基于药效团和分子对接的黄芪甲苷改善HepG2细胞胰岛素抵抗作用及机制研究

目的观察黄芪甲苷(astragalosideIV,ASTIV)改善人肝癌HepG2细胞胰岛素抵抗作用,基于药效团模型相互匹配和分子对接预测和验证AST IV可能作用靶点,探讨AST IV改善胰岛素抵抗机制。方法采用高浓度胰岛素诱导HepG2细胞制备胰岛素抵抗模型,ASTIV干预后,检测细胞葡萄糖消耗量,基于药效团模型相互匹配和分子对接预测ASTIV可能作用靶点,Western blotting法检测通路相关蛋白表达。结果 AST IV干预能显著增加胰岛素抵抗的HepG2细胞葡萄糖消耗量,且效应与盐酸吡格列酮相当;基于药效团模型相互匹配和分子对接预测AST IV作用靶点与酪氨酸磷酸酶1B(PTP1B)相关;Western blotting结果显示,胰岛素抵抗的HepG2细胞PTP1B蛋白表达水平显著升高,而胰岛素信号通路关键蛋白磷酸化的胰岛素受体(p-IR)和磷酸化的胰岛素受体底物1(p-IRS-1)表达水平显著降低;ASTIV的干预能显著降低PTP1B蛋白表达水平,升高p-IR和p-IRS-1蛋白表达水平。结论 ASTIV能显著改善高浓度胰岛素诱导的HepG2细胞的胰岛素抵抗,其作用机制与抑制PTP1B激活胰岛素信号通路有关。     

Analysis of Enoyl‐Acyl Carrier Protein Reductase Structure and Interactions Yields an Efficient Virtual Screening Approach and Suggests a Potential Allosteric Site

Enoyl‐acyl carrier protein reductases have an important role in fatty acid biosynthesis and are considered essential for bacterial and protozoal survival. Here, we perform a computational assessment of enoyl‐acyl carrier protein reductase structures, providing insights for inhibitor design that we incorporate into a virtual screening approach. Firstly, we analyse 80 crystal structures of 16 different enoyl‐acyl carrier protein reductases for their active site characteristics and druggability, finding these sites contain a readily druggable pocket, of varying size and shape. Interestingly, a high affinity, potentially allosteric site was identified for pfFabI. Analysis of the ligand–protein interactions of four enoyl‐acyl carrier protein reductases from different micro‐organisms (InhA, pfFabI, saFabI and ecFabI), involving 59 available crystal structures, found three commonly shared interactions; constraining these interactions in docking improved enrichment of enoyl‐acyl carrier protein reductase virtual screens, by up to 60% in the top 3% of the ranked library. This docking protocol also improved pose prediction, decreasing the root‐mean‐square deviation to crystallographic pose by up to 75% on average. The binding site analysis and knowledge‐based docking protocol presented here can potentially assist in the structure‐based design of new enoyl‐acyl carrier protein reductase inhibitors.     

Keynote review: histamine H3 receptor antagonists reach out for the clinic

Antagonists of the histamine H(1) and H(2) receptors have been successful as blockbuster drugs for treating allergic conditions and gastric ulcers, respectively. As such, histamine receptors have made a significant contribution to establishing G-Protein-coupled receptors as the favored drug targets of the industry. In this light, it can easily be understood that the discovery of a third histamine receptor subtype (H(3)R) in 1983 was greeted with considerable excitement. However, characterization of the H(3)R turned out to be far from trivial. In the past five years, molecular biology approaches have given fresh impetus to the H(3)R research field. As a result, H(3)R ligands are where they were anticipated to be 20 years ago: at the center of attention and on the verge of an anticipated breakthrough as the next generation of histaminergic blockbuster drugs. Here, we assess the status of the H(3)R medicinal chemistry programs of the various players in the field, as far as can be deduced from patent applications and scientific literature.     

