螺环吲哚类MDM2抑制剂的分子对接、定量构效关系和分子动力学模拟

采用分子对接、三维定量构效关系(3D-QSAR)和分子动力学方法研究了21个螺环吲哚类化合物与MDM2蛋白的相互作用, 并建立了相关预测模型. 比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)模型的交互验证相关系数q²分别为0.573 和0.651, 非交互验证相关系数r²分别为0.948和0.980. 分子对接得到的结合模式与分子动力学模拟得到的结果一致, 结合模式表明该类螺环吲哚化合物主要通过疏水相互作用和氢键与MDM2结合. 基于上述相互作用模型设计并合成了6个新结构螺环吲哚化合物, 并在MDM2高表达的前列腺癌LNCaP细胞株上测定其活性, 结果表明化合物5, 6的半数抑制浓度均低于1μg·mL^-1, 可作为新的抗肿瘤药物先导化合物进一步深入研究. 本研究对以MDM2为靶点的新结构螺环吲哚类抑制剂的开发提供了理论和实验依据.     

五元杂环并嘧啶类胸苷酸合成酶抑制剂的构效关系和分子对接

用比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)研究了38个五元杂环并嘧啶衍生物类胸苷酸合成酶抑制剂的三维定量构效关系(3D-QSAR), 建立了相关预测模型. CoMFA和CoMSIA模型的交互验证相关系数q²分别为0.662和0.672、非交互验证相关系数R²分别为0.921和0.884、外部交互验证相关系数Q_ext²分别为0.85和0.81. 分子对接得到的结合模式与三维定量构效关系得到的结果一致. 结果表明这两种模型都具有良好的预测能力, 可应用于指导化合物的设计和结构修饰, 为进一步设计新型胸苷酸合成酶抑制剂提供了理论依据.     

含磷嘧啶类CDK9抑制剂的分子对接、3D-QSAR和分子动力学模拟

选取64个具有潜力的含磷嘧啶类细胞周期依赖性蛋白激酶(CDK9)小分子抑制剂,采用分子对接方法研究了该类小分子与CDK9的结合作用,结果表明,分子构象、氢键形成、疏水性和氨基酸残基Cys106在此类抑制剂与CDK9的结合过程中具有重要作用.在配体叠合的基础上,运用比较分子力场分析(Co MFA)、比较分子相似性指数分析(Co MSIA)和Topomer Co MFA(T-COMFA)研究了分子结构与抑制活性的关系,发现由训练集立体场、静电场和疏水场组合的Co MSIA模型为最优模型,其内部交叉验证相关系数(Q2=0.557)、非交叉验证相关系数(R2=0.959)和外部预测相关系数(r2=0.863)具有统计学意义,该模型的三维等值线图直观显示了化合物的活性与其三维结构的关系.根据这些结果设计了10个具有新结构的含磷嘧啶类化合物,分子对接和分子动力学模拟结果表明,新化合物和CDK9的结合模式与原化合物64相同,自由能分析从理论上证明了新化合物64d的CDK9抑制活性优于化合物64,并且显示含磷基团与残基Asp109的静电场能在化合物与CDK9作用过程中有重要作用.     

3C-like蛋白酶抑制剂的构效关系、分子对接和分子动力学

3C-like蛋白酶是中东呼吸综合征冠状病毒（MERS-CoV）等其它冠状病毒的繁殖过程中极为重要的蛋白酶。它已成为人类在抗冠状病毒领域中的研究热点。本文基于计算生物学方法对与MERS-CoV同属的蝙蝠冠状病毒HKU4（HKU4-CoV）的43个肽类3C-like蛋白酶抑制剂分子,建立三维定量构效关系（3D-QSAR）模型。在基于配体叠合的基础上,发现比较分子相似性指数分析法（CoMSIA）中的四个场组合（位阻场、静电场、氢键供体场与氢键受体场）为最优的模型（Q²=0.522,R_ncv²=0.996,R_pre²=0.904;Q²：交叉验证相关系数,R_ncv²：非交叉验证相关系数,R_pre²：验证集分子的预测值相关系数）,并借助该模型通过分子对接（docking）与分子动力学（MD）方法阐明了配受体结合作用。实验结果表明：（1）基于最优的CoMSIA模型基础上的三维等势图形象地说明了分子基团的位阻作用、静电作用、氢键供体与氢键受体作用对分子生物活性的影响;（2）分子对接研究结果显示了疏水性以及结晶水、氨基酸His166和Glu169在配体和受体结合过程中产生重要作用;（3）分子动力学模拟进一步验证了分子对接模型的可靠性,并发现了两个新的关键氨基酸Ser24与Gln192,它们与配体产生了两个较强的氢键。此外,根据这些结果,一些新的具有潜在抑制活性的肽类化合物作为3C-like蛋白酶抑制剂被获得。以上结果能够帮助深入了解3C-like蛋白酶与肽类抑制剂的作用机理,并且能够为今后的抗MERS-CoV药物设计提供有价值的参考。     

