基于酵母水平的高通量药物筛选

随着后基因组时代的到来,越来越多的药物靶标蛋白将会被发现,基于靶标蛋白设计出的化合物也将大量涌现,高通量药物筛选日趋重要。酵母基因组的易操作性及其简单稳定的培养条件,使得该真核微生物成为一种理想的药物筛选工程细胞。本文讨论了选择酵母系统进行细胞水平筛选的优缺点,并从基于靶点和表型两种筛选模式对酵母水平的高通量药物筛选做一总结。     

药物蛋白质组学与药物发现

21世纪,科学家面临着从基因组到蛋白质组的转变,蛋白质组学是基因组和药物发现的效率。药物蛋白质组学研究不仅有助于发现治疗的可能靶点,也将明显提高药物发现的效率。药物蛋白质组学的研究内容,在临床前包括发现新的治疗靶点和发现针对所有靶点的全部化合物,在临床研究方面应包括药物作用的特异蛋白作为诊断和治疗的标志,或以蛋白质谱的差异来分类者。本文主要综述了蛋白质组学在药物靶点的发现和确认,以有药物发现过程中最有关的技术物研究进展。     

上海药物所计算生物学研究取得重要进展

上海药物所药物发现与设计中心（DDDC）近年来在计算生物学、计算化学和药物设计研究方面取得了可喜的成绩,相关研究成果分别在《美国科学院院刊》（PNAS）、《美国化学会志》（JACS）、《核酸研究》（NAR）、《生物化学杂志》（JBC）、《分子生物学杂志》（JMB）、《美国化学会药物化学杂志》（JMC）等国际一流刊物上发表。     

RNAi在药物研究中的应用

RNA干扰是双链RNA分子在mRNA水平上诱发的序列特异性的转录后基因表达沉默。在哺乳动物细胞里,RNAi可以由21-25个核苷酸长度的小干扰RNA（siRNA）触发,在后基因组时代的基因功能研究和药物开发中具有广阔的应用前景。现针对近年RNAi在药物研究中的应用包括应用RNAi发现新药靶、辅助确认药靶、RNAi药物、RNAi与耐药性等方面作一综述。     

网络药理学与药物发现研究进展

将生物学网络与药物作用网络整合,分析药物在网络中与节点或网络模块的关系,由寻找单一靶点转向综合网络分析,就形成了网络药理学.通过系统生物学的研究方法进行网络药理学分析,能够在分子水平上更好的理解细胞以及器官的行为,加速药物靶点的确认以及发现新的生物标志物.这使得我们有可能系统地预测和解释药物的作用,优化药物设计,发现影响药物作用有效性和安全性的因素,从而设计多靶点药物或药物组合.本文综述了网络药理学的新近研究进展,介绍在生物学网络的各个层面上网络药理学的研究和应用,展望网络药理未来的发展方向,对药物发现具有重要意义.     

C_4途径的发现及其生物学意义

C_4途径是继卡尔文发现C_3途径后,发现的一种固定CO_2的新途径。C_4途径的发现经历了最初发现、证实和揭示的过程,在植物细胞学、分类学、生态学、植物演化和CAM植物研究等方面都具有重要意义。     

生物学多媒体发现法教学模式的探索与实践

随着现代科技的飞速发展和教研教改的不断深入 ,应逐步改革传统教学中以教师讲解为主的灌输式教学。为此 ,对生物学多媒体发现法教学模式进行初步研究 ,在教学中以发现教学为主线 ,多媒体教学为辅的体现学生主动参与、主动发展的教学思想 ,构建有教育性、创造性、实践性的以学生主体活动为主的一种教学形式。1　教学指导思想多媒体发现法教学模式以结构主义教育思想为指导 ,以教育学和心理学为依据。结构主义教育思想来源于布鲁纳的认识论 ,他认为“主体对于来自外界的印象不是被动地接受 ,而是给以组织加工”。在教学方法上 ,他提倡“发现…     

