咪唑[1,2-b]哒嗪类m TOR抑制剂的三维定量构效关系及分子对接研究

目的:建立咪唑[1,2-b]哒嗪类m TOR抑制剂的三维定量构效关系(3D-QSAR)和分子对接模型。结合两个模型实验结果,分析化合物的结构与其生物活性间关系。方法 采用比较分子分析法(Co MFA)和比较分子相似性指数分析法(Co MSIA)来研究咪唑[1,2-b]哒嗪类m TOR抑制剂的三维定量构效关系,用分子对接方法来研究化合物与受体蛋白之间的相互作用模式。结果:建立了可靠、合理的咪唑[1,2-b]哒嗪类m TOR抑制剂Co MFA(q2=0.628,r2=0.989,r2pred=0.991)和Co MSIA(q2=0.593,r2=0.988,r2pred=0.989)模型。通过分析分子对接模型得出化合物与受体蛋白之间有关键的氢键连接。设计出了新化合物并预测了活性。结论:根据3DQSAR模型得到咪唑[1,2-b]哒嗪类m TOR抑制剂的结构与生物活性之间的关系,分析分子对接模型发现化合物与受体蛋白之间的作用关系,基于以上设计出了具有较好活性的新化合物。实验的研究发现为该类m TOR抑制剂的设计优化提供了思路。     

细胞周期素依赖性激酶活性中心残基与其抑制剂相互作用机制研究

以16个2-氨基噻唑衍生物抑制剂为研究对象,利用AutoDock4.2软件进行了分子对接,分析抑制剂分子和细胞周期素依赖性激酶(CDK2)的结合情况。研究结果显示,活性中心残基Leu83主干上的羰基和氨基分别与抑制剂分子C9原子上的氨基和噻唑环上的N原子形成氢键,Glu81主干上的羰基和抑制剂分子C8上的氨基形成氢键,Phe80侧链上苯基和抑制剂母体分子上的苯基形成了π-π堆积作用,CDK2通过与抑制剂分子之间形成的氢键网络和π-π堆积作用将小分子固定在CDK2的活性中心。     

新型吡唑-苯并咪唑酮类人类HPPD抑制剂的3D-QSAR研究

对-羟苯基丙酮酸双氧化酶(HPPD)是治疗络氨酸Ⅰ型血症的重要靶标。HPPD抑制剂可以有效的缓解络氨酸Ⅰ型血症症状。文章针对33个以吡唑-苯并咪唑酮为基本骨架的HPPD抑制剂,分别运用比较分子场分析(Co MFA)和比较分子相似性分析(Co MSIA)两种经典方法进行了三维定量构效关系(3D-QSAR)研究,并获得了预测能力较优的两个模型(Co MFA:q2=0.792,r2=0.947;Co MSIA:q2=0.836,r2=0.934)。3D-QSAR模型三维等值图揭示了一些结构特性与抑制活性的关系,为该类药物结构改造提供了有效信息,可减少设计合成工作量,提高新药研发成功的可能性。     

G蛋白偶联受体109B苯甲酸类激动剂三维定量构效关系

5-N,N-二取代5-氨基吡唑-3-羧酸、3-硝基-4-氨基苯甲酸和6-氨基烟酸类化合物是G蛋白偶联受体109B(GPR109B)潜在生物活性药物。本实验采用比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(Co MSIA)分别建立46个GPR109B激动剂分子的3D-QSAR模型,确定此类G蛋白偶联受体激动剂的分子结构与生物活性之间的定量关系。Co MFA模型的训练集抽一法交叉验证系数q~2=0.472,非交叉验证系数r~2=0.92,标准偏差SE=0.212;CoMSIA模型的训练集抽一法交叉验证系数q~2=0.498,非交叉验证系数r~2=0.803,标准偏差SE=0.332。两个3D-QSAR模型预测数值与实验数据基本一致,显示模型具有较好的预测能力。本实验根据CoMFA和CoMSIA模型所提供的立体场、静电场、氢键给体场等信息进一步提出改善此类激动剂生物活性的药物设计思路。     