Design of Novel IRAK4 Inhibitors Using Molecular Docking,Dynamics Simulation and 3D-QSAR Studies

Treatment of several autoimmune diseases and types of cancer has been an intense area of research over the past two decades. Many signaling pathways that regulate innate and/or adaptive immunity, as well as those that induce overexpression or mutation of protein kinases, have been targeted for drug discovery. One of the serine/threonine kinases, Interleukin-1 Receptor Associated Kinase 4 (IRAK4) regulates signaling through various Toll-like receptors (TLRs) and interleukin-1 receptor (IL1R). It controls diverse cellular processes including inflammation, apoptosis, and cellular differentiation. MyD88 gain-of-function mutations or overexpression of IRAK4 has been implicated in various types of malignancies such as Waldenström macroglobulinemia, B cell lymphoma, colorectal cancer, pancreatic ductal adenocarcinoma, breast cancer, etc. Moreover, over activation of IRAK4 is also associated with several autoimmune diseases. The significant role of IRAK4 makes it an interesting target for the discovery and development of potent small molecule inhibitors. A few potent IRAK4 inhibitors such as PF-06650833, RA9 and BAY1834845 have recently entered phase I/II clinical trial studies. Nevertheless, there is still a need of selective inhibitors for the treatment of cancer and various autoimmune diseases. A great need for the same intrigued us to perform molecular modeling studies on 4,6-diaminonicotinamide derivatives as IRAK4 inhibitors. We performed molecular docking and dynamics simulation of 50 ns for one of the most active compounds of the dataset. We also carried out MM-PBSA binding free energy calculation to identify the active site residues, interactions of which are contributing to the total binding energy. The final 50 ns conformation of the most active compound was selected to perform dataset alignment in a 3D-QSAR study. Generated RF-CoMFA (q² = 0.751, ONC = 4, r² = 0.911) model revealed reasonable statistical results. Overall results of molecular dynamics simulation, MM-PBSA binding free energy calculation and RF-CoMFA model revealed important active site residues of IRAK4 and necessary structural properties of ligand to design more potent IRAK4 inhibitors. We designed few IRAK4 inhibitors based on these results, which possessed higher activity (predicted pIC₅₀) than the most active compounds of the dataset selected for this study. Moreover, ADMET properties of these inhibitors revealed promising results and need to be validated using experimental studies.     

QSAR and Docking Studies of Thiazolidine-4-carboxylic Acid Derivatives as Neuraminidase Inhibitors

In order to understand the chemical-biological interactions governing their activities toward neuraminidase(NA), QSAR models of 28 thiazolidine-4-carboxylic acid derivatives with inhibitory influenza A virus were developed. Here a quantitative structure activity relationship(QSAR) model was built by three-dimensional holographic atomic vector field(3 D-HoVAIF) and multiple linear regression(MLR). The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations. The correlation coefficient(R2) of established MLR model was 0.984, and the cross-validated correlation coefficient(Q2) of MLR model was 0.947. Furthermore, the cross-validated correlation coefficient for the test set(Qext2) was 0.967. The binding mode pattern of the compounds to the binding site of integrase enzyme was confirmed by docking studies. The results of present study indicated that this model can aid in designing more potent neuraminidase inhibitors.     

