靶向雄激素受体与糖皮质激素受体的抗前列腺癌药物筛选模型的建立和应用

目的寻找可以克服由于糖皮质激素(GR)高表达造成的现有抗雄激素治疗药物耐药问题的化合物分子。方法构建双荧光素酶报告系统检测模型评价化合物对雄激素受体(AR)与GR的转录活性影响,进行基于AR拮抗剂分子共同特征药效团模型和基于GR蛋白晶体结构的虚拟筛选,对虚拟筛选得到的化合物分子进行初步活性评价,验证先导物分子的AR与GR转录抑制活性、耐药性前列腺癌细胞的增殖抑制活性。结果成功构建可用来评价化合物对AR与GR转录活性影响情况的双荧光素酶报告系统,通过虚拟筛选与活性检测得到了化合物分子G8,G8可以抑制AR与GR双靶点转录活性,抑制GR高表达的恩杂鲁胺耐药细胞22Rv1的增殖。结论证实了通过理性药物设计与生物筛选模型筛选得到的化合物G8,可以克服由于GR高表达造成的现有抗雄激素治疗药物耐药问题,具有潜在的临床应用价值。     

基于蛋白质区块结构码技术对EV71病毒抑制剂的高通量筛选

目的 运用蛋白质区块结构码技术对EV71病毒抑制剂进行筛选.方法 从-PDB数据库中提取EV71病毒的复合物晶体结构.通过使用蛋白质区块结构码技术和Discovery Studio Visualizer软件对PDB数据库中含有12种不同小分子化合物的EV71蛋白晶体结构的靶点区进行分析.分别采用不同EV71病毒蛋白的三类靶点片段所在的蛋白A链扫描晶体结构一维码数据库以期发现和EV71病毒蛋白靶点结构相似的新的靶蛋白.靶点结构相似的靶蛋白所作用的小分子可能成为EV71病毒的抑制剂.结果 POLG蛋白和EV71病毒蛋白靶点结构相似,两种POLG蛋白的抑制剂CHEMBL216000,CHEMBL222234可能成为EV71病毒的抑制剂.结论 从药物靶点结构角度阐述了小分子化合物和EV71病毒蛋白的作用机理.通过靶点结构序列的比对挖掘新的靶蛋白,进而为EV71病毒抑制剂的开发提供有益的线索.     

基于吩噻嗪类化合物的新型抗结核小分子化合物的设计、合成及活性研究

目的 借助计算机虚拟筛选技术设计并合成新型抗结核小分子化合物.方法 以氯丙嗪为模板分子,利用Discovery studio 3.0构建相应的3D药效团模型,并对虚拟化合物库进行筛选;对筛选结果进行手动择优选择,化学合成目标化合物并进行体外抗结核分枝杆菌的活性评价.结果 筛选得到活性化合物15个,并合成其中13个,其中化合物9(多巴胺)在体外对结核分枝杆菌表现出中等强度的抑制作用,MIC为8.0 μg/ml.结论 通过药效团的方法筛选得到了结构较吩噻嗪类化合物简单的抗结核活性小分子多巴胺,该化合物作为抗结核分枝杆菌的先导化合物,较吩噻嗪类具有更大的结构修饰空间.     

评价不同的打分函数对虚拟筛选β-分泌酶抑制剂富集率的影响

目的研究多种打分函数对计算机虚拟筛选β-分泌酶(β-secretase,BACE-1)抑制剂的影响。方法采用分子对接软件Surflex虚拟筛选了50个BACE-1的抑制剂和9950个无活性分子,同时应用5种打分函数对筛选的结果分别应用单个打分函数和多个打分函数组合得分排序。结果单独以Surflex_score一个函数抽提对接后的结合模式再进行打分排序后富集率为40,将Surflex_score和D_score两个函数组合后排序可获得48的富集率。结论组合多种不同的打分函数比单个打分函数打分能获得更多的活性化合物。     

