Large-scale prediction and testing of drug activity on side-effect targets

Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.     

Pathway-pathway network-based study of the therapeutic mechanisms by which salvianolic acid B regulates cardiovascular diseases

Investigation of the potential therapeutic mechanisms of drug candidates is an essential step in the process of new drug discovery.With the rapid development of systems biology,recent network analyses of proteins,drugs,and diseases have enabled great progress in delineating the molecule mechanisms of drug candidates.However,most analyses perform a direct association between gene/protein and disease levels without considering the intermediate biological pathways regulated by the drugs.Given that a protein performs its biological roles through pathways,we propose using a novel pathway-pathway network analysis to investigate the potential therapeutic functions of the drug candidates.Many studies have demonstrated that salvianolic acid B(SalB) of Salvia miltiorrhiza is an effective therapy for cardiovascular diseases(CVD).Using molecular docking methods to identify direct interacting targets of Sal B,we collected all Sal B-regulated proteins with supporting experimental evidence in PubMed abstracts.FDA-approved CVD drugs and their corresponding targets were also collected.From a traditional drug-protein network analysis,we found that Sal B could affect ACE and REN of the renin-angiotensin-aldosterone system to relax vessels and alleviate hypertension.Subsequent pathway-pathway network analysis was attempted to study the mechanisms of Sal B in treating CVD,and demonstrated that Sal B regulates immunity/inflammation,apoptosis,ion transport and basic metabolism processes in the treatment of CVD.Regulating the immune/inflammation process may be the major mechanism of Sal B.We believe that pathwaypathway network analysis is a novel method for studying the therapeutic mechanisms of herbal ingredients.     

作为抗癌药物载体的高分子研究进展

利用具有生物相容性的高分子作为载体，化学结合或物理包裹抗肿瘤化学药物．可提高抗肿瘤药物在体内的稳定性和生物利用度。本文从作为抗肿瘤药物载体的高分子的类型、制备方法、性能等方面综述了国内外的研究进展。     

Structure of the catalytic domain of human phosphodiesterase 5 with bound drug molecules

Phosphodiesterases (PDEs) are a superfamily of enzymes that degrade the intracellular second messengers cyclic AMP and cyclic GMP. As essential regulators of cyclic nucleotide signalling with diverse physiological functions, PDEs are drug targets for the treatment of various diseases, including heart failure, depression, asthma, inflammation and erectile dysfunction. Of the 12 PDE gene families, cGMP-specific PDE5 carries out the principal cGMP-hydrolysing activity in human corpus cavernosum tissue. It is well known as the target of sildenafil citrate (Viagra) and other similar drugs for the treatment of erectile dysfunction. Despite the pressing need to develop selective PDE inhibitors as therapeutic drugs, only the cAMP-specific PDE4 structures are currently available. Here we present the three-dimensional structures of the catalytic domain (residues 537-860) of human PDE5 complexed with the three drug molecules sildenafil, tadalafil (Cialis) and vardenafil (Levitra). These structures will provide opportunities to design potent and selective PDE inhibitors with improved pharmacological profiles.     

改进主动形状模型的遥感图像飞机目标识别方法

提出一种基于梯度方向直方图（H OG ）的飞机目标方向估计方法,通过改进主动形状模型（ASM）对不同类型目标之间的形变进行建模,利用核密度估计方法（KDE）得到目标的全局统计形状约束以实现目标识别,并设计了一种针对飞机目标的半自动图像特征点标定策略,提高了对训练样本特征点的标定效率。对遥感图像中飞机目标的识别实验表明,与现有方法相比,研究提出的方法对飞机目标具有更好的识别性能。     

基于频率值传播的药物副作用发生频率预测方法

确定药物副作用发生频率是药物风险-效益评估的关键问题.随机对照临床试验方法性能有限且成本昂贵.随着药物临床试验数据的增加,基于数据驱动计算方法研究药物-副作用关系成为可能.文章提出一种基于药物-副作用协同传播模型的药物副作用发生频率预测方法.该方法基于已知的药物副作用发生频率信息构建相似网络,基于已知频率信息在网络中高阶协同传播过程预测药物副作用发生频率.此外,提出一种基于邻域学习的相似网络构建方法,进一步提升模型预测性能.在SIDER 4.1和ADReCS 3.1中获得的真实的药物-副作用频率数据集上进行实验,相较于现有最优方法,提出的方法在均方根误差和平均绝对误差指标上分别下降了6.98%、7.23%.     

