虚拟活性化合物的自动生成

虚拟活性化合物的自动生成是从药效团和预先设定的结构碎片出发,通过碎片选择、碎片组装和柔性构象搜索来获得虚拟活性结构。经过对HIV-1蛋白酶抑制剂药效团进行虚拟活性化合物生成,得到了16个虚拟活性化合物,通过构象分析发现生成的化合物满足药效团的限制条件。说明这一方法能够有效的生成虚拟活性结构,与药效团检索结果对比发现生成的虚拟活性结构新颖易于合成。     

基于药效团模型的DHODH抑制剂构效关系研究

利用药效团模型研究二氢乳清酸脱氢酶(Dihydroorotate dehydrogenase,DHODH)抑制剂的构效关系,为DHODH抑制剂的虚拟筛选提供新的方法.以31个具有DHODH抑制活性的化合物为训练集化合物,半数抑制浓度(IC50)范围为7~63000 nmol/L,利用Catalyst/HypoGen算法构建DHODH抑制剂药效团模型,通过对训练集化合物多个构象进行叠合,提取药效团特征及三维空间限制构建药效团模型.利用基于CatScramble的交叉验证方法及评价模型对已知活性化合物的活性预测能力,确定较优药效团模型.模型包含1个氢键受体、3个疏水中心,表征了受体配体相互作用时可能发生的氢键相互作用、疏水相互作用和π-π相互作用,4个药效特征在三维空间的排列概括了DHODH抑制剂产生活性的结构特点.所得较优模型对训练集化合物及测试集化合物的计算活性值与实验活性值的相关系数分别为0.8405和0.8788.利用药效团模型对来源于微生物的系列化合物进行虚拟筛选,筛选出59个预测活性较好的化合物,可作为进一步药物研发的候选化合物.     

人类免疫缺陷病毒整合酶二酮酸类抑制剂的三维药效团构建

应用遗传算法相似性程序(GASP), 以作用于I型人类免疫缺陷病毒(human immun-odeficiency virus type 1, HIV-1)整合酶(IN)的二酮酸类(diketoacids, DKAs)抑制剂构建药效团模型. 所选训练集分子均具有可靠的类药性特征及DKAs药效团特征. 尝试将抑制剂与药效团叠合后的构象和抑制剂与IN的对接构象进行叠合, 得到药效团模型与分子对接构象中IN残基的相对位置, 并基于抑制剂的药效团模型特征与周围IN氨基酸残基位置的匹配情况进行药效团特征的修改. 所得最优药效团由1个疏水特征、3对氢键特征和1个氢键供体特征组成. 该药效团的命中物质量(goodness of hit, GH)为0.56, 产出率(Y)达63.6%, 假阳性率(FP)为0.41%. 该药效团具有较好的置信度, 产出率较高而假阳性率较低, 可用于数据库搜索发现新的具有DKAs药效团特征的活性化合物, 也可为先导化合物的改造提供帮助.     

基于“底物包膜”假说筛选新型HIV-1蛋白酶抑制剂

基于“底物包膜”假说, 以现有HIV-1蛋白酶抑制剂Darunavir为模板构建药效团模型并对中药化学数据库进行搜索; 采用分子对接方法进一步考察化合物与HIV-1蛋白酶结合情况及其与“底物包膜”符合程度, 优先选出两个化合物Annomonicin和去乙酰蟾蜍它灵; 应用分子动力学方法对这两个化合物进行动力学模拟, 观察它们与蛋白酶结合的复合物在动力学过程中的稳定性并计算其结合自由能, 综合评价筛选结果, 最终确定化合物Annomonicin具有更潜在的深入研究价值.     

