新药物分子设计的某些理论方法

新药物的先导物设计和新药物的优选设计是两个不同的概念和范畴，本文介绍了发现先导药物的组合化学、群集筛选和计算机筛选方法等最新进展。同时介绍了构效关系研究中的某些基本理论方法。讨论了新药物分子设计的某些问题及其弥补措施。     

毛细管电泳药物筛选方法与技术

毛细管电泳（CE）在新药研发领域显示着重要的应用前景。CE使用水溶液介质作为实验体系,保证了药物筛选在类似于生命介质的环境中进行,优于其他传统体外仪器筛选方法。除了维持被筛选分子和作用对象的生物活性外,CE筛选过程着重突出配体与受体之间的相互作用。毛细管电泳药物筛选瞄准与药理学理论相关的重要参数,如结合常数K_b 、结合速率常数K_on 和解离速率常数K_off ,有利于模拟并预测机体内靶标与药物之间的相互作用过程。该文回顾了毛细管电泳进行药物筛选的历史,评述了毛细管电泳药物筛选方法所依据的理论和相对成熟的各种常用方法,并抽取了部分典型实例以及相关技术进行说明,对以亲和毛细管电泳、动力学毛细管电泳为手段的药物筛选方法进行了介绍,包括分子和细胞层次的药物筛选,以及针对不同类型的候选药物的研究工作都有提及。毛细管电泳与多种技术的联用,包括与质谱以及化学发光等联用发挥了更大的效能。联用方法还应用于中药有效成分的筛选。毛细管电泳在DNA编码化合物库筛选中将有良好应用前景。馏分收集的发展为筛选药物提供了广阔前景,它配合指数富集配体系统进化技术为毛细管电泳药物筛选提供了更多可能。总之,毛细管电泳多样可选的药物筛选方法和技术将为新概念的药物筛选与药物评价提供有力支撑。     

分子对接在药物虚拟筛选中的应用进展

虚拟筛选是药物设计的重要手段之一,利用小分子化合物与药物靶标间的分子对接运算,研究人员可以准确地获取两者之间的相互作用情况,从候选化合物库中快速筛选出潜在的药物或药物前体,从而加速药物开发过程。介绍了虚拟筛选与分子对接的相关原理与流程,主要综述了对药物进行虚拟筛选时所涉及的分子对接技术类型、常见的分子对接软件以及分子对接典型样例。分子对接对提高虚拟筛选的效率、降低药物开发的成本具有重要的现实意义。     

基于微流控技术的细胞水平高通量药物筛选系统的研究进展

药物筛选是新药研发的关键步骤,创新药物的发现需要采用适当的药物作用靶点对大量化合物样品进行筛选。高通量筛选系统能够实现数千个反应同时测试和分析,大大提高了药物筛选的实验规模和效率。其中基于细胞水平的高通量药物筛选系统因为更加接近人体生理条件,成为主要的筛选模式。而目前发展成熟的高通量细胞筛选系统主要基于多孔板,存在细胞培养条件单一、耗时费力、试剂消耗量大等问题,且较难实现复杂的组合药物筛选。微流控技术作为一种在微米尺度通道中操纵和控制微流体的技术,具有微量、高效、高通量和自动化的优点,能较好地克服多孔板筛选系统的不足,为构建细胞高通量药物筛选系统提供了一种高效、可靠的技术手段。微流控系统在细胞培养材料、芯片结构设计和流体控制方面均可灵活变化,能更好地实现对细胞生长微环境的调控和模拟。文章综述了基于微流控技术的细胞水平高通量药物筛选系统的研究进展,按照不同的微流体操控模式,对基于灌注流、液滴和微阵列的3种类型的微流控细胞筛选系统进行了分类介绍,并分别总结了它们的优缺点,最后展望了微流控细胞水平高通量药物筛选系统的发展前景,提出了该领域目前存在的问题以及解决问题的方向。     

