4-苯胺喹唑啉类化合物合成研究进展

4-苯胺喹唑啉类化合物是一类具有广泛药理活性的喹唑啉类生物碱,在酪氨酸激酶受体(EGFR)抑制剂的研发中具有重要的作用。已经上市的此类药物有吉非替尼(gefitinib)和厄洛替尼(erlotinib)等。此类化合物的合成都是经过喹唑啉酮中间体或直接环合成4-苯胺喹唑啉。苯甲醛及其衍生物被用作反应原料,两种合成路线都要经历对苯甲醛的硝化及硝基的还原两步反应。笔者经查阅资料,设计并验证了以苯胺为原料、经靛红中间体得到4-苯胺喹唑啉类化合物的新的合成路线。本文依据这两种合成策略综述了4-苯胺喹唑啉类化合物的合成方法,并对各种方法的优缺点进行了总结,为进一步研究4-苯胺喹唑啉合成及设计具有药理活性的新化合物提供参考。     

表皮生长因子受体和抑制剂之间分子对接的研究

研究了表皮生长因子受体(EGFR)和4-苯胺喹唑啉类抑制剂之间的相互作用模式，表皮生长因子受体的三维结构通过同源蛋白模建的方法得到，而抑制剂和靶酶结合复合物结构则通过分子力学和分子动力学结合的方法计算得到。从模拟结果得到的抑制剂和靶酶之间的相互作用模式表明范德华相互作用、疏水相互作用以及氢键相互作用对抑制剂的活性都有重要的影响，抑制剂的苯胺部分位于活性口袋的底部，能够与受体残基的非极性侧链产生很强的范德华和疏水相互作用，抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏水性相互作用，而抑制剂喹唑啉环上的氮原子能和周围的残基形成较强的氢键相互作用，对抑制剂的活性有较大的影响，计算得到抑制剂和靶酶之间的非键相互作用能以及抑制剂和靶酶之间的相互作用信息能够很好地解释抑制剂活性和结构的关系，为全新抑制剂的设计提供了重要的结构信息。     

新型喹唑啉类PDE7抑制剂类似物的合成

以邻氨基苯甲酸为原料,经溴代和环合反应合成了4个新型喹唑啉类PDE7抑制剂类似物,其结构经1H NMR和ESI-MS表征。     

4-苯胺喹唑啉类化合物的合成与抗癌活性初步研究

以香兰素为起始原料,经过氰基化、醚化、硝化、还原和环化反应,合成了一系列新型的含二苯乙烯结构单元的4-芳胺基喹唑啉类衍生物。化合物的结构经IR、1H NMR和13C NMR确证,并采用MTT法对SMMC-7721(人肝癌细胞)、SK-OV-3(人卵巢癌细胞)等几种常见肿瘤细胞进行了初步体外抗肿瘤活性实验。结果表明合成的化合物均具有良好的抑制肿瘤细胞生长的作用。     

新型4-取代苯胺喹唑啉衍生物的合成与抗肿瘤活性研究

以6-碘喹唑啉-4-酮为原料,经氯代、胺化、Suzuki偶联、Wittig-horner等反应合成了7个新型的4 取代苯胺喹唑啉衍生物(5a~5g),其结构经¹H NMR和HR-MS(ESI)表征。采用MTT法研究了5a~5g对人乳腺癌细胞(MCF-7)、人肺癌细胞(A549)和人皮肤鳞癌细胞（A431）的抑制活性。结果表明：5a~5g对肿瘤细胞均具有明显的抑制活性;其中5e的抑制活性(IC₅₀=0.13~5.26 μmol·L^-1)优于拉帕替尼(IC₅₀=0.21~15.56 μmol·L^-1)。     

新型4-氨基喹唑啉衍生物的合成与抗癌活性研究

以香草醛(香兰素)为起始原料,合成了5个未见报道的化合物8a～8e。所得化合物由MS、IR、1H NMR、13C NMR和元素分析表征确认。其中,化合物8c和8e在10μmol/L药剂浓度下对人乳腺癌细胞Bcap-37的抑制率分别为88.1%和72.9%,值得进一步研究。     

4-苯氨基喹唑啉类衍生物的合成、表征及晶体结构

以香草醛为原料,经过7个步骤合成得到了12个新的4-苯氨基喹唑啉类化合物8a～81,产物的结构经1H NMR,13C NMR,IR,MS和元素分析确认,并用X射线衍射法测定化合物8b的晶体结构.化合物8b属三斜晶系,P-l空间群,晶胞参数:α=0.8868(5)nm,b=1.0239(6)nm,c=1.4515(9)nm,α=71.02(2)°,β=82.42(2)°,γ=71.78(2)°,V=1.1831 um3,Z=2,Dc=1.430Mg/m3,μ(MoKα)=1.773mm-1,λ=0.071073nm,F(000)=522.     