新型酪氨酸激酶小分子抑制的三维药效团研究

通过CATALYST软件包得到了两类HER2抑制的三维药效团模型。尽管亚苄基丙二腈化合物和3-取代吲哚啉-2-酮系列化合物具有完全不同的骨架结构,但得到的药效团却具有共同的特性,这表明当这两类抑制剂和受体发生相互作用时,采用了相似的结合模式。共同的药效团模型包括一个氢键受体,一个氢键给体,一个脂肪类疏水团以及一个芳香类疏水团。根据药效团模型,我们还进行了三维构效关系的研究,结果表明得到的药效团模型具有很好的预测能力(线性回归系数R≈0.96)。药效团模型对于研究酪氨酸激酶小分子抑制剂的结构与活性关系,以及评估和预测此类未知化合物活性具人重要的意义。     

新型酪氨酸激酶小分子抑制的三维药效团研究

通过CATALYST软件包得到了两类HER2抑制的三维药效团模型。尽管亚苄基丙二腈化合物和3-取代吲哚啉-2-酮系列化合物具有完全不同的骨架结构,但得到的药效团却具有共同的特性,这表明当这两类抑制剂和受体发生相互作用时,采用了相似的结合模式。共同的药效团模型包括一个氢键受体,一个氢键给体,一个脂肪类疏水团以及一个芳香类疏水团。根据药效团模型,我们还进行了三维构效关系的研究,结果表明得到的药效团模型具有很好的预测能力(线性回归系数R≈0.96)。药效团模型对于研究酪氨酸激酶小分子抑制剂的结构与活性关系,以及评估和预测此类未知化合物活性具人重要的意义。     

基于吡咯烷与正丁烷类衍生物CCR5拮抗剂的药效团模型构建

吡咯烷与正丁烷类CCR5(化学趋化因子受体5)拮抗剂可通过抑制人类免疫缺陷病毒(HIV-1)包膜蛋白与CCR5的相互作用而阻断病毒进入细胞. 本文使用已知拮抗剂结构和活性信息构建了一个三维药效团模型. 按照Catalyst/HypoGen模块的要求, 选择了25个结构和活性均具备差异性的分子作为药效团产生的训练集. 其中训练集分子以IC50值表示的生物活性值跨度为0.06到10000 nmol·L-1. 最好的药效团模型(Hypo 1)由两个正离子化特征以及三个疏水特征组成, 训练集预测相关系数为0.924, 均方根偏差为1.068. 模型用于预测由74个分子组成的测试集化合物活性, 结果表明模型可以提供较好的活性预测结果并用于新的拮抗剂的设计.     

计算机方法确定Darunavir衍生物作为HIV-1蛋白酶抑制剂的结构决定因素与结合机制

HIV-1是地球上最可怕以及最致命的病毒之一,它是导致艾滋病的主要原因．HIV-1蛋白酶在HIV-1病毒的复制过程中承担重要角色,因此通过抑制HIV-1蛋白酶的活性从而将其作为治疗方案被认为是一种十分有效的策略．为此探究HIV-1蛋白酶抑制剂的结构决定因素而进行设计与改进成为急需解决的问题．本文建立了一个包含193个Darunavir衍生物抑制剂的数据库,在此基础上,通过使用基于配体的三维定量结构-活性关系(3D-QSAR)研究,确定了一系列关键的结构特征．此外,我们还利用分子对接进一步阐明了配体与受体之间的复杂相互作用．结果显示最优的CoMSIA模型在有效性和可预测性方面都表现出了适当的性能(Q²=0.500,R_ncv²=0.882,R_pred²=0.797)．另外,数据集中活性最高的化合物171与Asp25,Gly27,Gly48,Asp124,Asp128和Asp129形成了若干个氢键,以交叉构象稳定结合在活性空腔中．根据从最佳CoMSIA模型和分子对接中获得的信息,我们...     

基于药效团的血管紧张素转换酶抑制肽的结构优化

采用Discovery Studio2．0中的药效团模型生成方法,产生了基于化学特征的ACE抑制肽的药效团模型．所选择的认为最好的药效团模型（Hypo1）含有5个化学特征（1个阴离子中心、1个氢键受体、1个氢键给体、2个疏水中心）．我们先前采用实验的方法,从蚕蛹蛋白中获得具有ACE抑制活性的六肽分子,本文结合产生的ACE抑制肽药效团模型和分子对接研究,对该六肽分子进行结构优化,以识别六肽中对ACE抑制活性起关键作用的结构部分．结果显示,药效团模型的方法可有效用于ACE抑制肽的结构优化．     

p53-MDM2结合抑制剂药效团模型的构建

采用Catalyst软件, 选择5类共24个p53-MDM2结合抑制剂作为训练集, 经计算机建模、构象优化, 由Catalyst系统构建出药效团模型, 并对药效团进行有效性分析, 结合已知的p53-MDM2结合抑制剂的结构信息, 筛选得到含有一个芳环中心、三个疏水中心和一个氢键受体的具有较好预测能力(Correl=0.941, Config=17.530, 吟cost=150.830)的药效团模型.     