二氢嘧啶并[4,5-d]嘧啶类衍生物作为集落刺激因子-1受体激酶抑制剂的分子对接和定量构效关系研究

集落刺激因子-1受体激酶（CSF-1R）属于Ⅲ型受体酪氨酸激酶家族成员,其在调控单核巨噬细胞系中发挥重要作用。CSF-1R及其配体异常表达与肿瘤发展过程密切相关。因此,CSF-1R信号传导可成为抗肿瘤治疗的有吸引力的靶标。本文用比较分子场分析法（CoMFA）和比较分子相似性指数分析法（CoMSIA）研究了54个二氢嘧啶并[4,5-d]嘧啶类CSF-1R激酶抑制剂的三维定量构效关系（3D-QSAR）。基于配体叠合,CoMFA和CoMSIA模型的交叉验证系数（q2）分别为0.725和0.636,拟合验证系数（r2）分别为0.960和0.958,结果表明这两种模型均具有较好的预测能力。所建模型的等势图能直观反映分子不同取代基对活性的影响,其中立体场和疏水场对活性的贡献较大。通过分子对接研究显示,氨基酸残基Cys666、Asp796在配体和受体结合过程中产生作用,分子对接的结合模式与3D-QSAR得到的结果一致。这些信息为进一步优化CSF-1R激酶抑制剂提供了理论基础。     

Molecular Docking, 3D-QSAR and Molecular Dynamics Simulation Studies of Substituted Pyrimidines as Selective Covalent Janus Kinase 3 Inhibitors

Janus kinase 3(JAK3) is a member of Janus kinase(JAK) family, and it represents a promising target for the treatment of immune diseases and cancers. However, no highly selective inhibitors of JAK3 have been developed. For discovering the binding mechanism of JAK3 and these inhibitors, a molecular modeling study combining molecular docking, three-dimensional quantitative structure-activity relationships(3D-QSAR), molecular dynamics and binding free energy calculations was performed on a series of pyrimidine-based compounds which could bind with the unique residue Cys909 of JAK3 kinase as the selective inhibitors of JAK3 in this work. The optimum Co MFA and Co MSIA models were generated based on the conformations obtained by molecular docking. The results showed that the models have satisfactory predicted capacity in both internal and external validation. Furthermore, a 50 ns molecular dynamics simulation was carried out to determine the detailed binding process of inhibitors with different activities. It was demonstrated that hydrogen bond interactions with Leu828, Glu903, Tyr904, Leu905 and Leu956 of JAK3 are significant for activity increase, and the Van der Waals interaction is mainly responsible for stable complex.     

Topomer CoMFA,HQSAR Studies and Molecular Docking of 2,5-Diketopiperazine Derivatives as Oxytocin Inhibitors

Topomer comparative molecular field analysis(Topomer Co MFA) and holographic quantitative structure-activity relationship(HQSAR) for 130 2,5-diketopiperazine derivatives were used to build a three-dimensional quantitative structure-activity relationship(3D-QSAR) model. The results show that the models have high predictive ability. For Topomer CoMFA, the cross-validated q~2 value is 0.710 and the non-cross-validated r~2 value is 0.834. The most effective HQSAR model shows that the cross-validation q~2 value is 0.700, the non-cross-validated r~2 value is 0.815, and the best hologram length value is 353 using connections and bonds as fragment distinctions. 50 highly active 2,5-diketopiperazine derivatives were designed based on the three-dimensional equipotential map and HQSAR color code map. Finally, the molecular docking method was also used to study the interactions of these new molecules by docking the ligands into the diketopiperazine active site, which revealed the likely bioactive conformations. This study showed that there are extensive interactions between the new molecule and Arg156, Arg122 residues in the active site of diketopiperazine. These results provide useful insights for the design of potent of the new 2,5-diketopiperazine derivatives.     

马来酰胺类糖原合成酶激酶-3β抑制剂的分子对接和三维定量构效关系

通过分子对接和三维定量构效关系(3D-QSAR)两种方法来确定两类马来酰胺类的糖原合成酶激酶-3β(GSK-3β)抑制剂的结合方式. 首先, 用分子对接确定抑制剂与GSK-3β结合模式及其相互作用; 然后用比较分子力场分析法(CoMFA)与比较分子相似性指数分析法(CoMSIA)对48个化合物做三维定量构效关系的分析. 两种方法得出的交互验证回归系数分别为0.669(CoMFA)和0.683(CoMSIA), 证明该模型具有很好的统计相关性, 同时也说明该模型具有较高的预测能力.根据该模型提供的信息, 设计出9个预测活性较好的分子.     