4-硫醚基喹唑啉类化合物的合成及抑菌活性研究

以4-氯喹唑啉和巯基化合物为原料, 丙酮作溶剂, 碳酸钾作缚酸剂, 合成了7个新型4-硫醚基喹唑啉类化合物. 采用¹H NMR, ¹³C NMR, IR及元素分析对目标化合物的结构进行了表征. 生物活性测试表明, 化合物1d在50 μg•mL^－1 药剂浓度下对小麦赤霉病菌、辣椒枯萎病菌、苹果腐烂病菌的抑菌活性分别达到69.5%, 71.9%和70.8%, EC₅₀分别为25.88, 17.08和28.77 μg•mL^－1.     

N-取代芳环-4-氨基喹唑啉类化合物的合成及生物活性研究

以4-氯喹唑啉和芳香胺反应,合成了三个新的N-取代苯环或杂环4-氨基喹唑啉类化合物.三个新化合物经1HNMR,IR及元素分析证明其结构.生物活性测试表明,三个新化合物均有一定的抑菌效果.     

新型喹唑啉类酪氨酸激酶化学抑制剂的设计与合成

以6-氨基藜芦酸和醋酸甲脒为起始原料,合成了一系列4-位具有不同芳胺基团,6,7-位引入不同取代基的新型喹唑啉类酪氨酸激酶化学抑制剂,其结构经1H NMR表征.     

Free energy perturbation and MM/PBSA studies on inclusion complexes of some structurally related compounds with β-cyclodextrin

Molecular dynamics (MD) simulations have been conducted to explore time-resolved guest–host interactions involving inclusion complex formation between β-cyclodextrin and organic molecules bearing two peripheral benzene rings in aqueous solution. Moreover, free energy perturbation (FEP) and thermodynamic integration (TI) methods at different simulation times have been employed to estimate the relative free energy of complexation. Also, the less computer-time demanding molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) method was used to estimate the free energy of complexation based on only 1-ns MD simulation. Results showed that both FEP and TI methods were able to reasonably reproduce the experimental thermodynamic quantities. However, long simulation times (e.g. 15 ns) were needed for benzoin mutating to benzanilide (BAN), while moderately shorter times were sufficient for BAN mutating to phenyl benzoate and for benzilic acid mutating to diphenylacetic acid. The results have been discussed in the light of the differences in the chemical structural and conformational features of the guest molecules. In general, it was apparent that the TI method requires less time for convergence of results than the FEP method. However, the less expensive MM/PBSA method proved capable of producing results that are in agreement with those of the more expensive TI and FEP methods.     

Hot spot computational identification: Application to the complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10

The definition and comprehension of the hot spots in an interface is a subject of primary interest for a variety of fields, including structure‐based drug design. Therefore, to achieve an alanine mutagenesis computational approach that is at the same time accurate and predictive, capable of reproducing the experimental mutagenesis values is a major challenge in the computational biochemistry field. Antibody/protein antigen complexes provide one of the greatest models to study protein–protein recognition process because they have three fundamentally features: specificity, high complementary association and a small epitope restricted to the diminutive complementary determining regions (CDR) region, while the remainder of the antibody is largely invariant. Thus, we apply a computational mutational methodological approach to the study of the antigen–antibody complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10. A critical evaluation that focuses essentially on the limitations and advantages between different computational methods for hot spot determination, as well as between experimental and computational methodological approaches, is presented. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking

In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high-throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein-ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein-ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free-energy estimations and is efficient to re-score the top-hit poses produced by other less-accurate scoring functions.     

Can MM‐PBSA calculations predict the specificities of protein kinase inhibitors?

An application of the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) protocol to the prediction of protein kinase inhibitor selectivity is presented. Six different inhibitors are placed in equivalent orientations in each of six different receptors. Fully solvated molecular dynamics is then run for 1 ns on each of the 36 complexes, and the resulting trajectories scored, using the implicit solvent model. The results show some correlation with experimentally-determined specificities; anomalies may be attributed to a variety of causes, including difficulties in quantifying induced fit penalties and variabilities in normal modes calculations. Decomposing interaction energies on a per-residue basis yields more useful insights into the natures of the binding modes and suggests that the real value of such calculations lies in understanding interactions rather than outright prediction.     

On Restraints in End-Point Protein–Ligand Binding Free Energy Calculations

The impact of harmonic restraints on protein heavy atoms and ligand atoms on end-point free energy calculations is systematically characterized for 54 protein–ligand complexes. We observe that stronger restraints reduce the equilibration time and statistical inefficiency, suppress conformational sampling, influence correlation with experiment, and monotonically decrease the estimated loss of entropy upon binding, leading to stronger estimated binding free energies in most systems. A statistical estimator that reweights for the biasing potential and includes data prior to the estimated equilibration time has the highest correlation with experiment. A spring constant of 20 cal mol⁻¹ Å⁻² maintains a near-native energy landscape and suppresses artifactual energy minima while minimally limiting thermal fluctuations about the crystal structure. © 2019 Wiley Periodicals, Inc.     