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1′ pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC₅₀ value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.     

6-氮杂吲唑类Pim-1激酶抑制剂的3D-QSAR、药效团模型研究和分子设计

Pim-1 激酶通过作用于多种信号通路或靶点影响肿瘤的发生发展,近年来被认为是肿瘤治疗的良好靶标。本文采用SYBYL-X2. 1. 1软件中的TopomerCoMFA、GALAHAD模块建立计算机模型,研究39个基于6-氮杂吲唑环的Pim-1激酶抑制剂的三维定量构效关系及药效团特征元素。结果显示,TopomerCoMFA建模所得交叉验证系数（q2）和相关系数（r2）分别为0. 756和0. 951,结合外部验证表明此3D-QSAR模型具有较高预测能力及较好的统计学稳定性,同时,用等势图描述了R1、R2基团处立体场、静电场对活性的具体影响。药效团研究结果表明,含氢键受体的芳香杂环母核结构,以及侧链取代基中含有芳香杂环结构对化合物的活性贡献较大。最后根据上述模型信息新设计了15个Pim-1激酶抑制剂分子并完成活性预测及分子对接模式研究,其中4个分子的预测pIC50高于建模分子中活性最好的化合物17,Surflex-Dock分析显示新设计分子均与Pim-1激酶形成较强氢键相互作用。基于6-氮杂吲唑环的Pim-1激酶抑制剂的3D-QSAR模型以及药效团模型可用于指导新型抑制剂的结构优化,为设计和开发具有较高活性的新型Pim-1激酶抑制剂提供有效帮助。     

β分泌酶抑制剂的药效团模型研究

选择活性跨越0.002至25 μmol•L－1的4类共25个β分泌酶抑制剂作为训练集, 使用Catalyst软件包构建出药效团模型, 并通过对药效团的有效性分析, 筛选得到的最佳模型(correlCorrel＝0.969, Config＝16.32, Δcost＝62.422)由一个环芳香性、一个疏水中心、一个正电荷中心和一个氢键供体组成. 并用其它209个抑制剂组成测试集对模型进行验证, 结果表明该模型显示出较强的预测能力, 能够为进一步的数据库搜索, 寻找新型的β分泌酶抑制剂先导物提供依据.     

A 3D QSAR pharmacophore model and quantum chemical structure--activity analysis of chloroquine(CQ)-resistance reversal

Using CATALYST, a three-dimensional QSAR pharmacophore model for chloroquine(CQ)-resistance reversal was developed from a training set of 17 compounds. These included imipramine (1), desipramine (2), and 15 of their analogues (3-17), some of which fully reversed CQ-resistance, while others were without effect. The generated pharmacophore model indicates that two aromatic hydrophobic interaction sites on the tricyclic ring and a hydrogen bond acceptor (lipid) site at the side chain, preferably on a nitrogen atom, are necessary for potent activity. Stereoelectronic properties calculated by using AM1 semiempirical calculations were consistent with the model, particularly the electrostatic potential profiles characterized by a localized negative potential region by the side chain nitrogen atom and a large region covering the aromatic ring. The calculated data further revealed that aminoalkyl substitution at the N5-position of the heterocycle and a secondary or tertiary aliphatic aminoalkyl nitrogen atom with a two or three carbon bridge to the heteroaromatic nitrogen (N5) are required for potent "resistance reversal activity". Lowest energy conformers for 1-17 were determined and optimized to afford stereoelectronic properties such as molecular orbital energies, electrostatic potentials, atomic charges, proton affinities, octanol-water partition coefficients (log P), and structural parameters. For 1-17, fairly good correlation exists between resistance reversal activity and intrinsic basicity of the nitrogen atom at the tricyclic ring system, frontier orbital energies, and lipophilicity. Significantly, nine out of 11 of a group of structurally diverse CQ-resistance reversal agents mapped very well on the 3D QSAR pharmacophore model.     