基于奥司他韦衍生物的抗流感病毒H7N9的分子对接

研究奥司他韦类衍生物对新型禽流感病毒H7N9的抑制作用,本人选取32个奥司他韦类的合成化合物为配体,从PDB(Protein Data Bank)数据库中下载了H7N9的受体蛋白,因H7N9具有R292K-N9和R294K-N9两个突变型病毒,所以下载了包括4MWQ(N9-R294)、2QWE(R292K-N9)和4MWW(R294K-N9)三个神经氨酸酶的受体蛋白,将32个配体分子与3个受体蛋白分别进行分子对接,分子对接软件采用SYBYL-2.0中Surflex-Dock软件。结果发现,这32个奥司他韦类衍生物通过与4MWQ、2QWE、4MWW受体蛋白活性位点主要氨基酸残基主要产生氢键结合力、疏水作用和静电作用力而产生抑制作用,为新的神经氨酸酶抑制剂的研发设计提供了有用的结构信息,对流感病毒的新药研发具有积极的意义。     

阿魏酸酰胺类乙酰胆碱酯酶抑制剂的三维定量构效关系研究

采用比较分子场分析(Co MFA)和比较分子相似性分析法(Co MSIA)建立阿魏酸酰胺类乙酰胆碱酯酶抑制剂的三维定量构效关系(3D-QSAR)模型,研究阿魏酸酰胺类乙酰胆碱酯酶抑制剂的构效关系。结果表明,建立的Co MFA-1(Q~2=0.576,r~2=0.992)和Co MSIA(Q~2=0.468,r~2=0.987)模型可靠、合理,揭示了阿魏酸酰胺类化合物与其体外乙酰胆碱酯酶抑制活性间的关系,可为合理设计新的具有更好活性的乙酰胆碱酯酶抑制剂提供科学依据。     

咪唑[2,1-b][1,3,4]噻二唑类ALK5抑制剂3D-QSAR研究

TGF-β信号的转导与纤维化疾病的发生及癌细胞的侵入和转移高度相关,而TGF-β信号通路中的重要节点ALK5是治疗这些疾病的理想靶标。本文针对31个新型咪唑[2,1-b][1,3,4]噻二唑类ALK5抑制剂,分别运用Co MFA和Co MSIA两种经典方法进行了3D-QSAR研究,并获得了预测能力较优的两个模型(Co MFA:q2=0.803,r2=0.969;Co MSIA:q2=0.765,r2=0.938)。3D-QSAR模型三维等值图揭示了一些结构特性与抑制活性的关系,为该类药物结构改造提供了有效信息,可减少设计合成工作量,提高新药研发成功的可能性。     

新型蝶啶酮类PLK1抑制剂的虚拟筛选

Polo样激酶1(PLK1)是治疗多种癌症的一个靶点,蝶啶酮衍生物作为PLK1抑制剂具有显著的生物活性。为了更好理解PLK1抑制剂的药效特征并筛选出具有新骨架的苗头化合物,对新型三/四唑蝶啶酮衍生物进行了系统的分子模拟,主要包括分子对接、药效团模型构建、虚拟筛选和分子动力学模拟。分子对接结果表明,关键氨基酸残基C67、A80、K82、L130、C133、F183可以通过疏水作用、氢键或π-π堆积作用与三/四唑蝶啶酮衍生物相互作用。通过构建的药效团模型,结合分子对接和药代动力学ADME预测,虚拟筛选得到了3个潜在化合物(VS01、VS02和VS03)。分子动力学模拟结果表明,VS02和VS03不仅能与PLK1稳定结合,而且结合自由能优于已报道活性最高的化合物27。为新型PLK1抑制剂的筛选和开发提供了有效信息和理论参考。     