基于生物信息学的息痛散治疗痛风性关节炎的作用机制

目的:挖掘中药复方息痛散的有效成分、预测其潜在功能靶标,通过网络药理学和实验验证的方法探讨息痛散治疗痛风性关节炎的作用机制。方法:利用TCMSP、TCMID数据库筛选出息痛散的活性成分及靶标;通过NCBI、GeneCards数据库筛选痛风性关节炎的疾病靶点;将两者靶点通过Cytoscape软件构建蛋白互作网络图并进行拓扑学分析;筛选出核心靶点;通过R软件进行KEGG和GO富集分析;最后分子对接及Western Blot实验验证网络药理学富集分析结果。结果:共筛选出146个活性成分以及158个关键靶点,涉及PI3K-Akt信号通路、TNF信号通路和MAPK信号通路等,实验验证显示通路关键节点蛋白存在差异性表达。结论:本研究系统揭示息痛散通过多成分-多靶点-多途径共同调控痛风性关节炎的物质基础和作用机制,为中药复方息痛散的临床应用提供理论基础和科学依据。     

搭建基于ROCKS的计算机集群系统虚拟筛选β位淀粉样前体蛋白分泌酶1抑制剂

目的 搭建价格便宜的计算机集群用于大规模药物虚拟筛选β位淀粉样前体蛋白分泌酶1(BACE-1)抑制剂.方法 对32台普通个人计算机(PC)进行安装部署Rocks4.3集群操作系统,使用系统自带的默认资源管理软件Sun Grid Engine(SGE),利用AutoDock 4.0在PC集群上进行大规模的虚拟筛选BACE-1抑制剂.结果 针对老年性痴呆发病的关键酶BACE-1成功地虚拟筛选了Sigma公司100000个小分子化合物数据库,发现了2个具有开发潜力的苗头化合物.其解离常数分别为303.36和1.79 nmol/L,半数抑制浓度为(91.0±3.5)和(73.0±4.8)μmol/L.结论 利用普通计算机集群系统可以象高性能计算机一样完成药物虚拟筛选工作.     

核糖体蛋白L12-L10相互作用抑制剂的筛选及其抗结核活性的研究

目的以L12-L10相互作用为靶点筛选具有抗结核活性的先导化合物。方法应用酵母双杂交模型AH109(pAD-L12+pBD-L10)通过生长抑制方法筛选阳性化合物,以AH109(pAD-T+pBD-53)作为对照;通过96孔板法检测阳性化合物对耻垢分枝杆菌的抑制活性;应用定量微孔板快速显色法(MABA)检测抗结核杆菌活性;通过β-半乳糖苷酶活性定量检测判断阳性化合物在模型上对L12-L10相互作用的阻断活性;应用体外蛋白表达系统检测阳性化合物对蛋白表达的抑制作用;应用平皿二倍稀释法检测阳性化合物的药敏作用。结果筛选到4个在模型上具有活性的阳性化合物,其对耻垢分枝杆菌具有比较好的抑制活性,其最小抑制浓度(MIC)在3.125~12.5μg/ml之间;其中IBM-T275对结核分枝杆菌标准株和临床分离株均具有比较好的抑制活性,MIC在5~10μg/ml之间,而对细菌抑制活性较低,其MIC均在64μg/ml以上;IBM-T275能够抑制酵母模型内β-半乳糖苷酶的表达,并且能够体外抑制蛋白表达,其IC50为12.57μg/ml。结论筛选到1个具有抗结核杆菌活性的阳性化合物,其抗结核活性可能与阻断L12-L10蛋白相互作用相关。     