基于数据挖掘及网络药理学探讨中药治疗消化性溃疡的用药规律及作用机制

运用数据挖掘和网络药理学方法探讨中药治疗消化性溃疡(peptic ulcer, PU)的用药规律,筛选核心药对潜在靶点并研究其治疗PU的作用机制。通过频数分析、关联规则分析得出核心药对,筛选核心药对活性成分及靶点;将核心药对治疗PU的关键靶点进行基因本体(gene ontology, GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析;建立药对成分-靶点-信号通路网络。233份治疗PU的处方中含216味中药,其中茯苓-白术为核心药对。核心药对的22个化学成分对应的143个潜在靶点中与PU交集的靶点有41个。通过GO分析,得到相关的92个生物学过程,5个分子功能及11个细胞组成,KEGG分析得出15条信号通路。核心药对茯苓-白术能通过JUN、IL6、TP53、AKT1、VEGFA、MAPK1、CASP3、EGFR、RB1、IL1B靶点调控IL-17、PI3K-AKT、NF-κB、幽门螺杆菌感染中的上皮细胞信号转导等相关通路发挥对PU的治疗作用。通过探讨中药治疗PU的用药规律,初步阐述了治疗PU的核心药对茯苓-白术的药理作用,为临床用药和新药研究提供思路。     

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.     

基于数据挖掘和网络药理学探讨川贝母治疗肺系疾病的核心中药和机制

基于数据挖掘川贝母治疗肺系疾病的核心中药和基于网络药理学探讨“川贝母-人参”治疗肺系疾病之支气管哮喘的作用机制。通过数据处理软件,利用统计学方法对所收集的含贝母肺系疾病中药组方进行频数统计、关联规则分析和聚类分析。并利用网络药理学知识对核心药对治疗肺系典型疾病支气管哮喘进行靶点收集筛选、基因本体论(gene ontology, GO)富集分析和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes, KEGG)富集分析,最后利用分子对接验证。共筛选出含贝母处方420个,涉及中药463味;高频药物有甘草、杏仁等;聚类分析可得8类;高频核心二联药物组合有“川贝母-阿胶”“川贝母-人参”等,三联药物组合包括“川贝母-天冬-麦冬”“川贝母-天冬-甘草”等,四联药物组合“川贝母-桑白皮-桔梗-甘草”“川贝母-桑白皮-杏仁-甘草”等;由于阿胶为动物药材,则分析“川贝母-人参”药对治疗作为治疗支气管哮喘这一典型肺系疾病的核心药对,其中Hub靶点包括“AKT1”“PTGS2”等;核心活性成分包括“beta-sitosterol”“kaempferol”...     

The challenge of new drug discovery for tuberculosis

Tuberculosis (TB) is more prevalent in the world today than at any other time in human history. Mycobacterium tuberculosis, the pathogen responsible for TB, uses diverse strategies to survive in a variety of host lesions and to evade immune surveillance. A key question is how robust are our approaches to discovering new TB drugs, and what measures could be taken to reduce the long and protracted clinical development of new drugs. The emergence of multi-drug-resistant strains of M. tuberculosis makes the discovery of new molecular scaffolds a priority, and the current situation even necessitates the re-engineering and repositioning of some old drug families to achieve effective control. Whatever the strategy used, success will depend largely on our proper understanding of the complex interactions between the pathogen and its human host. In this review, we discuss innovations in TB drug discovery and evolving strategies to bring newer agents more quickly to patients.     

