毒蕈碱型M1受体的同源模建和分子对接

采用同源模建方法对M1受体的三维结构进行了模拟,将得到的模型分别与M受体完全激动剂乙酰胆碱和M1受体选择性激动剂占诺美林进行分子对接,形成非特异性激动和特异性激动的受体-配体复合物.用分子动力学模拟方法分别将未与小分子对接的M1受体、M1受体-乙酰且H碱复合物、M1受体-占诺美林复合物置于磷脂双膜中模拟10 ns.将模拟后的蛋白质结构与包含活性分子的测试库对接并将结果打分,以top5%富集因子(EF)作为评价依据,用占诺美林优化后的M1受体模型的EF为8.0,用乙酰胆碱优化后M1受体模型的EF为6.5,非复合物的EF为1.5.说明M1受体选择性激动剂复合物进行分子动力学模拟后得到的三维结构模型比较合理,可以作为化合物虚拟筛选的模型对新化合物进行虚拟筛选,为找到新的选择性M1受体激动剂奠定了基础.     

α1A-肾上腺素受体的同源模建及其对接研究

以β2肾上腺素受体(β2-AR)为模板,采用同源模建和分子动力学模拟构建了人类α1A-肾上腺素受体(α1A-AR)的三维结构模型,并利用PROCHECK,PROSA和WHAT-IF评估了模型的合理性.所得的结构采用分子对接程序Flexidock与激动剂去甲肾上腺素和拮抗剂西罗多辛分别进行对接,结果表明,2种配基具有相似...     

同源模建和分子对接研究HDAC1/HDAC8的选择性

组蛋白去乙酰化酶(HDACs)是近年来治疗肿瘤的重要靶标之一.由于HDACs包含多种亚型,且各亚型的生理功能存在一定的差异,其选择性抑制剂的开发已成为当前的研发热点.我们通过同源模建的HDAC1结构,与已有的HDAC8晶体结构的活性位点进行比较分析,探讨了对两者选择性有重要影响的残基,为基于受体的选择性抑制剂研究提供重要信息.同时选择了52个HDAC抑制剂,分别建立了HDAC1、HDAC8的活性值与对接打分值的线性回归模型.所建的HDAC1和HDAC8的线性构效关系模型的非交叉验证系数R2分别为0.82和0.80,表明具有一定的统计学意义.利用所建模型对已设计合成的化合物进行了预测,预测结果对HDAC1、HDAC8选择性抑制剂的优化改造提供了一定的指导意义.     

大麻素受体CB1三维结构的同源模建及其对接研究

大麻素CB1受体属于G蛋白偶联受体. 以牛视紫红质的晶体结构为模板, 利用同源模建法对CB1受体的三维结构进行了模拟, 并采用分子动力学方法对模型进行了修正和优化. 在此基础上, 分析了活性位点的组成和结构, 研究了拮抗剂利莫那班与CB1受体的对接, 明确了CB1受体与利莫那班结合时起重要作用的氨基酸残基. 发现利莫那班与CB1受体残基Lys192形成氢键相互作用是CB1受体拮抗剂的重要分子作用基础.     

鲍曼不动杆菌LpxC的同源模建及分子对接

鲍曼不动杆菌已成为最普遍的医院致病菌,且耐药情况严峻.LpxC作为新抗菌药物靶点被大量研究,但鲍曼不动杆菌LpxC晶体尚未解析得到,基于其结构的药物设计等工作无法开展.以铜绿假单胞菌LpxC晶体结构为模板,通过同源模建方法获得鲍曼不动杆菌LpxC结构模型.较好的Ramachandran plot分布和Profile-3D结果验证了模型的合理性.用分子动力学模拟优化鲍曼不动杆菌LpxC模型,修补部分不合理构象.后续分子对接结果显示S构型的苄氧乙酰基羟肟酸类抑制剂比R构型分子能更有效地结合在F191,H237和K238组成的较浅口袋中,这可能是S构型抑制剂活性更高的主要因素,模拟结果与实验数据吻合较好.     

