抗癌性苯并噻唑类衍生物三维定量构效关系研究

应用比较分子场分析法(CoMFA)对一系列抗癌性苯并噻唑类衍生物进行了三维定量构效关系(3D-QSAR)研究，建立了交叉验证的CoMFA模型，并在此基础上建立了非交叉验证的偏最小二乘分析模型．所建最佳模型的交叉验证相关系数为0.642，非交叉验证相关系数为0.976，估算的标准误差S＝0.161,统计方差比F(3;20)＝111.4，表明该模型是合理有效的．同时对该系列抗癌化合物的3D-QSAR进行了深入研究．结果表明，在R取代基的第一个原子上引入吸电子基团或原子，如F等，便可增强与它直接相连的C19的正电荷，从而增强C19ˉ位上处于静电场蓝色区域的原子的正电荷．同时，选择适当体积大小的取代基R，使之落入立体场绿色区域，就能有效地改善这类化合物的抗癌活性．     

Molecular Modeling and Design of Arylthioindole Derivatives as Tubulin Inhibitors

对一系列具有抗人乳腺癌细胞系MCF-7生物活性的微管蛋白抑制剂─芳基硫代吲哚衍生物(arylthioindole),进行了三维定量构效关系(3D-QSAR)和对接(docking)研究. 在训练集中,建立了具有良好统计质量和预报能力的比较分子力场分析(CoMFA) 模型,其非交叉验证相关系数平方R₂为0.898,交叉验证相关系数平方q₂为0.654. 同时在测试集的验证中得到预测相关系数平方R₂(pred)为0.816, 进一步表明了该模型具有较高的预测能力. 此外,通过对接研究,获得了这些化合物与微管蛋白作用的键合方式和构象,发现该系列化合物的CoMFA力场分布与对接结合位点上的三维拓朴结构相一致. 根据CoMFA和对接分析的结果,细致地讨论和总结了有利于提高或改进该类化合物活性的主要因素,即在取代基R3、R4和R5上引进高电负性的基团,在取代基R6上引进带有高电负性且大体积的基团,以及在取代基R7上引进小体积的基团等都是有利的. 基于这些研究结果,在理论上还设计了5个新的具有较高活性的化合物.     

噻吩并嘧啶衍生物抗胃癌活性的CoMFA模型与分子设计

基于比较分子力场分析(CoMFA)方法建立25种噻吩并嘧啶衍生物抗胃癌活性(pM)的三维定量构效关系(3D-QSAR)。训练集中20个化合物用于建立预测模型,测试集6个化合物(含模板分子)作为模型验证。已建立的CoMFA模型的交叉验证系数(Rcv2)、非交叉验证系数(R2)分别为0.369、0.831,说明所建模型具有较强的稳定性和良好的预测能力。该模型中立体场、静电场贡献率依次为40.9%、59.1%,表明影响抑藻活性(pI)的主要因素是取代基的库仑力、氢键及配位,其次是取代基的疏水性和空间位阻。基于此研究结果,设计了4个具有较高抗胃癌活性的新化合物,有待医学实验验证。     

基于Topomer CoMFA方法对芳基硫代吲哚衍生物的分子建模与设计

采用Topomer CoMFA方法对30个芳基硫代吲哚衍生物进行三维定量关系研究,建立了3D-QSAR模型,所得模型的交叉验证相关系数q~2,非交叉验证相关系数r~2,外部验证的复相关系数Q_(ext)~2分别为0.562,0.878,0.985,结果表明该模型具有较好的稳定性和预测能力.Topomer CoMFA模型等势面提供的立体场与静电场可视化图像,直观的揭示了这一系列化合物中不同取代基结构对其生物活性的影响,运用这些信息进行分子设计,在理论上获得了5个具有较高活性的新化合物,该QSAR的实验结果可为合成新药提供理论参考.     

分子内氮原子上亲核取代反应的理论研究

在MP2(full)/631+G(d,p)理论水平上,以-CHR-(CH2)3-NFCH3(R=H,CH3,CH2CF3,CHO,COCH3)为计算模型,对分子内可能发生的两条反应路径—氮原子上的亲核取代反应及消去反应进行了理论研究.结果表明,当进攻基团-CHR为碱性较强的基团,即R=H、CH3、CH2CF3时,有利于发生消去反应而生成直链化合物R-CH2-(CH2)3N=CH2;而当R为吸电子基团-CHO、-COCH3时,主要发生分子内氮原子上的亲核取代反应,产物为含氮的五员杂环化合物.这些理论预测与已有的实验结果吻合.     

4-羟氨基-α-吡喃酮甲酰胺类似物的3D-QSAR及分子对接研究

采用Topomer CoMFA方法对42个4-羟氨基-α-吡喃酮甲酰胺类似物进行三维定量构效关系(3D-QSAR)分析.所得最优模型的拟合、交互验证、及外部验证的复相关系数分别为0.926、0.638、0.923,结果表明该模型具有良好的稳定性和预测能力.采用Topomer Search技术在ZINK数据库中进行虚拟筛选,筛选出2个R1基团和16个R2基团,进而设计出32个具有更高活性的新型4-羟氨基-α-吡喃酮甲酰胺类化合物.采用分子对接技术对药物与受体的作用机制进行了研究,结果显示,药物与蛋白酶的ARG47、ILE368和GLY201位点作用明显,该QSAR的研究结果可为新药合成提供理论参考.     

