黄酮化合物色谱保留时间与其三维结构的关系研究

利用比较分子相似性指数分析（CoMSIA）方法,结合黄酮类化合物含有较多羟基、易形成较强分子内氢键的特点,建立了黄酮类化合物色谱保留时间与其三维结构的关系模型,以探讨黄酮类化合物色谱保留时间预测的新方法。模型交叉验证相关系数q2值为0．705,非交叉验证相关系数r2为0．981,表明模型具有较好的预测能力。该研究结果对进一步开展黄酮类化合物液相色谱保留参数与三维结构关系的研究提供了思路和方法。     

化合物毒性及三维结构参数的定量构效关系研究

目的：建立小分子化合物毒性的三维定量构效关系模型,探索化合物毒性数据和三维结构参数之间关系的方法。方法：利用比较分子力场分析方法（CoMFA）,建立了一组对发光菌有急性毒性的小分子的三维定量构效模型。结果：模型的交叉验证相关系数q^2=0．731,非交叉验证相关系数r^2=0．973,标准偏差SE=0．122,F=70．910。结论：该模型具有较好的预测能力,表明在甲基的邻对位减小取代基体积或电负性可以降低化合物毒性。     

新型乙酰胆碱酯酶抑制剂的三维定量构效关系研究

通过应用乙酰胆碱酯酶抑制剂筛选模型, 检测了一系列苯戊烯酮衍生物的抑制活性, 然后应用比较分子场分析方法, 建立了乙酰胆碱酯酶抑制剂结构与活性之间的三维定量构效关系模型, 为设计高活性的乙酰胆碱酯酶抑制剂提供线索. 模型R²_CV = 0.629, 最佳主成分数为6, 传统相关系数为R²＝0.972, F＝72.41, 标准误差SE＝0.331, 所得模型不仅可以解释化合物的构效关系, 而且对高活性化合物有很好的预测能力. 通过比较立体场和静电场的系数等势图, 分析了结构与活性的关系, 得到的结果可以指导新化合物的设计与合成.     

螺环哌啶类似物作为DOR激动剂的特征结构研究

阿片受体激动剂与特定阿片受体亚型结合,常用来治疗与外伤、癌症或心脏病相关的严重疼痛,是十分有吸引力的药用物质．阿片受体有3种经典亚型(δ, κ, μ),均有与其对应的激动剂．δ阿片受体(DOR)激动剂因其还有明显的抗焦虑、抗抑郁和器官保护作用,是非常有前景的药物．本文研究了一批共102个N-取代螺环哌啶类似物作为δ阿片受体激动剂的分子,采用比较分子力场(CoMFA)和比较分子相似性指数(CoMSIA)两种分析方法对所有分子进行了三维定量构效关系(3D-QSAR)研究,其中基于疏水场和氢键供体场参数建立的CoMSIA模型最佳,其模型结果为：Q²=0.501,R²_ncv=0.787,R²_pre=0.780,证明模型自我吻合良好,同时有较强的内部及外部预测能力．而模型的等势线图分析表明,在R₁处引入疏水性的取代基及在R₂处引入亲水性的取代基或氢键供体基团对提高激动剂活性有利．这些结论有助于更好地理解N-取代螺环哌啶类似物作为DOR激动剂的机理,为新型的δ阿片受体激动剂的设计和优化提供一定的指导．     

醛糖还原酶抑制剂细胞筛选模型的建立

目的：将糖尿病慢性并发症相关基因醛糖还原酶 (aldose reductase, AR) 基因与腺相关病毒(adeno associated virus, AAV) 表达载体pSNAV2.0重组,使其在HEK293细胞中表达,以基因工程表达的AR为靶向,建立醛糖还原酶抑制剂 (aldose reductase inhibitor, ARI) 细胞筛选模型。方法：首先采用酶切、连接等方法构建含有人AR基因序列的AAV表达载体pSNAV-hAR,将重组质粒转染HEK293细胞,通过活性测定、Western blot和免疫荧光检测目的基因转染及表达的情况。结果：PCR、酶切、DNA测序均证实表达质粒pSNAV-hAR构建正确。转染HEK293细胞后,一系列分析结果显示,腺相关病毒表达载体介导的AR真核细胞表达产物是具有功能活性的目的蛋白。应用经典醛糖还原酶抑制剂 Sobinil 和 Zopolrestat 对此模型进行了验证。结论：AR高表达细胞模型的建立,为进一步筛选ARI、探讨多元醇通路学说在糖尿病慢性并发症发病机制中的作用奠定了基础。针对先后建立的酵母细胞与真核细胞模型的特点及三种AR活性测定方法中的注意事项进行了讨论。     