阿那白滞素与白细胞介素-1β的分子作用机制

阿那白滞素(Anakinra)是一类重要的白细胞介素-1β的抑制剂,对于治疗多种疾病引起的并发症具有重要作用。采用分子对接和分子动力学方法研究了Anakinra抑制白细胞介素-1β的分子作用机制。结果表明,Anakinra可由氢键作用结合于白细胞介素-1β的表面,它的结合使白细胞介素-1β的结构趋于稳定,从而抑制其生物活性。Anakinra的结合没有明显改变白细胞介素-1β的亲水性和疏水性,白细胞介素-1β内部氢键数目的改变是稳定性发生改变的主要原因。     

芦丁与弹性蛋白酶相互作用的研究

天然产物芦丁(Rutin)可以抑制弹性蛋白酶的活性,采用多光谱法与分子对接技术研究芦丁与弹性蛋白酶(PPE)的相互作用。研究结果表明,Rutin对PPE存在荧光猝灭效应,且为静态猝灭。Rutin与PPE能形成1∶1复合物,在298 K下其结合常数为4.90×10⁴ L/mol,主要结合力为氢键和范德华力。根据Forster′s非辐射能量转移理论,计算得到Rutin与PPE的结合距离r为4.55 nm。紫外光谱与同步荧光光谱结果表明,Rutin可使PPE周围微环境发生改变,极性增加、亲水性增加和疏水性减弱。傅里叶变换红外光谱与圆二色光谱分析表明,Rutin使PPE的α-螺旋、β-折叠含量降低,酶结构变得松散,改变了PPE的二级结构。分子对接模拟表明,Rutin与PPE距离在0.4 nm之内的氨基酸残基共有11个,共形成5条氢键,同时还有强大的范德华力与π-阳离子相互作用,多种作用力使Rutin与PPE形成稳定的复合物,抑制了弹性蛋白酶的活性。     

Probing Structural Features and Binding Mode of 3-Arylpyrimidin-2,4-diones within Housefly γ-Aminobutyric Acid (GABA) Receptor

In order to obtain structural features of 3-arylpyrimidin-2,4-diones emerged as promising inhibitors of insect γ-aminobutyric acid (GABA) receptor, a set of ligand-/receptor-based 3D-QSAR models for 60 derivatives are generated using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The statistically optimal CoMSIA model is produced with highest q(2) of 0.62, r(2) (ncv) of 0.97, and r(2) (pred) of 0.95. A minor/bulky electronegative hydrophilic polar substituent at the 1-/6-postion of the uracil ring, and bulky substituents at the 3'-, 4'- and 5'-positions of the benzene ring are beneficial for the enhanced potency of the inhibitors as revealed by the obtained 3D-contour maps. Furthermore, homology modeling, molecular dynamics (MD) simulation and molecular docking are also carried out to gain a better understanding of the probable binding modes of these inhibitors, and the results show that residues Ala-183(C), Thr-187(B), Thr-187(D) and Thr-187(E) in the second transmembrane domains of GABA receptor are responsible for the H-bonding interactions with the inhibitor. The good correlation between docking observations and 3D-QSAR analyses further proves the model reasonability in probing the structural features and the binding mode of 3-arylpyrimidin-2,4-dione derivatives within the housefly GABA receptor.     

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q² = 0.621, r²_pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.     

Docking-Based 3D-QSAR Studies for 1,3,4-oxadiazol-2-one Derivatives as FAAH Inhibitors

