibitors well and afford us important information for structure-based drug design.