紫檀芪调控KDR和EGFR活性发挥抗肾细胞癌作用研究

目的 利用网络药理学对紫檀芪抗肾细胞癌潜在靶点进行预测,探讨其多靶点、多通路机制抗肾透明细胞癌的分子机制.方法 利用TCMSP、Swiss Target Prediction、Chembl数据库预测紫檀芪的作用靶点,利用OMIM、DisGeNET数据库获得肾细胞癌相关靶点蛋白,对两者靶点进行交集,并用JVENN绘制Venn图,利用STRING及Cytoscape构建PPI网络,根据degree值筛选出关键蛋白,利用GEPIA数据库分析关键蛋白在肾癌细胞及配对正常肾细胞中的差异表达,并利用分子对接对紫檀芪与关键蛋白相关作用进行验证.结果 紫檀芪的潜在靶点有614个,肾透明细胞癌的相关靶点有280个,两者共同作用的靶点有33个,关键的靶点包括MAPK1、EGFR、AKT1、PIK3CB、KDR,其中KDR和EGFR在肾细胞癌中表达显著高于正常配对的肾组织.分子对接发现紫檀芪与KDR和EGFR均具有较好的结合能力.结论 紫檀芪抗肾细胞癌具有多靶点、多途径的特点,KDR和EGFR可能为紫檀芪抗肾细胞癌的关键靶点.     

基于网络药理学和分子对接探讨斑蝥复方制剂治疗宫颈癌的作用机制

目的:基于网络药理学和分子对接技术,探讨斑蝥复方制剂治疗宫颈癌的生物活性成分以及潜在作用机制.方法:从中药系统药理学数据库分析平台(TCMSP)和文献筛选确定相应的活性成分和药物靶点,通过Genecards、OMIM数据库收集宫颈癌靶点.运用STRING数据库借助Cytoscape3.8.2软件构建PPI网络图和"药物...     

基于网络药理及分子对接预测青蒿素对银屑病的作用机制

目的 利用网络药理学和分子对接技术，探讨青蒿素防治银屑病的作用机制。方法 通过PubChem数据库和Swisstarget数据库获取青蒿素的主要有效成分及其作用靶点，从GeneCard数据库获取银屑病的治疗靶点，然后利用STRING数据库和Cytoscape构建靶点PPI网络，并进行聚类分析和筛选关键靶点。利用R软件进行基因本体（GO）和京都基因与基因组百科全书（KEGG）通路分析和目标基因可视化。最后通过AutoDock软件对青蒿素与靶基因进行分子对接验证。结果 共获得41个交集靶点，通路富集分析显示，这些靶点通过调节神经营养蛋白信号通路、血清素突触通路等发挥防治银屑病的作用。对接结果显示，青蒿素可与关键靶点HSP90AA1、EGFR、MAPK14、MAP2K1匹配。结论 通过网络药理学及分子对接的方法，找到了青蒿素治疗银屑病可能的潜在靶点，预测了其发挥药理作用的关键通路。     

Structure-Based Virtual Screening of FGFR Inhibitors

BACKGROUND: Receptor rearrangement upon ligand binding (induced-fit) constitutes a complicating factor in structure-based virtual screening, as protein flexibility is only partially included in many high-throughput docking programs. The effect of protein structure in these cases is rarely discussed. AIM: Our objective was to analyze this influence on three aspects of automated ligand docking: (i) the successful reproduction of binding modes; (ii) the performance in binding site detection for a series of initial decoys positioned on the protein surface; and (iii) the extent to which the protein conformation biases the enrichment factors and the diversity in scaffold retrieval of a Virtual Screening experiment. METHODS: A fibroblast growth factor receptor (FGFR), for which several structures complexed with different inhibitors are publicly available, was selected as a study case. Besides its biological relevance, FGFR is an interesting target because of the structural changes occurring on ligand binding in receptor tyrosine kinases. Three common scoring functions (AUTODOCK, ChemScore, and GoldScore), under different parameter settings, were employed to dock a set of inhibitors of FGFR into these structures. RESULTS: We show how the choice of one particular protein x-ray structure restricts the docking process to the detection of those compounds that belong to the same chemical series or are similar to the chemotype of the corresponding co-crystallized ligand.     