烟曲霉细胞壁作为药物靶标的鉴定研究

烟曲霉(Aspergillus fumigatus)作为侵袭性真菌感染的三大机会病原真菌之一,因其高致病率和高致死率而成为威胁人类健康的重大隐患。有限的抗真菌类药物以及近年来耐药性菌株的涌现使得寻找新的药物靶标并开发新型抗真菌药物迫在眉睫。真菌细胞壁作为真菌所特有的结构一直以来被认为是理想的药物靶标。本文概述了烟曲霉细胞壁结构及合成过程的相关研究进展,并分析了参与细胞壁各组分合成的酶作为药靶的可行性。     

大肠杆菌耐药机制中激活外排泵和减少摄入量的研究进展

概述了大肠杆菌中激活外排泵和减少摄入量这两个重要的耐药机制和克服它们的新策略,主要包括近年来在理解外排泵系统的物理结构、功能和调控子中的进步和有利于开发以外排泵为靶位的药物研究进展。     

重症新型冠状病毒感染药物治疗的研究进展

新型冠状病毒引起的新型冠状病毒感染(Coronavirus Disease-2019,COVID-19)在全球流行爆发,严重威胁人类生命健康,给全球造成了巨大的医疗、经济和社会破坏。重症COVID-19患者病死率高,目前无特效治疗药物,现有的药物治疗主要是通过抑制病毒复制、抗炎及免疫调节等机制起效。对于COVID-19患者,早期使用合适、有效的治疗药物会降低住院率及死亡率,并降低医疗成本,减轻医务人员负担。本文对重症COVID-19患者治疗药物的研究进行综述,拟为临床救治COVID-19患者的药物选择提供参考。     

基于网络药理学和分子对接探讨黄连温胆汤治疗幽门螺杆菌相关性胃炎的作用机制

运用网络药理学和分子对接方法探索黄连温胆汤治疗幽门螺杆菌相关性胃炎的分子机制。应用中药系统药理学数据库与分析平台对黄连温胆汤药物活性成分及药物作用靶点基因进行筛选。通过Genecards数据库、DisGENET数据库查找幽门螺杆菌相关性胃炎疾病相关靶点,利用维恩在线绘图工具获得疾病与药物的共同靶点基因。利用Cytoscape 3.8.2软件以及STRING数据库分别构建药物-化合物-靶点相互作用网络及蛋白质-蛋白质相互作用网络图。运用DAVID数据库进行基因本体功能和京都基因与基因组百科全书通路富集分析。选取度值排名前3的靶点蛋白和活性成分使用AutoDockTools 1.5.6软件进行分子对接。共筛选得到槲皮素、川皮苷、柚皮素等127种黄连温胆汤药物活性成分,并获得Akt1、JUN、TNF-α、STAT3等101个潜在靶点蛋白,涉及P53信号通路、NOD样受体信号通路、TNF信号通路等90条信号通路。分子对接结果显示关键靶点STAT3、TP53、Akt1与活性成分槲皮素、川皮苷、柚皮素的亲和力较好,其中以Akt1与柚皮素的结合能力最强。通过分析黄连温胆汤治疗幽门螺杆菌相关性胃炎的作...     

从小分子药物中探求药物研发新思路

目的:分析小分子药物的优势,提出小分子库是良好的药物筛选库。方法:首先从DrugBank中筛选单靶点小分子药物,构建靶点—结构网络,然后探索小分子药物的化学空间,最后对主要化学性质进行统计分析。结果:小分子药物靶点在结构分类上α/β类型最多(47.98%),并且最古老的fold覆盖了较多的药物和靶点;另外,小分子药物有着良好的分布多样性,而且化学性质也有较好的优势。结论:单靶点结构网络的构建为进一步对天然产物的演变研究提供了新思路,小分子库是药物筛选良好的化合物库。     

后基因组研究与新药开发

传统的药物开发方法在很多方面受到制约，而新的生物技术以及计算机技术为药物开发提供了新的思路．应用现代生物学的理论和技术以及计算机技术来寻找药物作用的靶点，进行药物作用机制的研究以及进行新药毒理学和药动学的研究可以大大提高新药开发的效率．     