This work aimed to construct 3D-QSAR CoMFA and CoMSIA models for a series of 31 FAAH inhibitors, containing the 1,3,4-oxadiazol-2-one moiety. The obtained models were characterized by good statistical parameters: CoMFA Q² = 0.61, R² = 0.98; CoMSIA Q² = 0.64, R² = 0.93. The CoMFA model field contributions were 54.1% and 45.9% for steric and electrostatic fields, respectively. In the CoMSIA model, electrostatic, steric, hydrogen bond donor, and hydrogen acceptor properties were equal to 34.6%, 23.9%, 23.4%, and 18.0%, respectively. These models were validated by applying the leave-one-out technique, the seven-element test set (CoMFA r²_test-set = 0.91; CoMSIA r²_test-set = 0.91), a progressive scrambling test, and external validation criteria developed by Golbraikh and Tropsha (CoMFA r²₀ = 0.98, k = 0.95; CoMSIA r²₀ = 0.98, k = 0.89). As the statistical significance of the obtained model was confirmed, the results of the CoMFA and CoMSIA field calculation were mapped onto the enzyme binding site. It gave us the opportunity to discuss the structure–activity relationship based on the ligand–enzyme interactions. In particular, examination of the electrostatic properties of the established CoMFA model revealed fields that correspond to the regions where electropositive substituents are not desired, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one moiety. This highlights the importance of heterocycle, a highly electronegative moiety in this area of each ligand. Examination of hydrogen bond donor and acceptor properties contour maps revealed several spots where the implementation of another hydrogen-bond-donating moiety will positively impact molecules’ binding affinity, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one ring. On the other hand, there is a large isopleth that refers to the favorable H-bond properties close to the terminal phenoxy group of a ligand, which means that, generally speaking, H-bond acceptors are desired in this area.     

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q² (cross-validated correlation coefficient) = 0.557, R²_ncv (non-cross-validated correlation coefficient) = 0.740, R²_pre (predicted correlation coefficient) = 0.749 and Q² = 0.598, R²_ncv = 0.767, R²_pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.     

3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.     

Combined 3D-QSAR Modeling and Molecular Docking Studies on Pyrrole-Indolin-2-ones as Aurora A Kinase Inhibitors

Aurora kinases have emerged as attractive targets for the design of anticancer drugs. 3D-QSAR (comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)) and Surflex-docking studies were performed on a series of pyrrole-indoline-2-ones as Aurora A inhibitors. The CoMFA and CoMSIA models using 25 inhibitors in the training set gave r(2) (cv) values of 0.726 and 0.566, and r(2) values of 0.972 and 0.984, respectively. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to rationalize the key structural requirements responsible for the activity. Surflex-docking studies revealed that the sulfo group, secondary amine group on indolin-2-one, and carbonyl of 6,7-dihydro-1H-indol-4(5H)-one groups were significant for binding to the receptor, and some essential features were also identified. Based on the 3D-QSAR and docking results, a set of new molecules with high predicted activities were designed.     

Combined 3D-QSAR, Molecular Docking and Molecular Dynamics Study on Derivatives of Peptide Epoxyketone and Tyropeptin-Boronic Acid as Inhibitors Against the β5 Subunit of Human 20S Proteasome

An abnormal ubiquitin-proteasome is found in many human diseases, especially in cancer, and has received extensive attention as a promising therapeutic target in recent years. In this work, several in silico models have been built with two classes of proteasome inhibitors (PIs) by using 3D-QSAR, homology modeling, molecular docking and molecular dynamics (MD) simulations. The study resulted in two types of satisfactory 3D-QSAR models, i.e., the CoMFA model (Q(2) = 0.462, R(2) (pred) = 0.820) for epoxyketone inhibitors (EPK) and the CoMSIA model (Q(2) = 0.622, R(2) (pred) = 0.821) for tyropeptin-boronic acid derivatives (TBA). From the contour maps, some key structural factors responsible for the activity of these two series of PIs are revealed. For EPK inhibitors, the N-cap part should have higher electropositivity; a large substituent such as a benzene ring is favored at the C6-position. In terms of TBA inhibitors, hydrophobic substituents with a larger size anisole group are preferential at the C8-position; higher electropositive substituents like a naphthalene group at the C3-position can enhance the activity of the drug by providing hydrogen bond interaction with the protein target. Molecular docking disclosed that residues Thr60, Thr80, Gly106 and Ser189 play a pivotal role in maintaining the drug-target interactions, which are consistent with the contour maps. MD simulations further indicated that the binding modes of each conformation derived from docking is stable and in accord with the corresponding structure extracted from MD simulation overall. These results can offer useful theoretical references for designing more potent PIs.     