新药发现与开发的技术展望

生命科学的高速发展改变了新药研究开发的传统模式。以基因组学为主导的多领域、多学科和多专业的交叉融合极大地提高了发现先导化合物的速率。体外药代和毒性快速检测手段的出现将突破新药临床前评估的技术瓶颈,中药现代化的内涵会以国际通用科学语言进行诠释,预见一系列治疗严重危害人类健康和生命的疾病的创新药物,将在今后20年内成功上市,广泛应用。     

寻找微生物基因组中适合高通量药物筛选靶点的功能未知基因

开发有新作用机制的抗生素迫在眉睫。刚发现青霉素时 ,几乎所有的金黄色链球菌都是药物敏感型 ;异烟肼和链霉素刚用来治疗结核病时 ,效果几乎 1 0 0 % ,但 90年代中期 ,几乎 90 %的金黄色链球菌和 50 %以上的结核分枝杆菌都耐药 ,耐多药菌株也日益普遍。现有抗生素的作用机制比较单一 ,是细菌产生耐药性的一个主要原因。解决日益严重的细菌耐药性、交叉耐药性、毒性和难以根除条件致病菌感染最有效的途径是开发新作用机制的抗生素。1 .微生物基因组及其功能未知基因中蕴涵了开发新型抗生素的大量有用靶点抗生素开发首先往往需要鉴定靶点。靶…     

浏览药物发现数据

为了使药物发现数据变得更有意义，许多公司开发了具有可视化功能的分析工具供研究人员使用。本文将为读者介绍这些具有可视化功能的一系列工具。     

量子点在新药开发中的应用

由于具有优异的光学特性,量子点在生物医学领域内的研究和应用取得了一些有意义的进展,同时也引起了新药开发人员的兴趣.本文概述了量子点在新药开发中所具有的优势,分析了量子点在药物传输、药物筛选和药靶确证方面的潜在应用,进一步讨论了当前量子点应用于新药开发存在的问题和不足.     

Novel computational biology methods and their applications to drug discovery

Computational biology methods are now firmly entrenched in the drug discovery process. These methods focus on modeling and simulations of biological systems to complement and direct conventional experimental approaches. Two important branches of computational biology include protein homology modeling and the computational biophysics method of molecular dynamics. Protein modeling methods attempt to accurately predict three-dimensional (3D) structures of uncrystallized proteins for subsequent structure-based drug design applications. Molecular dynamics methods aim to elucidate the molecular motions of the static representations of crystallized protein structures. In this review we highlight recent novel methodologies in the field of homology modeling and molecular dynamics. Selected drug discovery applications using these methods conclude the review.     

In vivo drug target discovery: identifying the best targets from the genome

A vast number of genes of unknown function threaten to clog drug discovery pipelines. To develop therapeutic products from novel genomic targets, it will be necessary to correlate biology with gene sequence information. Industrialized mouse reverse genetics is being used to determine gene function in the context of mammalian physiology and to identify the best targets for drug development.     

光亲和标记技术在药物发现中的应用

功能蛋白质组学的研究在药物发现中扮演着重要的角色,而光亲和标记技术是研究功能蛋白质组学的主要策略之一,它主要有两个方面的应用：靶标蛋白的确定和活性小分子配体与靶标蛋白作用模式的揭示,这些信息为药物的发现提供了强有力的支持。     

A solid-phase glycosyltransferase assay for high-throughput screening in drug discovery research

Glycosyltransferases mediate changes in glycosylation patterns which, in turn, may affect the function of glycoproteins and/or glycolipids and, further downstream, processes of development, differentiation, transformation and cell-cell recognition. Such enzymes, therefore, represent valid targets for drug discovery. We have developed a solid-phase glycosyltransferase assay for use in a robotic high-throughput format. Carbohydrate acceptors coupled covalently to polyacrylamide are coated onto 96-well plastic plates. The glycosyltransferase reaction is performed with recombinant enzymes and radiolabeled sugar-nucleotide donor at 37°C, followed by washing, addition of scintillation counting fluid, and measurement of radioactivity using a 96-well -counter. Glycopolymer construction and coating of the plastic plates, enzyme and substrate concentrations, and linearity with time were optimized using recombinant Core 2 1-6-N-acetylglucosaminyltransferase (Core 2 GlcNAc-T). This enzyme catalyzes a rate-limiting reaction for expression of polylactosamine and the selectin ligand sialyl-Lewis^x in -glycans. A glycopolymer acceptor for 1-6-N-acetylglucosaminyltransferase V was also designed and shown to be effective in the solid-phase assay. In a high-throughput screen of a microbial extract library, the coefficient of variance for positive controls was 9.4%, and high concordance for hit validation was observed between the Core 2 GlcNAc-T solid-phase assay and a standard solution-phase assay. The solid-phase assay format, which can be adapted for a variety of glycosyltransferase enzymes, allowed a 5–6 fold increase in throughput compared to the corresponding solution-phase assay.     