Is inhibition process better described with MD(QM/MM) simulations? The case of urokinase type plasminogen activator inhibitors

Urokinase plasminogen activator (uPA) is an enzyme involved in cancer growth and metastasis. Therefore, the design of inhibitors of uPA is of high therapeutic value, and several chemical families have been explored, even if none has still emerged, emphasizing the need of a rationalized approach. This work represents a complete computational study of uPA complexed with five inhibitors, which present weak similarities. Molecular dynamics simulations in explicit solvent were conducted, and structural analyses, along with molecular mechanics (MM)/Poisson-Boltzmann surface area free energies estimations, yield precious structure-activity relationships of these inhibitors. Besides, we realized supplemental QM/MM computations that improved drastically the quality of our models providing original information on the hydrogen bonds and charge transfer effects, which are, most often, neglected in other studies. We suggest that these simulations and analyses could be reproduced for other systems involving protein/ligand molecular recognitions.     

Crystal molecular dynamics simulations to speed up MM/PB(GB)SA evaluation of binding free energies of di-mannose deoxy analogs with P51G-m4-Cyanovirin-N

Complexes of two Cyanovirin-N (CVN) mutants, m4-CVN and P51G-m4-CVN, with deoxy di-mannose analogs were employed as models to generate conformational ensembles using explicit water Molecular Dynamics (MD) simulations in solution and in crystal environment. The results were utilized for evaluation of binding free energies with the molecular mechanics Poisson-Boltzmann (or Generalized Born) surface area, MM/PB(GB)SA, methods. The calculations provided the ranking of deoxy di-mannose ligands affinity in agreement with available qualitative experimental evidences. This confirms the importance of the hydrogen-bond network between di-mannose 3'- and 4'-hydroxyl groups and the protein binding site B(M) as a basis of the CVN activity as an effective HIV fusion inhibitor. Comparison of binding free energies averaged over snapshots from the solution and crystal simulations showed high promises in the use of the crystal matrix for acceleration of the conformational ensemble generation, the most time consuming step in MM/PB(GB)SA approach. Correlation between energy values based on solution versus crystal ensembles is 0.95 for both MM/PBSA and MM/GBSA methods.     

基于分子动力学模拟和连续介质模型的自由能计算方法*

近些年,基于分子动力学模拟和连续介质模型的自由能计算方法受到了越来越多的关注,其中MM/PBSA就是最具代表性的方法.在MM/PBSA中,体系的焓变采用分子力学(MM)的方法计算得到;溶剂效应中极性部分对自由能的贡献通过解Poisson-Boltzmann(PB)方程的方法计算得到;溶液效应中非极性部分对自由能的贡献则通过分子表面积(SA)计算得到.本文结合我们科研组的工作,就近几年MM/PBSA方法的最新进展做了较为详细的阐述,同时对MM/PBSA的发展前景进行了展望.     

HIV-1整合酶与芳香二酮酸类抑制剂相互作用的分子模拟研究

用分子对接方法研究了一系列芳香二酮酸类抑制剂与HIV-1整合酶的识别及相互作用. 结果表明, 抑制剂结合到整合酶Asp64～Leu68, Thr115～Phe121, Gln148～Lys159和Mg2＋所构成的口袋区, 抑制机理与5CITEP相似. 采用分子动力学模拟和MM/PBSA方法计算了芳香二酮酸类抑制剂与整合酶之间的结合自由能, 计算结果与实验值相吻合, 平均绝对偏差为3.6 kJ/mol, 体系范德华相互作用和溶剂化效应的非极性项是利于形成复合物的主要因素. 相关性分析结果表明, 结合自由能值与疏水相互作用有较强的线性相关(R＝0.61), 基于此, 用多元线性回归方法给出了一个能较强预测芳香二酮酸类抑制剂与HIV-1整合酶的结合自由能预测模型, 为后续基于抑制剂结构的抗HIV-1药物分子设计提供指导.     

HIV-1蛋白酶与抑制剂作用的结合自由能计算

HIV-1蛋白酶是治疗艾滋病的重要靶标酶之一. 采用分子动力学模拟, 运用MM-PBSA方法计算了HIV-1蛋白酶与三个抑制剂BE4, BE5和BE6的结合自由能, 结果表明抑制剂P₁/ 位置的苄基上双氟原子的不同位置对结合自由能产生不同的影响. 通过能量分解的方法考察了HIV-1蛋白酶的主要残基与三个抑制剂间的相互作用与识别, 结果表明三个抑制剂以相同的作用模式与HIV-1蛋白酶结合, 计算结果与实验结果基本吻合.