苯并咪唑类缓蚀剂的HQSAR研究及分子设计

采用分子全息定量构效关系(HQSAR)方法, 构建苯并咪唑衍生物在酸性环境中的缓蚀性能与结构之间的定量构效关系模型, 研究不同碎片区分参数及碎片大小对模型质量的影响, 寻找最优HQSAR模型, 并对其稳定性及预测能力进行评价. 结果显示: 选取碎片区分参数为原子类型(A)、化学键类型(B)、连接性(C)、氢原子(H)、手性(Ch)、氢键给体和受体(D&;A), 碎片大小为1-3 建模时, 得到的HQSAR 模型(r²(非交叉验证系数)=0.996, q²(交叉验证系数)=0.960, SE_cv(交叉验证标准误差)=3.709)具有良好的统计学稳定性及预测能力. 根据最优HQSAR模型图设计出的38种苯并咪唑类化合物理论上均具有较好的缓蚀性能. 本研究为油气田新型高效缓蚀剂研发提供可靠的理论依据.     

N-取代马来酰亚胺类hMGL抑制剂的3D-QSAR、分子对接和分子动力学研究

本文通过三维定量构效关系(3D-QSAR)建模、分子对接和分子动力学模拟,探讨了41个N-取代马来酰亚胺类衍生物与人单酰甘油脂肪酶(hMGL)的相互作用,并构建了相关模型。其中,比较分子力场分析模型(CoMFA、q₂ ^{= 0. 5}41、r₂ ^{= 0. 9}72)和比较分子相似性指数分析模型(CoMSIA、q₂ ^{= 0. 5}88、r₂ ^{= 0. 9}19)具有较好的预测能力。QSAR模型等势图阐明了该系列化合物生物活性与结构的关系,并依此设计了系列衍生物。采用分子对接和分子动力学模拟探讨了高活性化合物36、46与hMGL(PDB ID: 3PE6)的结合模式和稳定性,结果表明二者主要通过氢键和疏水相互作用与hMGL结合并且形成了稳定的复合物。随后对pIC₅₀预测值优于文献报道中最高活性化合物36的8个衍生物进行分子对接和ADMET预测,选择2个衍生物进行分子动力学模拟,结果表明2个衍生物分别与hMGL形成的复合物结合构象稳定。本研究为新型N-取代马来酰亚胺类单酰甘油脂肪酶抑制剂的开发提供了理论依据。     

咪唑啉衍生物缓蚀剂的定量构效关系及分子设计

采用量子化学密度泛函理论(DFT)及线性回归分析方法, 对十一烷基咪唑啉衍生物缓蚀剂抗H2S、CO2腐蚀性能进行了定量构效关系(QSAR)研究. 通过回归分析, 筛选出了影响缓蚀剂缓蚀性能的主要因素, 建立了QSAR模型, 并使用留一法交叉验证对模型的稳定性及预测能力进行了分析. 结果表明, 电子转移参数△N、咪唑环上非氢原子静电荷之和∑Qring及分子极化率α对咪唑啉类缓蚀剂的缓蚀性能有很大的贡献, 所得模型的拟合相关系数(R2)和交叉验证相关系数(q2)分别为0.924 和0.917, 模型对此类缓蚀剂抗H2S、CO2腐蚀性能具有较好的预测效果. 应用QSAR研究结果进行了分子设计, 在理论上提出了一些具有较高抗H2S、CO2腐蚀性能的新型咪唑啉衍生物, 为实验工作者合成新型缓蚀剂提供理论参考.     