Homology modeling: an important tool for the drug discovery

In the last decades, homology modeling has become a popular tool to access theoretical three-dimensional (3D) structures of molecular targets. So far several 3D models of proteins have been built by this technique and used in a great diversity of structural biology studies. But are those models consistent enough with experimental structures to make this technique an effective and reliable tool for drug discovery? Here we present, briefly, the fundamentals and current state-of-the-art of the homology modeling techniques used to build 3D structures of molecular targets, which experimental structures are not available in databases, and list some of the more important works, using this technique, available in literature today. In many cases those studies have afforded successful models for the drug design of more selective agonists/antagonists to the molecular targets in focus and guided promising experimental works, proving that, when the appropriate templates are available, useful models can be built using some of the several software available today for this purpose. Limitations of the experimental techniques used to solve 3D structures allied to constant improvements in the homology modeling software will maintain the need for theoretical models, establishing the homology modeling as a fundamental tool for the drug discovery.     

Yeast and drug discovery

Advanced genetic techniques, along with the high degree of conservation of basic cellular processes, have made the yeast Saccharomyces cerevisiae a valuable system for identification of new drug targets, target-based and non-target-based drug screening, and detailed analysis of the cellular effects of drugs. Yeast also presents a convenient system for antifungal drug discovery because it is closely related to Candida albicans, a major human pathogen. Many yeast genes remain poorly characterized, and most of the sophisticated techniques in yeast have been in widespread use less than a decade – a period shorter than the typical cycle from target identification to marketing approval for a new drug. It is likely that most of the benefits of yeast in discovery and development of therapeutic compounds have yet to be realized. Electronic Publication     

Genetics-directed drug discovery for combating Mycobacterium tuberculosis infection

Mycobacterium tuberculosis (Mtb), the pathogen of tuberculosis (TB), is one of the most infectious bacteria in the world. The traditional strategy to combat TB involves targeting the pathogen directly; however, the rapid evolution of drug resistance lessens the efficiency of this anti-TB method. Therefore, in recent years, some researchers have turned to an alternative anti-TB strategy, which hinders Mtb infection through targeting host genes. In this work, using a theoretical genetic analysis, we identified 170 Mtb infection-associated genes from human genetic variations related to Mtb infection. Then, the agents targeting these genes were identified to have high potential as anti-TB drugs. In particular, the agents that can target multiple Mtb infection-associated genes are more druggable than the single-target counterparts. These potential anti-TB agents were further screened by gene expression data derived from connectivity map. As a result, some agents were revealed to have high interest for experimental evaluation. This study not only has important implications for anti-TB drug discovery, but also provides inspirations for streamlining the pipeline of modern drug discovery.     

Protein targets for structure-based anti-Mycobacterium tuberculosis drug discovery

Mycobacterium tuberculosis, which belongs to the genus Mycobacterium, is the pathogenic agent for most tuberculosis (TB). As TB remains one of the most rampant infectious diseases, causing morbidity and death with emergence of multi-drug-resistant and extensively-drug-resistant forms, it is urgent to identify new drugs with novel targets to ensure future therapeutic success. In this regards, the structural genomics of M. tuberculosis provides important information to identify potential targets, perform biochemical assays, determine crystal structures in complex with potential inhibitor(s), reveal the key sites/residues for biological activity, and thus validate drug targets and discover novel drugs. In this review, we will discuss the recent progress on novel targets for structure-based anti-M. tuberculosis drug discovery.