Mapping the binding site for gossypol-like inhibitors of Plasmodium falciparum lactate dehydrogenase

Gossypol is a di-sesquiterpene natural-product in the form of a functionalised binaphthyl and is isolated from cotton plants. The compound has long been known to exhibit anti-malarial and other biological activities. Previous studies have indicated that compounds of this type target Plasmodium falciparum lactate dehydrogenase (pfLDH), an essential enzyme for energy generation within the parasite. In this study, we report that simple naphthalene-based compounds, the core of the gossypol structure, exhibit weak inhibition of the parasite lactate dehydrogenase. Crystal structures of the complexes formed by binding of these naphthalene-based compounds to their target enzyme have been used to delineate the molecular features likely to form the gossypol binding site. Two modes of binding are observed: one overlapping the pyruvate but not the co-factor site, the other bridging the binding sites for the co-factor nicontinamide group and pyruvate substrate. This latter site encompasses molecular features unique to Plasmodium forms of LDH and is likely to represent the mode of binding for gossypol derivatives that show selectivity for the parasite enzymes. We also report a substrate analogue that unexpectedly binds within the adenine pocket of the co-factor groove. Although these core pharmacophore-like molecules only exhibit low levels of inhibitory activity, these molecular snapshots provide a rational basis for renewed structure-based development of naphthalene-based compounds as anti-malarial agents.     

An introduction to the computer-aided structure-based drug design--applications of bioinformatics to drug discovery

Computer-aided drug design methods are effective tools for drug discoveries. It is only small number of compounds that are required to be synthesized in practice, if the computer-aided drug design methods are used to predict the activities of the compounds. The methods are based on the interaction theory between drugs and their target proteins. Steric, electrostatic and hydrophobic complementarities are important in the interaction between the drug and the target protein. When three-dimensional structures of target proteins are known, the method is called as a structure-based drug design, while in case that the structures are unknown, a ligand-based drug design approach is employed for the computer-aided rational drug design. In the computer-aided structure-based drug design, it is important to build up the three-dimensional structure of drug-protein complex and to calculate a binding affinity of the drug to the protein. A molecular dynamics/free energy calculation is one of the most powerful tools to predict the binding affinity of a ligand molecule, when the three-dimensional structure of the drug-protein complex is available. The molecular dynamics/free energy calculation has been able to evaluate the binding affinities of a lot of ligand molecules to the target proteins successfully.     

Identification of Novel Compounds against an R294K Substitution of Influenza A (H7N9) Virus Using Ensemble Based Drug Virtual Screening

Influenza virus H7N9 foremost emerged in China in 2013 and killed hundreds of people in Asia since they possessed all mutations that enable them to resist to all existing influenza drugs, resulting in high mortality to human. In the effort to identify novel inhibitors combat resistant strains of influenza virus H7N9; we performed virtual screening targeting the Neuraminidase (NA) protein against natural compounds of traditional Chinese medicine database (TCM) and ZINC natural products. Compounds expressed high binding affinity to the target protein was then evaluated for molecular properties to determine drug-like molecules. 4 compounds showed their binding energy less than -11Kcal/mol were selected for molecular dynamics (MD) simulation to capture intermolecular interactions of ligand-protein complexes. The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method was utilized to estimate binding free energy of the complex. In term of stability, NA-7181 (IUPAC namely {9-Hydroxy-10-[3-(trifluoromrthyl) cyclohexyl]-4.8-diazatricyclo [6.4.0.02,6]dodec-4-yl}(perhydro-1H-inden-5-yl)formaldehyde) achieved stable conformation after 20ns and 27ns for ligand and protein root mean square deviation, respectively. In term of binding free energy, 7181 gave the negative value of -30.031 (KJ/mol) indicating the compound obtained a favourable state in the active site of the protein.     