基于Topomer CoMFA的吡唑啉嘧啶类IL-2诱导T细胞激酶抑制剂的3D-QSAR及分子对接

本文采用Topomer CoMFA方法对37个吡唑啉嘧啶类IL-2诱导T细胞激酶抑制剂进行三维定量构效关系研究.得到3D-QSAR模型,其交互验证系数q~2为0.728,非交叉相关系数r~2为0.994,主成分数N为8,标准估计误差SEE为0.097.结果表明该模型有较好的预测能力.采用Topomer Search技术在ZINC数据库中进行R基的筛选,并设计6个新分子.最后用分子对接技术研究了4个新分子与IL-2诱导的T细胞激酶(Itk)大分子蛋白的作用模式,从结果中可以看到,4个新分子与Itk蛋白的A/LYS391、A/MET438位点作用显著.     

应用CoMFA研究抗菌肽的三维定量构效关系

采用比较分子场分析(CoMFA)方法对抗菌九肽、抗菌十四肽、抗菌十八肽进行三维定量构效关系(3D-QSAR)分析,建立了预测力强的3D-QSAR模型.结果表明,所建立的3D-QSAR模型对三种抗菌肽均有较好的统计学稳定性及预测能力(抗菌九肽:交叉验证系数q~2=0.537,非交叉验证相关系数r~2=0.961,外部样本检验复相关系数Q_(ext)~2=0.883;抗菌十四肽:q~2=0.502,r~2=0.718,Q_(ext)~2=0.645;抗菌十八肽:q~2=0.550,r~2=0.967,Q_(ext)~2=0.989).三维等势图不仅解释了抗菌肽结构与活性的关系,而且为抗菌肽的进一步合成提供了理论依据.     

基于Topomer CoMFA的苯磺酰基亚胺噻唑衍生物的三维定量构效关系研究和分子设计

采用Topomer CoMFA方法对21个苯磺酰基亚胺噻唑衍生物进行三维定量构效关系研究,得到了HIV-1非核苷类逆转录酶抑制剂的3D-QSAR模型,其拟合复相关系数r2=0.964,交互验证复相关系数q2=0.801,外部验证复相关系数Qext2=0.959;采用基于片段的药物设计方法 Topomer Search从ZINC数据库中虚拟筛选出3个Ra基团和7个Rb基团,且设计得到21个新化合物.结果表明:该模型不仅稳定性良好,而且具有较强的预测能力;采用Topomer Search技术能够有效的筛选进而设计出新的化合物,为抗艾滋病新药的设计提供理论依据.     

HIV-1整合酶抑制剂的3D-QSAR研究

采用Topomer CoMFA方法对26个香豆素衍生物进行三维定量构效关系研究,建立了3D-QSAR模型,所得优化模型的非交叉相关系数、交互验证系数以及外部验证的复相关系数分别为0.973,0.666和0.960,结果表明该模型具有良好的稳定性和预测能力.运用这些信息进行分子对接,在理论上验证所构建的模型具有较高的可信性.此外,QSAR的研究结果可为新药合成提供理论参考.     

A combined 3D-QSAR and molecular docking strategy to understand the binding mechanism of V600EB-RAF inhibitors

B-RAF is a member of the RAF protein kinase family involved in the regulation of cell growth, differentiation, and proliferation. It forms a part of conserved apoptosis signals through the RAS?CRAF?CMAPK pathway. ^V600EB-RAF protein has much potential for scientific research as therapeutic target due to its involvement in human melanoma cancer. In this work, a molecular modeling study was carried out for the first time with 3D-QSAR studies by following the docking protocol on three different data sets of ^V600EB-RAF inhibitors. Based on the co-crystallized compound (PDB ID: 1UWJ), a receptor-guided alignment method was utilized to derive reliable CoMFA and CoMSIA models. The selected CoMFA model gives the best statistical values (q ² =?0.753, r ² =?0.962). With the same alignment protocol, a statistically reliable CoMSIA model out of fourteen different combinations was also derived (q ² = 0.807, r ² = 0.961). The actual predictive powers of both models were rigorously validated with an external test set, which gave satisfactory predictive r ² values for CoMFA and CoMSIA models, 0.89 and 0.88, respectively. In addition, y-randomization test was also performed to validate our 3D-QSAR models. Contour maps from CoMFA and CoMSIA models supported statistical results, revealed important structural features responsible for biological activity within the active site and explained the correlation between biological activity and receptor?Cligand interactions. Based on the developed models few new structures were designed. The newly predicted structure (IIIa) showed higher inhibitory potency (pIC₅₀ 6.826) than that of the most active compound of the series.     

De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q ², 0.671; r ², 0.969; CoMSIA with q ², 0.608; r ², 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein?Cligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.     

