光系统Ⅱ抑制剂: 顺式氰基丙烯酸酯化合物的 三维构效关系的电子结构研究

以距离比较法所获得的顺式氰基丙烯酸酯化合物的活性构象为模板,对39个该类化合物采用比较分子场方法进行了三维构效关系的研究。结果表明,所获得的药效团模型具有很好的预测能力。同时采用量子化学的方法对活性构象模板分子电子结构作了讨论。     

Ordinal classification using Comparative Molecular Field Analysis

Comparative Molecular Field Analysis (CoMFA) is most widely used as one of the 3-dimensional QSAR (3D-QSAR) methods to identify the relationship between chemical structure and biological activity. Conventional CoMFA requires at least 3 orders of experimental data, such as IC50 and Ki, to obtain a good model, although practically there are many screening assays where biological activity is measured only by a rating scale. Hence, rating classification-oriented CoMFA coupled with ordinal logistic regression has been developed, and its predictive ability and 3D graphical analysis ability have been investigated. As a result, this novel CoMFA (Logistic CoMFA) has been found to be more robust than conventional CoMFAs in both predictive and 3D graphical analysis abilities. Furthermore, Logistic CoMFA is useful since it can provide the probability of each rank.     

Comparative molecular field analysis of non-steroidal aromatase inhibitors related to fadrozole

Summary A series of non-steroidal inhibitors of aromatase, structurally related to fadrozole (2), was investigated with the aim of developing a 3D QSAR model using the Comparative Molecular Field Analysis (CoMFA) technique. The alignment of the molecules was performed following two approaches (atom-by-atom and field fit), both starting from an initial hypothesis of superimposition of fadrozole to a steroidal inhibitor (3). From a number of CoMFA models built with different characteristics, one was recognized as the most statistically relevant; this one is discussed in detail. The features of the 3D QSAR model are consistent with those of other 3D and QSAR models of aromatase and its inhibitors.     

嘧啶（氧）苯甲酸类除草剂的3D—QSAR研究

利用比较分子场分析 (Co MFA)方法 ,对 2 0种嘧啶 (氧 )苯甲酸类化合物进行了三维定量构效关系(3 D-QSAR)研究。得到了具有较强预测能力的 QSAR模型。并对此模型进行了验证 ,在此基础上 ,设计了具有更高活性的化合物。     

2(1H)-喹啉-2,4-二酮类化合物抗小麦锈病的3D-QSAR研究

用比较分子力场分析(CoMFA)方法和比较分子相似性指数分析(CoMSIA)方法研究了21个2(1H)-喹啉-2,4-二酮类化合物抗小麦锈病的三维定量构效关系(3D-QSAR),发现用CoMFA方法可以找到最佳的3D-QSAR模型,并通过量子化学从头计算的方法研究了不同活性化合物的前线轨道及静电势分布图的差异.所得构效关系模型为发现更高活性的化合物提供理论指导.     

Three-dimensional quantitative structure activity relationship (QSAR) of cytotoxic active 3,5-diaryl-4,5-dihydropyrazole analogs: a comparative molecular field analysis (CoMFA) revisited study

ABSTRACT: In vitro antitumor evaluation of the synthesized 46 compounds of 3,5-diaryl-4,5-dihydropyrazoles against EAC cell lines and 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described. CoMFA derived QSAR model shows a good conventional squared correlation coefficient r2 and cross validated correlation coefficient r2 cv 0.896 and 0.568 respectively. In this analysis steric and electrostatic field contribute to the QSAR equation by 70% and 30% respectively, suggesting that variation in biological activity of the compounds is dominated by differences in steric (van der Waals) interactions. To visualize the CoMFA steric and electrostatic field from partial least squares (PLS) analysis, contour maps are plotted as percentage contribution to the QSAR equation and are associated with the differences in biological activity. BACKGROUND: Pyrazole derivatives exhibit a wide range of biological properties including promising antitumor activity. Furthermore, Aldol condensation assisted organic synthesis has delivered rapid routes to N-containing heterocycles, including pyrazoles. Combining these features, the use of chalconisation-assisted processes will provide rapid access to a targeted dihydropyrazoles library bearing a hydrazino 3D QSAR study using pharmacophore and Comparative Molecular Field Analysis (CoMFA) methods were described for evaluation of antioxidant properties. RESULTS: Chalcones promoted 1 of the 2 steps in a rapid, convergent synthesis of a small library of hydrazinyl pyrazole derivatives, all of which exhibited significant antitumor activity against Ehrlich Ascites Carcinoma (EAC) human tumor cell line comparable to that of the natural anticancer doxorubicin, as a reference standard during this study. In order to understand the observed pharmacological properties, quantitative structure-activity relationship (3D QSAR) study was initiated. CONCLUSIONS: Chalcones heating provides a rapid and expedient route to a series of pyrazoles to investigate their chracterization scavenging properties. Given their favorable properties, in comparison with known anticancer, these pyrazole derivatives are promising leads for further development and optimization.     