基于网络药理学研究厚朴-杏仁治疗哮喘的潜在作用机制

本研究采用网络药理学方法分析厚朴-杏仁配伍治疗哮喘的潜在作用机制。通过BATMAN-TCM数据库检索厚朴、杏仁的中药化学成分及靶标信息，PALM-IST数据库搜索疾病靶标信息，string数据库构建靶标的蛋白质相互作用网络，利用Cytoscape v3.5.1对药物靶标相互作用进行可视化分析，DAVID数据库和Cytoscape v3.5.1的ClueGO+CluePedia插件对药物关键靶标进行GO生物功能富集分析和KEGG信号通路富集分析。共检索到厚朴-杏仁化合物51个，靶标435个，哮喘疾病相关靶标415个，进而分析得到药物治疗疾病关键靶标14个，包括肿瘤坏死因子、过氧化氢酶、白介素13、β2肾上腺素能受体等；GO基因功能分析主要涉及应激反应调控、先天性免疫反应调控、防御反应、急性炎症反应、刺激反应、凝血止血调节、自我内稳定、活性氧代谢过程等生物过程；KEGG分析主要参与NF-κB、IL-17、FcεRI、Toll受体及FoxO等信号通路。厚朴-杏仁能通过多个靶点、多种途径、多条通路对哮喘的气道慢性炎症、气道重塑和气道高反应起潜在治疗作用。     

基于网络药理学研究厚朴-杏仁治疗哮喘的潜在作用机制

本研究采用网络药理学方法分析厚朴-杏仁配伍治疗哮喘的潜在作用机制。通过BATMAN-TCM数据库检索厚朴、杏仁的中药化学成分及靶标信息,PALM-IST数据库搜索疾病靶标信息,string数据库构建靶标的蛋白质相互作用网络,利用Cytoscape v3.5.1对药物靶标相互作用进行可视化分析,DAVID数据库和Cytoscape v3.5.1的ClueGO+CluePedia插件对药物关键靶标进行GO生物功能富集分析和KEGG信号通路富集分析。共检索到厚朴-杏仁化合物51个,靶标435个,哮喘疾病相关靶标415个,进而分析得到药物治疗疾病关键靶标14个,包括肿瘤坏死因子、过氧化氢酶、白介素13、β2肾上腺素能受体等;GO基因功能分析主要涉及应激反应调控、先天性免疫反应调控、防御反应、急性炎症反应、刺激反应、凝血止血调节、自我内稳定、活性氧代谢过程等生物过程;KEGG分析主要参与NF-κB、IL-17、FcεRI、Toll受体及FoxO等信号通路。厚朴-杏仁能通过多个靶点、多种途径、多条通路对哮喘的气道慢性炎症、气道重塑和气道高反应起潜在治疗作用。     

中药致肝毒性相关机制研究

随着我国中医药事业的快速发展,中药在诸多疾病的应用治疗上成果斐然,但不可否认的是,治疗过程中不断出现的毒副作用也是不容忽视的.众所周知,肝脏是机体内负责能量合成和物质代谢的中心器官,特别容易受到药物的损害,成为药源性组织损伤的主要靶器官之一.近年来,其作用机制研究取得了较大的进展,主要包括中药对肝脏细胞的直接损伤、氧化损伤、代谢损伤等.通过查阅相关文献,总结了中药致肝毒性的作用机制及其研究的思路和方法,以期为临床上中药的应用以及其作为保健品的开发,提供可靠的借鉴及依据.     

“硅替代”新药创制研究进展

“硅替代”新药创制即合成现有药物的含硅结构类似物．含硅药物与其碳结构类似物相比，具有独特的理化性质，并表现出特定的生物活性，如更强的药效、更高的选择性和更小的毒副作用．因此，对现有药物进行硅替代是设计、改造药物的有效途径．文章对各种硅替代药物进行了全面综述．