Comparative molecular field analysis and comparative molecular similarity indices analysis of hydroxyethylamine derivatives as selective human BACE-1 inhibitor

Three-dimensional quantitative structure–activity relationship (3D-QSAR) models were developed based on comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), on a series of 43 hydroxyethylamine derivatives, acting as potent inhibitors of β-site amyloid precursor protein (APP) cleavage enzyme (BACE-1). The crystal structure of the BACE-1 enzyme (PDB ID: 2HM1) with one of the most active compound 28 was available, and we assumed it to be the bioactive conformation of the studied series, for 3D-QSAR analysis. Statistically significant 3D-QSAR model was established on a training set of 34 compounds, which were validated by a test set of 9 compounds. For the best CoMFA model, the statistics are, r ² =  0.998, r²_cv = 0.810{r^{2}_{\rm cv} = 0.810} , n =  34 for the training set and r²_pred = 0.934{r^{2}_{\rm pred} = 0.934} , n = 9 for the test set. For the best CoMSIA model (combined steric, electrostatic, hydrophobic, and hydrogen bond donor fields), the statistics are r ² =  0.978, r²_cv = 0.754{r^{2}_{\rm cv} = 0.754} , n =  34 for the training set and r²_pred = 0.750{r^{2}_{\rm pred} = 0.750} , n =  9 for the test set. The resulting contour maps, produced by the best CoMFA and CoMSIA models, were used to identify the structural features relevant to the biological activity in this series of analogs. The data generated from the present study will further help to design novel, potent, and selective BACE-1 inhibitors.     

CoMFA and CoMSIA of diverse pyrrolidine analogues as dipeptidyl peptidase IV inhibitors: active site requirements

The inhibition of dipeptidyl peptidase IV (DPP-IV) has emerged as an attractive target in the treatment of type 2 diabetes. In view of this development, a critical analysis of structural requirements of the DPP-IV inhibitors is envisioned to identify the significant features toward design of selective inhibitors. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) contour plots of pyrrolidine based analogues are used to analyze the structural requirements of a DPP-IV active site. The CoMFA model has shown a cross-validated q ² of 0.651 with a non-cross-validated r ² of 0.882 and explained 70.6% variance in the activity of external test compounds. In this, the steric and electrostatic fields have respectively contributed 59.8 and 40.2%, respectively, to the explained activity of the compounds. The CoMSIA model has shown optimum predictivity (cross-validated q ² = 0.661; non-cross-validated r ² = 0.803; external test set’s predictive r ² = 0.706) with four molecular fields namely, steric, electrostatic, hydrogen bond (HB)-donor, and HB-acceptor. The contour plots of molecular fields resulting from these studies have suggested: (i) steric restriction with small electron rich substituent at 2- and 3-position of pyrrolidine ring, (ii) presence of electropositive ring linker between the pyrrolidine head and aryl tail, (iii) presence of electron-rich groups around the aryl tail moiety, and (iv) presence of sulfonamide between the ring linker and aryl tail which would increase DPP-IV binding affinity of the compounds. These findings will help in the design of structurally related/new compounds as potential DPP-IV inhibitors.     

Synthesis, in vitro antitubercular activity and 3D-QSAR study of 1,4-dihydropyridines

In continuation of our research program on new antitubercular agents, this article is a report of the synthesis of 97 various symmetrical, unsymmetrical, and N-substituted 1,4-dihydropyridines. The synthesized molecules were tested for their activity against M. tuberculosis H ₃₇Rv strain with rifampin as the standard drug. The percentage inhibition was found in the range 3–93%. In an effort to understand the relationship between structure and activity, 3D-QSAR studies were also carried out on a subset that is representative of the molecules synthesized. For the generation of the QSAR models, a training set of 35 diverse molecules representing the synthesized molecules was utilized. The molecules were aligned using the atom-fit technique. The CoMFA and CoMSIA models generated on the molecules aligned by the atom-fit method show a correlation coefficient (r ²) of 0.98 and 0.95 with cross-validated r ²(q ²) of 0.56 and 0.62, respectively. The 3D-QSAR models were externally validated against a test set of 19 molecules (aligned previously with the training set) for which the predictive ${r^{2} (r^{2}_{\rm pred})}$ is recorded as 0.74 and 0.69 for the CoMFA and CoMSIA models, respectively. The models were checked for chance correlation through y-scrambling. The QSAR models revealed the importance of the conformational flexibility of the substituents in antitubercular activity.     

Comparative docking and CoMFA analysis of curcumine derivatives as HIV-1 integrase inhibitors

The docking studies and comparative molecular field analysis (CoMFA) were performed on highly active molecules of curcumine derivatives against 3′ processing activity of HIV-1 integrase (IN) enzyme. The optimum CoMFA model was selected with statistically significant cross-validated r² value of 0.815 and non-cross validated r ² value of 0.99. The common pharmacophore of highly active molecules was used for screening of HIV-1 IN inhibitors. The high contribution of polar interactions in pharmacophore mapping is well supported by docking and CoMFA results. The results of docking, CoMFA, and pharmacophore mapping give structural insights as well as important binding features of curcumine derivatives as HIV-1 IN inhibitors which can provide guidance for the rational design of novel HIV-1 IN inhibitors.