非水溶性药物潜在靶蛋白筛选方法探索

针对化学蛋白质组学在筛选非水溶性药物的靶蛋白中存在的问题,建立了以非水溶性药物颗粒为载体的靶蛋白筛选方法.通过避免药物固定化,不仅可以保留全部的药物官能团,而且减少了蛋白质在固载基质上的非特异性吸附,可提高获得数据的可信度.将非溶性药物地塞米松颗粒直接与人小细胞肺癌H446细胞提取蛋白质通过间歇性振荡孵育24h,然后采用缓冲液清洗药物颗粒,最后对药物颗粒特异性结合的蛋白质进行酶解和分离鉴定.结果表明,筛选出41个潜在的药物靶蛋白,参与了与DEX药物作用机理相关的多种蛋白质代谢通路和糖代谢通路,同时还发现部分蛋白质参与了帕金森症疾病过程.     

高通量药物筛选现代检测技术研究进展

高通量药物筛选是发现创新药物的重要技术途径.高通量筛选结果必须通过适当的检测方法才能反映出来,检测技术是实现高通量药物筛选的基础.本文综述了近年来有关光学分析、色谱分析、热分析、电化学分析、质谱、核磁共振等现代检测技术在高通量药物筛选研究中的进展.     

基于三维多靶阵列微流控芯片研究小檗碱对多种DNA的靶向性

研制了一种能体现药物对多靶点杂泛性作用的三维多靶阵列微流控芯片。芯片分为三层上下立体结构,上层为多个靶点通道,下层为药液通道,中间以PC多孔膜相隔。药液在流动过程中通过多孔膜扩散至上层与各靶点竞争结合,靶点通道中的溶液流出后收集检测药物结合量。本文以小檗碱为模型药物,以1种双链DNA(CTDNA)和3种G-四链体DNA(HT22、HT24、C-MYC)为多靶点模型,测定小檗碱对4种不同DNA的亲和力和选择性。结果证明,小檗碱和各DNA结合量由大到小依次为HT22>HT24> C-MYC> CTDNA,说明小檗碱对G-四链体DNA具有较高的选择性。该芯片模拟药物作用的杂泛性,并从中筛选出足够强度和选择性好的药物,可拓展用于多靶点药物的筛选以及多成分对多靶点的作用机制研究。     

亚运会兴奋剂检测

本文建立了检查IOC禁用的五大类100种药物的筛选和确证方法。对药物检查机构及资格认可,药物检验的一般步骤,第十一届亚运会兴奋剂的检测均作了简要的介绍。     

药物筛选新技术及其应用进展

药物筛选是应用适当的筛选方法和筛选技术从海量化合物中筛选出具有药理活性的化合物的方法,是提高研发效率、缩短周期、减少成本、降低风险、使新药研发能够持续进行的关键。药物筛选新技术的开发已成为医药科学研究的重要内容。该文就近年来发展的药物筛选新技术及其应用进行了简要综述。     

化学库及分子差异性设计研究进展

组合化学是近年来发展起来的一种快速合成和平行筛选群体化合物的新方法。它可以用来设计先导化合物，也可以对药物分子进行结构改造。本文主要综述了化学库的合成以及计算机辅助组合化学的研究进展。     

化学基元组学与药物创新

化学基元组学（chemomics）是与化学信息学、生物信息学、合成化学等学科相关的交叉学科．生物系统从内源性小分子（天然砌块）出发,通过酶催化的化学反应序列制造天然产物．生物系统通过化学反应和天然砌块向目标天然产物“砌入”一组原子,这样的一组原子称为化学基元（chemoyl）．化学基元组（chemome）是生物组织中所含有的化学基元的全体．化学基元组学研究各种化学基元的结构、组装与演化的基本规律．在生存压力和繁衍需求的驱动下,生物系统已经进化出有效手段来合成天然产物以应付环境的变化,并产生了丰富多彩的生物和化学多样性．近年来,人们意识到药物创新的瓶颈之一是药物筛选资源的日益枯竭．化学基元组学可以解决这个瓶颈问题,它通过揭示生物系统制备化学多样性的规律,发展仿生合成方法制备类天然化合物库（quasi natural product libraries）以供药物筛选．本文综述了化学基元组学的主要研究内容及其在药物创新各领域中的潜在应用．     