咪唑啉酮类除草剂的三维构效关系研究

从三维角度出发,采取不同的构象搜索方法得到了咪唑酮类化合物分子的活性构象。利用比较分子场分析方法进一步证实了模板分子构象的正确性。并从静电场、立体场及活性关系等方面进行了三维定量构效关系研究,得到了具有较强预测能力的QSAR模型。     

High-affinity interactions of ligands at recombinant Guinea pig 5HT7 receptors

The serotonin 5HT₇ receptor has been implicated in numerous physiological and pathological processes from circadian rhythms [1] to depression and schizophrenia. Clonal cell lines heterologously expressing recombinant receptors offer good models for understanding drug-receptor interactions and development of quantitative structure-activity relationships (QSAR). Comparative Molecular Field Analysis (CoMFA) is an important modern QSAR procedure that relates the steric and electrostatic fields of a set of aligned compounds to affinity. Here, we utilized CoMFA to predict affinity for a number of high-affinity ligands at the recombinant guinea pig 5HT₇ receptor. Using R-lisuride as the template, a final CoMFA model was derived using procedures similar to those of our recent papers [2, 3, 4] The final cross-validated model accounted for >85% of the variance in the compound affinity data, while the final non-cross validated model accounted for >99% of the variance. Model evaluation was done using cross-validation methods with groups of 5 ligands. Twenty cross-validation runs yielded an average predictive r²(q²) of 0.779 ± 0.015 (range: 0.669–0.867). Furthermore, 3D-chemical database search queries derived from the model yielded hit lists of promising agents with high structural similarity to the template. Together, these results suggest a possible basis for high-affinity drug action at 5HT₇ receptors.     

Modeling ligand-receptor interaction for some MHC class II HLA-DR4 peptide mimetic inhibitors using several molecular docking and 3D QSAR techniques

The ligand-receptor interaction between some peptidomimetic inhibitors and a class II MHC peptide presenting molecule, the HLA-DR4 receptor, was modeled using some three-dimensional (3D) quantitative structure-activity relationship (QSAR) methods such as the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and a pharmacophore building method, the Catalyst program. The structures of these peptidomimetic inhibitors were generated theoretically, and the conformations used in the 3D QSAR studies were defined by docking them into the known structure of HLA-DR4 receptor through the GOLD, GLIDE Rigidly, GLIDE Flexible, and Xscore programs. Some of the parameters used in these docking programs were selected by docking an X-ray ligand into the receptor and comparing the root-means-square difference (RMSD) computed between the coordinates of the X-ray and docked structure. However, the goodness of a docking result for docking a series of peptidomimetic inhibitors into the HLA-DR4 receptor was judged by comparing the Spearman's rank correlation coefficient computed between each docking result and the activity data taken from the literature. The best CoMFA and CoMSIA models were constructed using the aligned structures of the best docking result. The CoMSIA was conducted in a stepwise manner to identify some important molecular features that were further employed in a pharmacophore building process by the Catalyst program. It was found that most inhibitors of the training set were accurately predicted by the best pharmacophore model, the Hypo1 hypothesis constructed. The deviation or conflict found between the actual and predicted activities of some inhibitors of both the training and the test sets were also investigated by mapping the Hypo1 hypothesis onto the corresponding structures of the inhibitors.     

CoMFA modeling of human catechol O-methyltransferase enzyme kinetics

Three-dimensional QSAR models with different charge calculation methods (MOPAC-AM1-ESP, MOPAC-AM1-Coulson and Gasteiger-Hückel) were developed for predicting all three enzyme kinetic parameters Km, Vmax and Vmax/Km for catecholic substrates of human soluble catechol O-methyltransferase (S-COMT). The empirical parameters of 45 substrates were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). Alignment rules for CoMFA were developed based on the catalytic mechanism and crystal structure of S-COMT, and the analysis was optimized using an all-space search technique. Leave-one-out and leave-n-out cross-validation (with 5 and 10 cross-validation groups) was carried out, and all developed models proved to be statistically significant with q2 values up to 0.84. The models based on MOPAC charge calculations predicted the empirical values clearly better than the Gasteiger-Hückel method. The derived CoMFA coefficient contour maps of steric and electrostatic interactions correlated clearly with the S-COMT crystallographic structures.     

咪唑-1-羟酸酯类化合物的构效关系研究

利用CoMFA方法，对20种咪唑-l-羧酸酯类化合物进行了三维定量均效关系研究．研究结果表明，影响其药效的主要因素是空间结构．得到了具有较强预测能力的QSAR模型．在此基础上，设计了高活性的化合物，并发现了分子中存在着明显的芳环堆积现象，可能和对受体的识别有关．     

应用分子图形学、分子力学、量子化学及静电势研究农药分子结构与性能关系(ΧⅢ)──用比较分子力场方法研究4-肟醚基喹唑啉类化合物的结构与抗烟草花叶病毒活性的三维构效关系