旱生香茶菜二萜化合物细胞毒活性的三维构效研究

应用比较分子力场法（COMFA）研究了一系列旱生香茶菜二萜化合物对人红细胞白血病（K562）、人旱幼粒白血病（HL-60）、人胃腺癌（MKN-28）和人结肠癌（HCT）细胞体外抗肿瘤活性进行了三维定量构效关系的初步研究,其结果将为香条菜二萜的结构修饰和简化,先导化合物的发现提供理论依据。     

A型肉毒毒素抑制剂的分子全息定量构效关系研究

目的:建立A型肉毒毒素抑制剂的定量构效关系模型。方法:应用分子全息定量构效关系(HQSAR)技术,研究了14种A型肉毒毒素抑制剂的抑制活性与其二维分子结构之间的关系,讨论了碎片区分参数及碎片长度对模型质量的影响。结果:最佳全息条件下产生的模型相关系数r2为0.780,交叉验证相关系数q2LOO为0.583。所建模型具有良好的拟和效果和较高的预测能力,HQSAR模型贡献图显示抑制剂分子中的噻吩环及羟胺对活性有较大贡献。结论:本研究对新抑制剂的设计具有一定的指导作用。     

黄酮类化合物药理作用的研究进展

总结黄酮类化合物在药理作用方面的研究近况,在阐述黄酮类化合物的生物活性、药理作用的同时,结合结构分析和作用机制,揭示与其部分活性相关的构效关系,并对黄酮类化合物药理作用的研究提出进一步的展望。     

定量计算萜类驱避化合物与二氧化碳缔合对其蚊虫驱避活性的影响

为验证萜类驱避化合物与嗅觉引诱物二氧化碳存在缔合作用, 并研究缔合作用对蚊虫驱避活性的影响。本研究借助计算化学的方法获得缔合体和缔合能量, 利用Gaussian View和Gaussian 03W软件分别构建和优化二氧化碳、 22个萜类蚊虫驱避化合物以及它们与二氧化碳缔合后的三维分子结构, 经Ampac 8.16转化后, 获得它们的缔合能量。借助定量构效关系计算方法研究缔合作用对驱避活性的影响, 利用Codessa 2.7.10计算获得驱避剂和缔合体的各类结构描述符, 从包括缔合体结构描述符及特征描述符在内的各类结构参数中筛选显著性参数, 以萜类驱避化合物对白纹伊蚊Aedes albopictus的校正驱避率的对数值为活性数据, 建立结构描述符与驱避活性的定量构效关系（quantitative structure-activity relationship, QSAR）模型。结果获得了22个萜类驱避化合物与二氧化碳缔合的缔合能量, 计算显示它们之间存在缔合作用并且可以形成缔合体; 获得1个R²为0.9643的4参数QSAR模型, 这4个参数所对应的结构描述符分别是COM-WNSA 3 Weighted PNSA (PNSA3*TMSA/1 000) ［Zefirov’s PC］, f-TerCO₂-Min e-n attraction for a C-O bond, M-Max 1-electron reaction index for an O atom, M-Min (>0.1) bond order of an H atom, 前2个参数分别为缔合体的整体结构描述符和碎片特征描述符。计算化学结果表明, 萜类驱避化合物与二氧化碳存在缔合作用, 该缔合作用对驱避活性的影响显著。     

天然黄酮类化合物的构效关系最新研究进展

天然黄酮类化合物以其在抗衰老、抗肿瘤、抗炎、肝脏保护和降血糖方面的高活性成为天然产物的研究热点。近年来,关于天然黄酮类化合物的提取和纯化、结构分析、生物利用度和药理活性有许多报道。本文对天然黄酮类化合物的构效关系的研究进展进行综述,旨在为天然黄酮类化合物未来发展和利用提供参考。     

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.     