趋化因子CCR2的同源模建,分子对接和3D-QSAR研究

趋化因子CCR2参与炎症反应、免疫移植排斥和肿瘤的发生,已成为新的研究热点。本文以CCR5的晶体结构为模板,同源模建CCR2的结构,并用CCR2小分子抑制剂与其进行分子对接以得到小分子的最优构象。在对接叠合的基础上建立了QSAR模型,采用比较分子场分析(Co MFA)以及比较分子相似性分析(Co MSIA)研究得到Co MFA和Co MSIA模型最佳评价参数分别为q2=0.743,r2=0.968和q2=0.68,r2=0.978。3D-QSAR模型的等势图分析表明,改造配体R3基团可提高化合物活性。所建模型稳定性好、预测性强,对基于CCR2的小分子抑制剂的设计、优化和改造提供了参考。     

人类丝氨酸消旋酶的同源模建及其与多肽类抑制剂的分子对接

利用同源模建和分子动力学模拟方法构建了人类丝氨酸消旋酶(hSR)的三维结构, 并利用profile-3D和procheck方法评估了模型的可靠性. 在此基础上用分子对接程序(affinity)将多肽类抑制剂A和B分别与hSR进行对接, 获得了其复合物结构的理论模型. 通过配体与受体之间相互作用能和结构分析给出了此类抑制剂与hSR的具体结合方式, 明确了hSR与此类抑制剂结合时起重要作用的氨基酸残基, 为基于人类丝氨酸消旋酶三维结构的药物设计提供重要的参考信息.     

Furcatin 水解酶的三维结构模建和与furcatin 的对接研究

利用同源模建和动力学模拟方法，模建了furcatin水解酶（FH）的三维结构．并在这基础上，分析了活性位点的组成和结构．研究了furcatin与FH的对接．结果表明，Ser84，Arg146，Thr189，Thr234和Gly372在复合物的形成过程中起重要的作用．其中，Ser84，Argl46和Thr189是在FH的活性口袋的二糖部分的亚单位一1中重要的氨基酸，Thr234和Gly372是亚单位-2中重要的氨基酸．     

A_1腺苷受体的同源模建及其结构验证

采用同源模建的方法构建了A1腺苷受体的三维结构,并与拮抗剂分子DPCPX对接,将得到的复合物结构进行5 ns的分子动力学模拟,以最后2 ns的平均结构和平衡后抽取的11帧构象共12个蛋白结构为研究对象,用包含52个活性分子和1000个诱饵分子的测试库,分别通过DOCK、VINA和GOLD三种对接软件进行评价,最终得出合理的蛋白质模型.根据top10%的富集因子(EF)和ROC曲线下面积(AU-ROC)的计算结果,我们认为GOLD是最适合A1腺苷受体的对接软件,而12个蛋白质结构中F5和Favg的三维结构模型比较合理,可以作为进一步大规模虚拟筛选的模型.     

CCK1受体的同源模拟和分子对接研究

采用同源建模法对CCK1受体的三维结构进行了模拟,并采用分子动力学方法对模型进行修正和优化,再采用与训练集激动剂和拮抗剂分子对接的方法分别得到激动状态和拮抗状态CCK1受体的三维结构模型。得到的模型使用DOCK对接软件对训练集中的分子进行对接,所得结果与其实际活性拟合度较好,说明我们建立的激动和拮抗状态下的CCK1受体的三维结构模型比较合理,可以作为化合物虚拟筛选的模型对新化合物进行虚拟筛选。     

Using Homology Modeling, Molecular Dynamics and Molecular Docking Techniques to Identify Inhibitor Binding Regions of Somatostatin Receptor 1

The G protein coupled receptor(GPCR), one of the members in the superfamily, which consists of thousands of integral membrane proteins, exerts a wide variety of physiological functions and responses to a large portion of the drug targets. The 3D structure of somatostatin receptor 1(SSTR1) was modeled and refined by means of homology modeling and molecular dynamics simulation. This model was assessed by Verify-3D and Vadar, which confirmed the reliability of the refined model. The interaction between the inhibitor cysteamine, somatostatin(SST) and SSTR1 was investigated by a molecular docking program, Affinity. The binding module not only showed the crucial residues involved in the interaction, but also provided important information about the interaction between SSTR1 on the one hand and ligands on the other, which might be the significant evidence for the structure-based design.     