Design and synthesis of simple macrocycles active against vancomycin-resistant enterococci (VRE)

16-membered meta,para-cyclophanes mimicking the vancomycin binding pocket (D-O-E ring) were designed and synthesized. The structural key features of these biaryl ether containing macrocycles are (1) the presence of beta-amino-alpha-hydroxy acid or alpha,beta-diamino acid as the C-terminal component of the cyclopeptide and (2) the presence of a hydrophobic chain or lipidated aminoglucose at the appropriate position. Cycloetherification by an intramolecular nucleophilic aromatic substitution reaction (S(N)Ar) is used as the key step for the construction of the macrocycle. The atropselectivity of this ring-closure reaction is found to be sensitive to the peptide backbone and chemoselective cyclization (phenol versus primary amine) is achievable. Glycosylation of phenol was realized with freshly prepared 3,4,6-tri-O-acetyl-2-N-lauroyl-2-amino-2-deoxy-alpha-D-glucopyranosyl bromide under phase-transfer conditions. Minimum inhibitory concentrations for all of the derivatives are measured by using a standard microdilution assay, and potent bioactivities against both sensitive and resistant strains are found for some of these compounds (MIC (minimum inhibitory concentration) = 4 microg mL(-1) against VRE). From these preliminary SAR studies, it was anticipated that both the presence of a hydrophobic substituent and an appropriate structure of the macrocycle were required for this series of compounds to be active against VRE.     

Comparative pharmacophore modeling of human adenosine receptor A1 and A3 antagonists

Adenosine receptors are promising therapeutic targets in drug discovery. In this study, three-dimensional pharmacophore models of human adenosine receptor A1 and A3 antagonists were developed based on 26 and 23 diverse compounds, respectively. The best A1 pharmacophore model (A 1 _Hopy1) consists of four features: one hydrogen bond donor, one hydrophobic point and two ring aromatics, while the best A 3 pharmacophore model (A3 _Hopy1) also has four features: one hydrogen bond acceptor, one hydrophobic point and two ring aromatics. The correlation coefficients were 0.840 for A 1 test set with 146 diverse compounds and 0.827 for A3 test set with 238 diverse compounds. In the simulated virtual screening experiments, high enrichment factors of 6.51 and 6.90 were obtained for A 1 _Hopy1 and A3 _Hopy1 models, respectively. Moreover, two models also showed high subtype-selectivity in the simulated virtual screening experiments. These results could be helpful for the discovery of novel potent and selective A 1 and A3 antagonists.     

2D-QSAR Studies on Triazolone Compounds Containing Benzenesulfonic Amide

The geometry structures of 6 triazolone compounds containing benzenesulfonic amide were fully optimized with DFT (Density Functional Theory) method at the B3LYP/6-31G level, and the structural and electronic parameters of the compounds were calculated. The hydrophobic and topological parameters of the title compounds were calculated by HyperChem software. The mono-and bi-parametric models between the parameters and biological activity of the compounds were analyzed by Multiple Linear Regression method based on Hansch-Fujita model. The results show that the activities of the title compounds were increased with higher hydrophobic property logP and molecular volume V, lower molecular energy ETOTAL and elec-tronegative of benzene ring Qph.     

氧肟酸类组蛋白去乙酰化酶抑制剂的药效团模型研究

基于24个目前已知的氧肟酸类组蛋白去乙酰化酶抑制剂,我们运用Catalyst软件建立了一个三维药效团模型。其中,最好的药效团模型1,包含了四个化学特征（一个氢键供体,一个芳环和两个疏水基）,相关系数达到0.946,并由另外20个化合物进行了测试验证。我们第一次特征性描述了组蛋白去乙酰化酶的帽子（CAP）部分。我们的研究结果对于设计全新组蛋白去乙酰化酶抑制剂具有很好的指导作用。