Three-dimensional quantitative structure–activity relationship study on paullones as CDK inhibitors using CoMSIA and CoMFA

3D-QSAR studies were conducted on a series of paullones as CDK inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR) methods. Two methods were compared: the widely used comparative molecular field analysis (CoMFA) and the recently reported comparative molecular similarity indices analysis (CoMSIA). Systematic variations of some parameters in CoMSIA and CoMFA were performed to search for the best 3D-QSAR model. The computed results showed that the 3D-QSAR models from CoMSIA were clearly superior to those from CoMFA. Using the best model from CoMSIA analysis, a significant cross-validated q² was obtained and the predicted biological activities of the five compounds in the test set were in good agreement with the experimental values. The correlation results obtained from CoMSIA were graphically interpreted in terms of field contribution maps allowing physicochemical properties relevant for binding to be easily mapped back onto molecular structures. The features in the CoMSIA contour maps intuitively suggested where to modify a molecular structure in terms of physicochemical properties and functional groups in order to improve its binding affinity, which is very important for improving our understanding of the ligand-receptor interactions and in helping to design compounds with improved activity.     

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r2, q2(loo) and r2(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r2(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.     

Docking-based 3D-QSAR study for 11beta-HSD1 inhibitors

11beta-Hydroxysteroid dehydrogenase (11beta-HSD) enzymes catalyze the conversion of biologically inactive 11-ketosteroids into their active 11beta-hydroxy derivatives and vice versa. 11beta-HSD1 has been studied as a potential treatment for metabolic disease such as diabetes and obesity. To find correlation between 11beta-HSD1 and inhibitors, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on 70 inhibitors, based on molecular docking conformations obtained by using FlexX-Pharm. The studies include comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Based on the docking results, highly predictive 3D-QSAR models were developed with q(2) values of 0.543 and 0.519 for CoMFA and CoMSIA, respectively. A comparison of the 3D-QSAR field contributions with the structural features of the binding site showed good correlation between the two analyses. Therefore, these results should be useful to the prediction of the activities of new 11beta-HSD1 inhibitors.     

Development of new CoMFA and CoMSIA 3D-QSAR models for anti-inflammatory phthalimide-containing TNFalpha modulators

In the present study, we describe a new 3D-QSAR analysis of 42 previously reported thalidomide analogues, with the ability to modulate the pro-inflammatory cytokine TNFalpha, by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Three statistically significant models were obtained. The best resulting CoMFA and CoMSIA models have conventional r(2) values of 0.996 and 0.983, respectively. The cross-validated q(2) values are 0.869 and 0.868, respectively. The analysis of CoMFA and CoMSIA contour maps provided insight into the possible sites for structural modification of the thalidomide analogues for better activity and reduced toxicity.     

3D-QSAR studies on c-Src kinase inhibitors and docking analyses of a potent dual kinase inhibitor of c-Src and c-Abl kinases

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses were carried out on quinazoline, quinoline, and cyanoquinoline derivatives inhibiting c-Src kinase. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models were developed. The conventional r2 values for CoMFA and CoMSIA are 0.93 and 0.89, respectively. In addition, a homology model of c-Src kinase with the activation loop resembling the active conformation was constructed using the crystal structure of the kinase domain of Lck. The ATP binding pocket of the active form of c-Src is similar to that of the c-Abl kinase in which the activation loop resembles that of an active form. One of the potent c-Src and c-Abl dual kinase inhibitors (77 or SKI-606) was docked inside the active sites of both c-Src and c-Abl. The orientation and hydrogen bonding interactions of 77 are similar in both kinases. The results of 3D-QSAR analyses and structure based studies will be useful for the design of novel c-Src and c-Abl dual kinase inhibitors.     