Chemomics and drug innovation

Chemomics is an interdisciplinary study using approaches from chemoinformatics,bioinformatics,synthetic chemistry,and other related disciplines.Biological systems make natural products from endogenous small molecules (natural product building blocks) through a sequence of enzyme catalytic reactions.For each reaction,the natural product building blocks may contribute a group of atoms to the target natural product.We describe this group of atoms as a chemoyl.A chemome is the complete set of chemoyls in an organism.Chemomics studies chemomes and the principles of natural product syntheses and evolutions.Driven by survival and reproductive demands,biological systems have developed effective protocols to synthesize natural products in order to respond to environmental changes;this results in biological and chemical diversity.In recent years,it has been realized that one of the bottlenecks in drug discovery is the lack of chemical resources for drug screening.Chemomics may solve this problem by revealing the rules governing the creation of chemical diversity in biological systems,and by developing biomimetic synthesis approaches to make quasi natural product libraries for drug screening.This treatise introduces chemomics and outlines its contents and potential applications in the fields of drug innovation.     

SARS-CoV protease inhibitors design using virtual screening method from natural products libraries

Two natural products databases, the marine natural products database (MNPD) and the traditional Chinese medicines database (TCMD), were used to find novel structures of potent SARS-CoV protease inhibitors through virtual screening. Before the procedure, the databases were filtered by Lipinski's ROF and Xu's extension rules. The results were analyzed by statistic methods to eliminate the bias in target-based database screening toward higher molecular weight compounds for enhancing the hit rate. Eighteen lead compounds were recommended by the screening procedure. They were useful for experimental scientists in prioritizing drug candidates and studying the interaction mechanism. The binding mechanism was also analyzed between the best screening compound and the SARS protein.     

Recent theoretical and practical applications of micellar liquid chromatography (MLC) in pharmaceutical and biomedical analysis

Micellar liquid chromatography (MLC) is an analytical technique belonging to the wide range of reversed-phase liquid chromatographic (RP-LC) separation techniques. MLC with the use of surfactant solutions above its critical micellar concentration (CMC) and the addition of organic modifiers is currently an important analytical tool with still growing theoretical considerations and practical applications in pharmaceutical analysis of drugs and other biologically active compounds. The use of MLC as an alternative, relatively much faster in comparison to conventional chromatographic separation techniques has several advantages, especially as being suitable for screening pharmaceutical analysis. The analytical data received from MLC analysis are considered a useful source of information to predict passive drug absorption, drug transport and other pharmacokinetics and physicochemical measures of pharmaceutical substances.     

The beautiful cell: high-content screening in drug discovery

The term “high-content screening” has become synonymous with imaging screens using automated microscopes and automated image analysis. The term was coined a little over 10 years ago. Since then the technology has evolved considerably and has established itself firmly in the drug discovery and development industry. Both the instruments and the software controlling the instruments and analyzing the data have come to maturity, so the full benefits of high-content screening can now be realized. Those benefits are the capability of carrying out phenotypic multiparametric cellular assays in an unbiased, fully automated, and quantitative fashion. Automated microscopes and automated image analysis are being applied at all stages of the drug discovery and development pipeline. All major pharmaceutical companies have adopted the technology and it is in the process of being embraced broadly by the academic community. This review aims at describing the current capabilities and limits of the technology as well as highlighting necessary developments that are required to exploit fully the potential of high-content screening and analysis.     

基于虚拟筛选策略发现新型潜在JAK3小分子抑制剂

利用已知活性的分子采用基于配体的策略构建药效团模型,通过基于类药规则、药效团模型、多种精度的分子对接算法、MM/GBSA结合能预测以及ADMET筛选手段对含约250万个分子的数据库进行虚拟筛选。发现5种JAK3抑制剂的新型骨架,其中6个以1-苯基咪唑烷-2-酮为骨架的分子在与JAK3激酶的结合能以及分子的ADMET性质评价方面均表现优异,具备高JAK3抑制剂潜力,被认为是虚拟筛选的命中分子。     

High throughput automated chromatin immunoprecipitation as a platform for drug screening and antibody validation