LRIG1 enhances the radiosensitivity of radioresistant human glioblastoma U251 cells via attenuation of the EGFR/Akt signaling pathway

The radiotherapy as a local and regional modality is widely applied in treatment of glioma, but most glioblastomas are commonly resistant to irradiation treatment. It remains challengeable to seek out efficient strategies to conquer the resistance of human glioblastoma cells to radiotherapy. Leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) is a newly discovered tumor suppressor which involved in regulation of chemosensitivity in various human cancer cells. In the present study, we established a radioresistant U251 cell line (U251R) to investigate the role of LRIG1 in regulation of radiosensitivity in human glioblastoma cells. Significantly decreased expression level of LRIG1 and enhanced expression of EGFR and phosphorylated Akt were detected in U251R cells compared with the parental U251 cells. U251R cells exhibited an advantage in colony formation ability, which accompanied by remarkably reduced X-ray-induced γ-H2AX foci formation and cell apoptosis. LRIG1 overexpression significantly inhibited the colony formation ability of U251R cells and obviously enhanced X-ray-inducedγ-H2AX foci formation and cell apoptosis. In addition, up-regulated expression of LRIG1 suppressed the expression level of EGFR and phosphorylated Akt protein. Our results demonstrated that LRIG1 expression was related to the radiosensitivity of human glioblastoma cells and may play an important role in the regulation of cellular radiosensitivity of human glioblastoma cells through the EGFR/Akt signaling pathway.     

Computational identification of novel histone deacetylase inhibitors by docking based QSAR

Histone deacetylases (HDACs) are enzymes that modify chromatin structure and contribute to aberrant gene expression in cancer. A series compounds with well-assigned HDAC inhibitory activity was used for docking based 3D-QSAR analysis. The 3D-QSAR acquired had excellent correlation coefficient value (q2=0.753) and high Fisher ratio (F=300.2). A validated pharmacophore model (AAAPR) was employed for virtual screening. After manual selection, molecular docking and further refinement, six compounds with good absorption, distribution, metabolism, and excretion (ADME) properties were selected as potential HDAC inhibitors. Further, the molecular interactions of these inhibitors with the HDAC active site residues were discussed in detail.     

富含亮氨酸重复序列免疫球蛋白样蛋白1基因特异性RNA干扰表达载体的构建、鉴定和稳定株筛选

背景：有研究表明富含亮氨酸重复序列免疫球蛋白样蛋白1(leucine-rich repeats and immunoglobulin-like domains 1,LRIG1)基因在神经胶质瘤细胞中呈低表达,LRIG1基因过表达后对神经胶质瘤细胞的 LRIG1 mRNA和蛋白表达均明显增强和抑制其生物学行为,但却很少有研究从阻断LRIG1基因的表达的角度进行论证。 目的：构建针对LRIG1基因的特异性RNA干扰质粒,稳定转染人脑胶质瘤GL15细胞系,观察其对目的基因LRIG1表达的影响。 方法：根据GenBank提供的LRIG1基因序列设计2条RNA干扰序列,命名为LRIG1-shRNA1和LRIG1-shRNA2,并设计1条非特异性序列作为阴性对照,命名为pGenesil2-negative shRNA。合成各自的寡核苷酸链,退火后与pGenesil2质粒载体连接,转化扩增后测定序列。用不同浓度的G418作用于GL15细胞确定G418对GL15细胞的筛选浓度。将3种重组表达载体转染GL15细胞,G418筛选后挑单克隆并扩增获得稳定株。Western blot检测LRIG1蛋白的表达。 结果与结论：构建的重组pGenesil2-LRIG1- shRNA质粒经限制性酶切及DNA测序分析证明其序列插入正确。转染pGenesil2- LRIG1-shRNA1(LRIG11)细胞和pGenesil2- LRIG1-shRNA2(LRIG12)细胞LRIG1蛋白表达水平较阴性对照组pGenesil2-negative shRNA分别下降47.9%(P < 0.01)和32.8% (P > 0.05)。结果证实,实验成功构建了针对LRIG1基因的特异性shRNA表达载体pGenesil2-LRIG1-shRNA1,其转染GL15细胞后可抑制LRIG1的表达。     