From Myricetin to the Discovery of Novel Natural Human ENPP1 Inhibitors: A Virtual Screening,Molecular Docking,Molecular Dynamics Simulation,and MM/GBSA Study

It was recently revealed that naturally occurring myricetin can inhibit ectonucleotidase ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), which, in turn, can treat ischemic cardiac injury. However, due to myricetin’s poor druggability, its further developments are relatively limited, which necessitates the discovery of novel ENPP1-inhibiting myricetin analogs as alternatives. In this study, the binding model of myricetin with ENPP1 was elucidated by molecular docking and molecular dynamics studies. Subsequently, virtual screening on the self-developed flavonoid natural product database (FNPD), led to the identification of two flavonoid glycosides (Cas No: 1397173-50-0 and 1169835-58-8), as potential ENPP1 inhibitors. Docking scores and MM/GBSA binding energies predicted that they might have higher inhibitory effects than myricetin. This study provides a strong foundation for the future development of ischemic cardiac injury drugs.     

苯并咪唑类缓蚀剂的3D-QSAR研究及分子设计

采用比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA), 对苯并咪唑衍生物抗盐酸腐蚀的缓蚀性能进行了三维定量构效关系研究, 并使用留一法交叉验证手段对3D-QSAR模型的稳定性及预测能力进行了分析. 结果表明, 立体场、静电场和氢键供体场(电子给体)是影响苯并咪唑缓蚀剂缓蚀性能的主要因素; 所构建的CoMFA模型(q2=0.541, R2=0.996)和CoMSIA模型(q2=0.581, R2=0.987)均具有较好的统计学稳定性和预测能力. 基于3D-QSAR等势图设计出了几种具有较好缓蚀性能的苯并咪唑化合物, 为油气田新型缓蚀剂的研发提供了一种新思路.     

Discovery of Novel Acetaldehyde Dehydrogenase 1A1(ALDH1A1) Inhibitors by Utilizing 3D-QSAR,Molecular Docking and Molecular Dynamics Simulation

Acetaldehyde dehydrogenase 1A1 is a hopeful therapeutic target to ovarian cancer. In this present work, 3D-QSAR, molecular docking and molecular dynamics(MD) simulations were implemented on a series of quinoline-based ALDH1A1 inhibitors to investigate novel acetaldehyde dehydrogenase 1A1 inhibitors as anticancer adjuvant drugs for ovarian cancer. Two reliable CoMFA(Q~2 = 0.583, R~2 = 0.967) and CoMSIA(Q~2 = 0.640, R~2 = 0.977) models of ALDH1A1 inhibitors were established. Novel ALDH1A1 inhibitors were predicted by the 3D-QSAR models. Molecular docking reveals important residues for protein-compound interactions, and the results revealed ALDH1A1 inhibitors had stronger electrostatic interaction and binding affinity with key residues of protein, such as Phe171, Val174 and Cys303. Molecular dynamics simulations further verified the results of molecular docking. The above information provided significant guidance for the design of novel ALDH1A1 inhibitors.     

Novel 4-Azapregnene Derivatives as Potential Anticancer Agents: Synthesis,Antiproliferative Activity and Molecular Docking Studies

A series of novel 21E-arylidene-4-azapregn-5-ene steroids has been successfully designed, synthesized and structurally characterized, and their antiproliferative activity was evaluated in four different cell lines. Within this group, the 21E-(pyridin-3-yl)methylidene derivative exhibited significant cytotoxic activity in hormone-dependent cells LNCaP (IC₅₀ = 10.20 µM) and T47-D cells (IC₅₀ = 1.33 µM). In PC-3 androgen-independent cells, the steroid 21E-p-nitrophenylidene-4-azapregn-5-ene was the most potent of this series (IC₅₀ = 3.29 µM). Considering these results, the 21E-(pyridin-3-yl)methylidene derivative was chosen for further biological studies on T47-D and LNCaP cells, and it was shown that this azasteroid seems to lead T47-D cells to apoptotic death. Finally, molecular docking studies were performed to explore the affinity of these 4-azapregnene derivatives to several steroid targets, namely 5α-reductase type 2, estrogen receptor α, androgen receptor and CYP17A1. In general, compounds presented higher affinity to 5α-reductase type 2 and estrogen receptor α.     