基于UPLC-Q-TOF-MS和网络药理学探讨丝穗金粟兰水提物抗炎镇痛药效物质及作用机制

目的 利用高效液相色谱-四极杆飞行时间串联质谱法（UPLC-Q-TOF-MS）分析丝穗金粟兰Chloranthus fortune水提物的主要成分,并结合网络药理学的方法对其抗炎镇痛药效物质及作用机制进行预测分析。方法 结合ChemSpider数据库、mz Cloud平台及现有文献研究,对目标化合物二级质谱特征碎片离子进行比对确认,鉴定丝穗金粟兰水提物的化学成分;通过FAFDrug4数据库筛选丝穗金粟兰水提物的活性成分,运用Pharmmapper平台和Uniprot数据库预测丝穗金粟兰的成分靶点,GeneCards平台获得相关疾病靶点,利用Venny平台获得成分和疾病的交集靶点;通过String数据库和Cytoscape3.7.0软件构建蛋白质-蛋白质相互作用（protein-protein interaction,PPI）网络,并筛选核心靶点,利用David数据库对潜在的核心靶点进行基因本体（gene ontology,GO）功能和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes,KEGG）通路富集分析,并构建“活性成分-靶点-...     

Strategies for Indirect Computer-Aided Drug Design

This review is intended to describe some of the methods and procedures used for computer-aided drug design when the structure of the macromolecular target is unknown, as is the case for CNS active drugs. Strategies and methods used in computer-aided design of drugs in such instances must be "indirect, i.e., focusing on the characterization of the ligands themselves. This situation is different from one in which the three-dimensional structure of the macromolecular target for a drug is known, for example, for drugs that are enzyme inhibitors, allowing "direct characterization of ligand-receptor interactions. Two qualitatively different "indirect approaches are described here. One, called 2D-QSAR, is briefly reviewed. It is based on delineating regression relationships between a specified biological end point and properties of the compounds eliciting it. The other, based on pharmacophore development, constitutes the main part of this review. Several levels of pharmacophore development are described, which differ in the extent to which they encompass fundamental molecular properties that are determinants of receptor recognition and activation. The strengths and limitations of each procedure are discussed and illustrated by examples. Two methods for obtaining model receptor structures are then briefly described. Both rely on the prior success of the indirect methods in obtaining ligand properties that modulate receptor recognition and activation. These emerging capabilities have the potential to bridge the gap between indirect and direct methods of drug design, since, if successful, the design process can continue in a direct mode using explicit characterization of drug–receptor interactions. Strategies for hypothesis validation and use of hypothesis for drug design and discovery are also briefly reviewed. The final sections of this review describe specific computational tools such as molecular mechanics and quantum mechanical methods used to characterize and identify relevant molecular properties and indicate some areas for future development of computational chemistry methods that could increase its effectiveness in the design of novel drugs.     

Structure Activity Relationship of Antiproliferative Agents using Multiple Linear Regression

With cancer‐related fatalities being the second leading cause of death in the USA, understanding the activity of effective chemotherapeutic agents is critical to addressing prostate and other cancers. Celecoxib, an FDA‐approved drug for the treatment of colon tumors, has been used successfully as a lead compound in the development of antiproliferative agents. The ability of celecoxib to inhibit the development and progression of tumors has been connected to a number of mechanisms of actions that are both dependent on and independent of its cyclooxygenase‐2 activity. A structure‐based approach has been employed to develop a model that underscores the structural significance of celecoxib as an antiproliferative agent. By evaluating the structure activity of this library of molecules, we were able to create a QSAR model for predicting the antiproliferative activity of structurally similar molecules. The development of the model will be presented in this paper.     