3D-QSAR studies on tripeptide aldehyde inhibitors of proteasome using CoMFA and CoMSIA methods

The ubiquitin-proteasome pathway plays a crucial role in the regulation of many physiological processes and in the development of a number of major human diseases, such as cancer, Alzheimer's, Parkinson's, diabetes, etc. As a new target, the study on the proteasome inhibitors has received much attention recently. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using comparative molecule field analysis (CoMFA) and comparative molecule similarity indices analysis (CoMSIA) techniques were applied to analyze the binding affinity of a set of tripeptide aldehyde inhibitors of 20S proteasome. The optimal CoMFA and CoMSIA models obtained for the training set were all statistically significant with cross-validated coefficients (q(2)) of 0.615, 0.591 and conventional coefficients (r(2)) of 0.901, 0.894, respectively. These models were validated by a test set of eight molecules that were not included in the training set. The predicted correlation coefficients (r(2)) of CoMFA and CoMSIA are 0.944 and 0.861, respectively. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of beta5 subunit of 20S proteasome, which suggests that the 3D-QSAR models built in this paper can be used to guide the development of novel inhibitors of 20S proteasome.     

Molecular docking and 3D-QSAR studies of Yersinia protein tyrosine phosphatase YopH inhibitors

Three-dimensional quantitative structure-activity relationship (QSAR) studies were conducted on two classes of recently explored compounds with known YopH inhibitory activities. Docking studies were employed to position the inhibitors into the YopH active site to determine the probable binding conformation. Good correlations between the predicated binding free energies and the inhibitory activities were found for two subsets of phosphate mimetics: alpha-ketocarboxylic acid and squaric acid (R2=0.70 and 0.68, respectively). The docking results also provided a reliable conformational alignment scheme for 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed based on the docking conformations, giving q2 of 0.734 and 0.754 for CoMFA and CoMSIA models, respectively. The 3D-QSAR models were significantly improved after removal of an outlier (q2=0.829 for CoMFA and q2=0.837 for CoMSIA). The predictive ability of the models was validated using a set of compounds that were not included in the training set. Mapping the 3D-QSAR models to the active site of YopH provides new insight into the protein-inhibitor interactions for this enzyme. These results should be applicable to the prediction of the activities of new YopH inhibitors, as well as providing structural implications for designing potent and selective YopH inhibitors as antiplague agents.     

Structural insights of PA-824 derivatives: ligand-based 3D-QSAR study and design of novel PA824 derivatives as anti-tubercular agents

Abstract

With the purpose of designing novel chemical entities with improved inhibitory potencies against drug-resistant Mycobacterium tuberculosis, the 3D- quantitative structure–activity relationship (QSAR) studies were carried out on biphenyl analogs of the tuberculosis (TB) drug, PA-824. Anti-mycobacterial activity (MABA) was considered for the 3D-QSAR studies using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The best CoMFA and CoMSIA models were found statistically significant with cross-validated coefficients (q²) of 0.784 and 0.768, respectively, and conventional coefficients (r²) of 0.823 and 0.981, respectively. The cross-validated and the external validation results revealed that both the CoMFA and CoMSIA models possesses high accommodating capacities and they would be reliable for predicting the pMIC values of new PA-824 derivatives. Based on the models and structural insights, a series of new PA-824 derivatives were designed and the anti-mycobacterial activities of the designed compounds were predicted based on the best 3D-QSAR model. The predicted data results suggest the designed compounds are more potent than existed ones.     

3D-QSAR studies on thieno[3,2-d]pyrimidines as phosphodiesterase IV inhibitors

Cyclic nucleotide phosphodiesterase IV (PDE IV) inhibitors find utility in asthma and Chronic Obstructive Pulmonary Disease (COPD) therapy. A series of 29 thieno[3,2-d]pyrimidines with affinity for PDE IV was subjected to three dimensional quantitative structure activity relationship (3D-QSAR) studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Both CoMFA and CoMSIA provided statistically valid models with good correlative and predictive power. The incorporation of hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields showed insignificant improvement in CoMSIA model. The 3D-QSAR models provide information for predicting the affinity of related compounds and designing more potent inhibitors.