HIV-1整合酶链转移抑制剂的3D-QSAR、分子对接和分子动力学模拟研究

为了获得高活性、结构新颖的整合酶链转移(INST)抑制剂,本文采用Co MFA和Co MSIA两种方法对32个萘啶类INST抑制剂进行了三维定量构效关系研究,并建立了相关模型,其交叉验证系数分别为q~2=0. 809和q~2=0. 816,拟合验证系数分别为r~2=0. 998和r~2=0. 981,表明所建立的模型是可靠的且具有一定的预测能力。利用分子对接探讨小分子化合物与INST蛋白的相互作用模式,结果表明,萘啶类化合物主要通过疏水作用和氢键作用与INSTIs蛋白结合。最后通过分子动力学模拟进一步验证对接结果发现,对接的结合模式与分子动力学模拟得到的结果是一致的。本研究获得的综合模型和推论可以为开发有效的HIV INSTIs提供重要的理论信息。     

New Triazinoindole Bearing Benzimidazole/Benzoxazole Hybrids Analogs as Potent Inhibitors of Urease: Synthesis,In Vitro Analysis and Molecular Docking Studies

Twenty-four analogs based on triazinoindole bearing benzimidazole/benzoxazole moieties (1–25) were synthesized. Utilizing a variety of spectroscopic methods, including ¹H-, ¹³C-NMR, and HREI-MS, the newly afforded compounds (1–25) were analyzed. The synthesized analogs were tested against urease enzyme (in vitro) as compared to the standard thiourea drug. All triazinoindole-based benzimidazole/benzoxazole analogs (1–25) exhibited moderate to excellent inhibition profiles, having IC₅₀ values of 0.20 ± 0.01 to 36.20 ± 0.70 μM when evaluated under the positive control of thiourea as a standard drug. To better understand the structure–activity relationship, the synthesized compounds were split into two groups, “A” and “B.” Among category “A” analogs, analogs 8 (bearing tri-hydroxy substitutions at the 2,4,6-position of aryl ring C) and 5 (bearing di-hydroxy substitutions at the 3,4-position of aryl ring C) emerged as the most potent inhibitors of urease enzyme and displayed many times more potency than a standard thiourea drug. Besides that, analog 22 (which holds di-hydroxy substitutions at the 2,3-position of the aryl ring) and analog 23 (bearing ortho-fluoro substitution) showed ten-fold-enhanced inhibitory potential compared to standard thiourea among category “B” analogs. Molecular docking studies on the active analogs of each category were performed; the results obtained revealed that the presence of hydroxy and fluoro-substitutions on different positions of aryl ring C play a pivotal role in binding interactions with the active site of the targeted urease enzyme.     

3MBA类FtsZ蛋白抑制剂的分子动力学模拟及抗菌作用机制

采用分子动力学模拟、蛋白质二级结构测定(DSSP)、口袋体积测量(POVME)以及MM-PBSA(molecular mechanics Poisson-Boltzmann surface area)方法, 系统研究了金黄色葡萄球菌丝状温度敏感性蛋白Z (SaFtsZ)-二磷酸鸟苷(GDP)二元复合物和SaFtsZ-GDP-3MBA (3-甲氧基苯甲酰胺)类衍生物三元复合物体系的稳定性、蛋白质二级结构、蛋白质构象、关键残基质心距、活性口袋体积以及相对结合自由能的变化规律. 研究表明: 当不含抑制剂存在时SaFtsZ-GDP二元复合物体系稳定性较差, 其T7Loop区域残基(203-209)波动较大, 且蛋白二级结构发生明显变化, 活性口袋体积急剧减小, 底物通道显著变窄且不稳定. 而含有抑制剂PC190723、Compound1 的类衍生物三元复合物体系的表现截然不同, 这主要是由于它们均能和活性口袋T7Loop区周围残基形成关键性的氢键以及疏水作用, 与FtsZ 蛋白紧密结合. 在SaFtsZ-GDP-3MBA三元复合物体系中, 3MBA仅能与活性口袋中部分残基形成疏水作用, 与FtsZ 蛋白亲和力较弱, 使其不能稳定地存在于活性口袋中, 进一步导致它的抗菌活性明显低于PC190723、Compound1. 这些发现深入揭示了3MBA类衍生物对FtsZ 蛋白的作用机制和影响规律, 为该类FtsZ 蛋白抑制剂的结构优化和产品开发应用提供了重要的理论依据.