Discovery of HIV‐1 Integrase Inhibitors: Pharmacophore Mapping,Virtual Screening,Molecular Docking,Synthesis, and Biological Evaluation

HIV‐1 integrase enzyme plays an important role in the life cycle of HIV and responsible for integration of virus into human genome. Here, both computational and synthetic approaches were used to design and synthesize newer HIV‐1 integrase inhibitors. Pharmacophore mapping was performed on 20 chemically diverse molecules using DISCOtech, and refinement was carried out using GASP. Ten pharmacophore models were generated, and model 2, containing four features including two donor sites, one acceptor atom, and one hydrophobic region, was considered the best model as it has the highest fitness score. It was used as a query in NCI and Maybridge databases. Molecules having more than 99% Q_fit value were used to design 30 molecules bearing pteridine ring and were docked on co‐crystal structure of HIV‐1 integrase enzyme. Among these, six molecules, showing good docking score compared with the reference standards, were synthesized by conventional as well as microwave‐assisted methods. All compounds were characterized by physical and spectral data and evaluated for in vitro anti‐HIV activity against the replication of HIV‐1 (IIIB) in MT‐4 cells. The used approach of molecular docking and anti‐HIV activity data of designed molecules will provide significant insights to discover novel HIV‐1 Integrase Inhibitors.     

新型Mer酪氨酸激酶抑制剂核心骨架的虚拟筛选

目的 发现一系列新型选择性Mer酪氨酸激酶抑制剂(TKI)的母核结构,并依据其设计化合物。方法 分别利用3个已发表的Mer TK及配体(化合物1、2和3)的复合晶体结构(PDB code:3TCP,4MHA和4M3Q),由ZINCPharmer来产生只包含配体核心区域的药效团模型,并对ZINC化合物库进行筛选。筛选结果经过分析、归类,得到新型母核结构,据其设计化合物,并利用分子对接技术对设计化合物进行初步评价。结果 药效团筛选得到含有16 253个化合物的数据集,归类为12种核心结构,它们可以和关键氨基酸形成相互作用的原子或基团。其中,化合物12将疏水脂肪链含于芳环中,结构变化较大,依据其设计了化合物16a~16d,分子对接发现16c评分最高,可作为进一步理性设计的基础。结论 本研究通过基于药效团模型的虚拟筛选方法,发现了一系列选择性Mer TKI母核结构的替代物,它们保持了选择性抑制剂与靶点的关键作用,可应用于新化合物的设计中。同时,此方法也可用于其他靶标药物的发现中。     

芳基哌嗪苯并噁嗪类化合物的设计、合成及生物活性研究

以具有5-HT再摄取/5-HT1A双重活性化合物为训练集分子,构建药效团模型,设计合成了8个未见文献报道的芳基哌嗪苯并噁嗪类新化合物,结构经1H NMR及HR-MS分析确证。5-HT再摄取和5-HT1A受体结合实验显示,VI1和VI7为5-HT再摄取/5-HT1A双重活性化合物。VI1和VI7可作为先导结构指导后续活性新化合物的设计和合成研究。     

Ligand-based virtual screening and molecular docking studies to identify the critical chemical features of potent cathepsin D inhibitors

Cathepsin D is a major component of lysosomes and plays a major role in catabolism and degenerative diseases. The quantitative structure-activity relationship study was used to explore the critical chemical features of cathepsin D inhibitors. Top 10 hypotheses were built based on 36 known cathepsin D inhibitors using HypoGen/Discovery Studio v2.5. The best hypothesis Hypo1 consists of three hydrophobic, one hydrogen bond acceptor lipid, and one hydrogen bond acceptor features. The selected Hypo1 model was cross-validated using Fischer's randomization method to identify the strong correlation between experimental and predicted activity value as well as the test set and decoy sets used to validate its predictability. Moreover, the best hypothesis was used as a 3D query in virtual screening of Scaffold database. Subsequently, the screened hit molecules were filtered by applying Lipinski's rule of five, absorption, distribution, metabolism, and toxicity, and molecular docking studies. Finally, 49 compounds were obtained as potent cathepsin D inhibitors based on the consensus scoring values, critical interactions with protein active site residues, and predicted activity values. Thus, we suggest that the application of Hypo1 could assist in the selection of potent cathepsin D leads from various databases. Hence, this model was used as a valuable tool to design new candidate for cathepsin D inhibitors.