Combined 3D-QSAR and Docking Modelling Study on Indolocarbazole Series Compounds as Tie-2 Inhibitors

Tie-2, a kind of endothelial cell tyrosine kinase receptor, is required for embryonic blood vessel development and tumor angiogenesis. Several compounds that showed potent activity toward this attractive anticancer drug target in the assay have been reported. In order to investigate the structure-activity correlation of indolocarbazole series compounds and modify them to improve their selectivity and activity, 3D-QSAR models were built using CoMFA and CoMSIA methods and molecular docking was used to check the results. Based on the common sketch align, two good QSAR models with high predictabilities (CoMFA model: q(2) = 0.823, r(2) = 0.979; CoMSIA model: q(2) = 0.804, r(2) = 0.967) were obtained and the contour maps obtained from both models were applied to identify the influence on the biological activity. Molecular docking was then used to confirm the results. Combined with the molecular docking results, the detail binding mode between the ligands and Tie-2 was elucidated, which enabled us to interpret the structure-activity relationship. These satisf actory results not only offered help to comprehend the action mechanism of indolocarbazole series compounds, but also provide new information for the design of new potent inhibitors.     

Structural Determinants of CX-4945 Derivatives as Protein Kinase CK2 Inhibitors: A Computational Study

Protein kinase CK2, also known as casein kinase-2, is involved in a broad range of physiological events including cell growth, proliferation and suppression of apoptosis which are related to human cancers. A series of compounds were identified as CK2 inhibitors and their inhibitory activities varied depending on their structures. In order to explore the structure-activity correlation of CX-4945 derivatives as inhibitors of CK2, in the present study, a set of ligand- and receptor-based 3D-QSAR models were developed employing Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The optimum CoMFA (R(cv) (2) = 0.618, R(pred) (2) = 0.892) and CoMSIA (R(cv) (2) = 0.681, R(pred) (2) = 0.843) models exhibited reasonable statistical characteristics for CX-4945 derivatives. The results indicated that electrostatic effects contributed the most to both CoMFA and CoMSIA models. The combination of docking analysis and molecular dynamics (MD) simulation showed that Leu45, Lys68, Glu81, Val116, Asp175 and Trp176 of CK2 which formed several direct or water-bridged H-bonds with CX-4945 are crucial for CX-4945 derivatives recognition to CK2. These results can offer useful theoretical references for designing more potent CK2 inhibitors.     

Structural Determination of Three Different Series of Compounds as Hsp90 Inhibitors Using 3D-QSAR Modeling, Molecular Docking and Molecular Dynamics Methods

Hsp90 is involved in correcting, folding, maturation and activation of a diverse array of client proteins; it has also been implicated in the treatment of cancer in recent years. In this work, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), molecular docking and molecular dynamics were performed on three different series of Hsp90 inhibitors to build 3D-QSAR models, which were based on the ligand-based or receptor-based methods. The optimum 3D-QSAR models exhibited reasonable statistical characteristics with averaging internal q(2) > 0.60 and external r(2) (pred) > 0.66 for Benzamide tetrahydro-4H-carbazol-4-one analogs (BT), AT13387 derivatives (AT) and Dihydroxylphenyl amides (DA). The results revealed that steric effects contributed the most to the BT model, whereas H-bonding was more important to AT, and electrostatic, hydrophobic, H-bond donor almost contributed equally to the DA model. The docking analysis showed that Asp93, Tyr139 and Thr184 in Hsp90 are important for the three series of inhibitors. Molecular dynamics simulation (MD) further indicated that the conformation derived from docking is basically consistent with the average structure extracted from MD simulation. These results not only lead to a better understanding of interactions between these inhibitors and Hsp90 receptor but also provide useful information for the design of new inhibitors with a specific activity.