细胞色素p450 2s1(CYP2s1)三维结构模建及其与维甲酸分子的对接研究

利用同源模建和分子动力学模拟,模建了细胞色素P450(CYP2s1)的三维结构．在模建结构的基础上,分析了活性位点的组成和结构,并进行了与小分子(维甲酸)的分子对接研究．研究结果表明,在由维甲酸和CYP2s1形成的复合物中,非键相互作用较强,其中,GLu411和Ala414是与维甲酸相互作用能最强的两个残基,对复合物的结合起重要作用．     

对羟基杏仁酸合成酶三维结构模建及其与底物的分子对接研究

以对羟基苯丙酮酸双氧化酶(HPPD)的晶体结构为模板, 利用同源模建方法构建了与其高度同源、底物相同但催化功能存在明显差别的对羟基杏仁酸合成酶(HMS)的三维结构, 并对模建结构的合理性进行了分析. 在模建结果的基础上, 对HPPD和HMS分别与底物羟苯基丙酮酸(HPP)进行分子对接计算, 比较了二者结合模式的异同, 为两种同源酶在催化方面差异性的合理阐释提供了一些有益的信息.     

人类腺苷受体A3亚型拮抗剂的构效关系分析

构建人类腺苷受体A3亚型药效团模型和三维蛋白结构模型用于作用模式研究.以18个来源于文献具有腺苷受体A3亚型拮抗活性的化合物作为训练集,使用HypoGen方法构建药效团模型.通过同源模建和分子动力学模拟构建了人类腺苷受体A3亚型的三维蛋白模型,并利用PROCHECK方法评估该模型的合理性,对所得的结构使用分子对接程序进行作用模式分析,药效团模型和同源模建结果相互匹配较好.使用新药效团模型对MDL药物数据库(MDDR)中包含的约120000个化合物进行虚拟筛选,得到了8个候选化合物,用于进一步的生物学评价和活性测定.本工作对于人类腺苷受体A3亚型拮抗剂的设计和抗哮喘药物的研发具有一定的理论指导和应用价值.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

Aflatoxin B1 and M1 in milk

The aflatoxin M₁ (AFLAM₁) is a mycotoxin that results from the hydroxylation of the aflatoxin B₁ (AFLAB₁). It contaminates the milk of animals fed with a diet containing its precursor. In this work, we determined the occurrence of AFLAB₁ and AFLAM₁ in milk, as well as the chromatographic conditions to quantify these mycotoxins. The extraction and quantification of AFLAB₁ and AFLAM₁ in naturally contaminated and artificially spiked milk samples which are produced and marketed in the state of RS were performed using the AOAC official method and UHPLC with fluorescence detection. We obtained a separation factor of 2.3 for AFLAB₁ and AFLAM₁ using a mobile phase consisting of 1% acetic acid:acetonitrile:methanol (55:10:35). The analytical curves had a wide linearity range and the limit of quantification (LOQ_m) concentrations of AFLAB₁ and AFLAM₁ were equal to 0.5 and 0.25 μg L⁻¹, respectively. Samples of pasteurized and ultra-high-temperature processed (UHT) milk showed natural contamination, and the levels for both aflatoxins ranged from 0.7 to 1.5 μg L⁻¹. Raw and concentrated milk samples only contained AFLAM₁, with a maximum average concentration of 1.7 μg L⁻¹. These concentrations, higher than permitted by legislation, confirm the existence of a health risk, as well as highlight the relevance of searching for alternatives to reduce this contamination.