Chromatin immunoprecipitation (ChIP) is an assay for interrogating protein-DNA interactions that is increasingly being used for drug target discovery and screening applications. Currently the complexity of the protocol and the amount of hands-on time required for this assay limits its use to low throughput applications; furthermore, variability in antibody quality poses an additional obstacle in scaling up ChIP for large scale screening purposes. To address these challenges, we report HTChIP, an automated microfluidic-based platform for performing high-throughput ChIP screening measurements of 16 different targets simultaneously, with potential for further scale-up. From chromatin to analyzable PCR results only takes one day using HTChIP, as compared to several days up to one week for conventional protocols. HTChIP can also be used to test multiple antibodies and select the best performer for downstream ChIP applications, saving time and reagent costs of unsuccessful ChIP assays as a result of poor antibody quality. We performed a series of characterization assays to demonstrate that HTChIP can rapidly and accurately evaluate the epigenetic states of a cell, and that it is sensitive enough to detect the changes in the epigenetic state induced by a cytokine stimulant over a fine temporal resolution. With these results, we believe that HTChIP can introduce large improvements in routine ChIP, antibody screening, and drug screening efficiency, and further facilitate the use of ChIP as a valuable tool for research and discovery.     

High throughput screening for neurodegeneration and complex disease phenotypes

High throughput screening (HTS) for complex diseases is challenging. This stems from the fact that complex phenotypes are difficult to adapt to rapid, high throughput assays. We describe the recent development of high throughput and high-content screens (HCS) for neurodegenerative diseases, with a focus on inherited neurodegenerative disorders, such as Huntington's disease. We describe, among others, HTS assays based on protein aggregation, neuronal death, caspase activation and mutant protein clearance. Furthermore, we describe high-content screens that are being used to prioritize hits identified in such HTS assays. These assays and screening approaches should accelerate drug discovery for neurodegenerative disorders and guide the development of screening approaches for other complex disease phenotypes.     

血脑屏障药物筛选模型的建立及丹参活性成分筛选分析

ECV304细胞在C6细胞的诱导下生长,通过细胞培养时间优化、渗透系数测定和细胞形态学观察等,建立ECV304/C6共培养血脑屏障(BBB)药物筛选模型.将该模型应用于从丹参提取液中筛选可能作用于中枢神经系统(CNS)的活性成分,结合液相色谱-质谱联用技术(LC-MS)分析,发现丹参提取液中至少有16种成分能够穿越BBB模型,其中4种成分被确认为隐丹参酮、丹参酮Ⅰ、丹参素和原儿茶酸.通过定量构效关系(QASR)分析,进一步从理论上证明所确认的4种化合物均符合CNS靶向药物的特征.研究结果表明,ECV304/C6共培养BBB模型能够在模拟生理状态下从中药复杂体系中筛选分离跨越BBB的活性成分组,可用于CNS药物开发的早期快速筛选,服务于中药现代化研究.     

Chlortetracycline,a Novel Arf Inhibitor That Decreases the Arf6-Dependent Invasive Properties of Breast Cancer Cells

Breast cancer is a major disease for women worldwide, where mortality is associated with tumour cell dissemination to distant organs. While the number of efficient anticancer therapies increased in the past 20 years, treatments targeting the invasive properties of metastatic tumour cells are still awaited. Various studies analysing invasive breast cancer cell lines have demonstrated that Arf6 is an important player of the migratory and invasive processes. These observations make Arf6 and its regulators potential therapeutic targets. As of today, no drug effective against Arf6 has been identified, with one explanation being that the activation of Arf6 is dependent on the presence of lipid membranes that are rarely included in drug screening. To overcome this issue we have set up a fluorescence-based high throughput screening that follows overtime the activation of Arf6 at the surface of lipid membranes. Using this unique screening assay, we isolated several compounds that affect Arf6 activation, among which the antibiotic chlortetracycline (CTC) appeared to be the most promising. In this report, we describe CTC in vitro biochemical characterization and show that it blocks both the Arf6-stimulated collective migration and cell invasion in a 3D collagen I gel of the invasive breast cancer cell line MDA-MB-231. Thus, CTC appears as a promising hit to target deadly metastatic dissemination and a powerful tool to unravel the molecular mechanisms of Arf6-mediated invasive processes.