应用比较分子力场分析 (Co MFA)方法研究 4 -肟醚基喹唑啉类化合物抗烟草花叶病毒活性的三维构效关系 (3 D-QSAR) ,引入分子的摩尔折射率 (MR)和偶极矩 (DIPOLE)分别作为 Co MFA的第三和第四个场 .在此基础上进行偏最小二乘 (PLS)分析 :交叉验证 (leave-one-out)结果为 r2cv=0 .4 43 ,非交叉验证 (novalidation)结果为 r2 =0 .93 2 ,说明所建立的模型有较好的可靠性 ,并且在三维等值线图的基础上得到了一个此类化合物的模拟作用模型 ,据此可生长出一系列先导分子     

1－环丙基－5，7，8取代－6－氟－1，4－二氢－4－氧－3－喹啉羧酸定量构效关系的比较分子力场分析研究

利用３Ｄ－ＱＳＡＲ中的比较分子力场分析法（ＣｏＭＦＡ）研究了标题化合物的定量构效关系。通过不同探针与空间网格点间隙的对比研究，发现以　、空间网格点间隙２０ｎｍ结果为最优。从　值来看，ＣｏＭＦＡ计算得到的模型有很高的预测性。依据ＣｏＭＦＡ系数图设计一些新化合物并预测了它们的活性，结果表明：对抑制革兰氏阳性菌有数种化合物的活性比迄今合成的化合物要高。     

Comparing the performance of FLUFF-BALL to SEAL-CoMFA with a large diverse estrogen data set: from relevant superpositions to solid predictions

In this work a template-based molecular mechanistic superposition algorithm FLUFF (Flexible Ligand Unified Force Field) and an accompanying local coordinate QSAR method BALL (Boundless Adaptive Localized Ligand) are validated against the benchmark techniques SEAL (Steric and Electrostatic Alignment) and CoMFA (Comparative Molecular Field Analysis) using a large diverse set of 245 xenoestrogens extracted from the EDKB (Endocrine Disruptor Knowledge Base) maintained by NCTR (National Centre for Toxicological Research). The results indicate that FLUFF is capable of generating relevant superpositions not only for BALL but also for CoMFA, as both techniques give predictive QSAR models. When the BALL and CoMFA methods are compared, it is clear that the BALL algorithm met or even exceeded the results of the standard 3D-QSAR method CoMFA using alignments either from the tailor-made superposition technique FLUFF or the reference method SEAL. The FLUFF-BALL method can be easily automated, and it is computationally light, providing thus a good computational "sieve" capable of fast screening of large molecule libraries.     

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.     

比较分子力场分析法(CoMFA)的研究新进展

CoMFA是目前3D-QSAR 中应用最广且最为成功的一种方法, 但其在设计思想和实施过程中还存在一定缺陷, 主要表现在匹配规则、新场引入、变量选择及数据处理等几个方面。本文对近年来关于CoMFA 方法的各种改进研究做了较为系统的综述, 并就CoMFA 在药物设计中的作用进行了展望。     

Computational studies of chiral catalysts: a comparative molecular field analysis of an asymmetric Diels-Alder reaction with catalysts containing bisoxazoline or phosphinooxazoline ligands

A QSAR using Comparative Molecular Field Analysis (CoMFA) is developed for a set of 23 catalysts containing bisoxazoline or phosphinooxazoline ligands that are known to induce asymmetry during the Diels-Alder reaction of N-2-alkenoyl-1,3-oxazolidine-2-one with cyclopentadiene. It is shown that extremely high q(2) statistics can be derived by using standard modeling protocols when internal validation alone is done as well as when an external test set is used. From these models it is shown that approximately 70% of the variance in the observed enantiomeric excess can be attributed to the steric field and the remainder of the variance to the electrostatic field. Suggestions about how to improve the performance of inefficient catalysts are given.     

CoMFA modeling of enzyme kinetics: K(m) values for sulfation of diverse phenolic substrates by human catecholamine sulfotransferase SULT1A3

Three-dimensional QSAR models were developed for predicting kinetic Michaelis constant (K(m)) values for phenolic substrates of human catecholamine sulfating sulfotransferase (SULT1A3). The K(m) values were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). The evaluated SULT1A3 substrate data set consisted of 95 different substituted phenols, catechols, catecholamines, steroids, and related structures for which the K(m) values were available. The data set was divided in three different subgroups in the initial analysis: (1). for the first CoMFA model substrates with only one reacting hydroxyl group were selected (n = 51), (2).the second model was build with structurally rigid substrates (n = 59), and (3). finally all substrates of the data set were included in the analysis (n = 95). Substrate molecules were aligned using the aromatic ring and the reacting hydroxyl group as a template. After the initial analysis different substrate alignment rules based on the existing knowledge of the SULT1A3 active site structure were evaluated. After this optimization a final CoMFA model was built including all 95 substrates of the data set. Cross-validated q(2) values (leave-one-out and leave-n-out) and coefficient contour maps were calculated for all derived CoMFA models. All four CoMFA models were statistically significant with q(2) values up to 0.624. These predictive QSAR models will provide us information about the factors that affect substrate binding at the active site of human catecholamine sulfotransferase SULT1A3.