Predicting peptide binding to Major Histocompatibility Complex molecules

The Major Histocompatibility Complex (MHC) constitutes an important part of the human immune system. During infection, pathogenic proteins are processed into peptide fragments by the antigen processing machinery. These peptides bind to MHC molecules and the MHC-peptide complex is then transported to the cell membrane where it elicits an immune response via T-cell binding. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. One of the most challenging aspects of this area of research is understanding the specificity and sensitivity of the binding process. An empirical approach to the problem is unfeasible as there are over 512 billion potential binding peptides for each MHC molecule. Computational approaches offer the promise of predicting peptide binding, thus dramatically reducing the number of peptides proceeding to experimental verification. Various bioinformatic approaches have been developed to predict whether or not a particular peptide will bind to a particular MHC allele. Currently, peptide binding prediction methods can be categorised into three major groups: motif- and scoring matrix-based methods, artificial intelligence- (AI-) based methods, and structure-based methods. The first two are sequence-based approaches and are generally based on common sequence motifs in peptides known to bind to MHC molecules. The structure-based approach concerns the structural features and the distribution of energy between the binding peptide and the MHC molecule. Although knowledge of the molecular structure of the MHC molecules is expected to lead to better predictions of peptide binding, the development of structure-based methods has been relatively slow compared to sequence-based methods. Comparisons of various methods showed that the best sequence-based methods significantly outperform structure-based methods. This may be improved by producing more structures and binding data desperately needed by many alleles, especially class II molecules. On the other hand, the large number of verification methods and indicators used by structure-based studies hinders critical evaluation of the methods. Adopting commonly used assessment procedures can demonstrate the relative performance of structure-based methods in a straightforward comparison with other methods. This review provides an overview of current methods for predicting peptide binding to the MHC, with a focus on structure-based methods, and explores the potential for future development in this area.     

Chemoprevention of Prostate Cancer by Cholecalciferol (Vitamin D<Subscript>3</Subscript>): 25-hydroxylase (CYP27A1) in Human Prostate Epithelial Cells

The 20–30 year latency period for prostate cancer provides an important opportunity to prevent the development of invasive cancer. A logical approach for chemoprevention to reduce incidence is to identify agents, such as, vitamin D, which can inhibit cell proliferation and induce differentiation, are safe, and readily available to the public at low cost. Epidemiological evidence suggests that vitamin D deficiency is associated with increased risk for prostate cancer. We examined the ability and mechanisms of action of cholecalciferol (vitamin D₃), a precursor of the most biologically active hormone calcitriol, to block or reverse premalignant changes. The immortalized, non-tumorigenic, RWPE-1 human prostate epithelial cell line, was used. Results show that cholecalciferol, at physiological levels: (i) inhibits anchorage-dependent growth (ii) induces differentiation by increasing PSA expression and (iii) exerts its effects by up-regulating vitamin D receptor (VDR), retinoid-X receptors (RXRs), and androgen receptor (AR). Furthermore, we discovered that human prostate epithelial cells constitutively express appreciable levels of 25-hydroxylase CYP27A1 protein, the enzyme which catalyzes the conversion of cholecalciferol to 25(OH)D₃, and that CYP27A1 is up-regulated by cholecalciferol. Recent studies show that human mitochondrial CYP27A1 can also catalyze 1α-hydroxylation of 25(OH)D₃ to calcitriol. The presence of 25-hydroxylase in human prostate epithelial cells has not previously been shown. Since human prostate epithelial cells have the necessary enzymes and the rare ability to locally convert cholecalciferol to the active hormone calcitriol, we propose that they are a prime target for chemoprevention of prostate cancer with cholecalciferol whose safety is well established as a supplement in vitamins and fortified foods.