An overview of drug screening using primary and embryonic stem cells

Cellular technologies are widely used in drug discovery to treat human diseases. Most studies involve the expression of recombinant targets in immortalized cells and measure drug interactions using simple, quantifiable responses. Such cells are also amenable to high throughput screening (HTS) methods. However, the cell phenotype employed in HTS is often determined by the assay technology available, rather than the physiological relevance of the cell background. They are, therefore, suboptimal surrogates for cells that accurately reflect human diseases. Consequently, there is growing interest in adopting primary and embryonic stem cells in drug discovery. Primary cells are already used in secondary screening assays in conjunction with confocal imaging techniques, as well as in target validation studies employing, for example, gene silencing approaches. Stem cells can be grown in unlimited quantities and can be derived from transgenic animals engineered to express disease causing proteins better coupling the molecular target with function in vivo. Human stem cells also offer unique opportunities for drug discovery in that they can be directed to specific phenotypes thus providing a framework to identify tissue-selective agents. Organizing stem cells into networks resembling those in native tissues, potentially returns drug discovery back to the highly successful pharmacological methods of the past, in which organ and tissue based systems were used, but with the advantage that they can be utilized using modern HTS technologies. This emerging area will lead to discovery of compounds whose effect in vivo is more predictable thereby increasing the efficiency of drugs that ameliorate human disease.     

The use of immortalized cell lines in GPCR screening: the good, bad and ugly

For most membrane-bound molecular targets, including G protein linked receptors (GPCRs), the optimal approach in drug discovery involves the use of cell based high throughput screening (HTS) technologies to identify compounds that modulate target activity. Most GPCRs have been cloned and can therefore be routinely expressed in immortalized cell lines. These cells can be easily and rapidly grown in unlimited quantities making them ideal for use in current HTS technologies. A significant advantage of this approach is that immortalized recombinant cells provide a homogenous background for expression of the target which greatly facilitates consistency in screening, thus allowing for a better understanding of the mechanism of action of the interacting compound or drug. Nonetheless, it is now evident that numerous disparities exist between the physiological environment of screening systems using recombinant cells and natural tissues. This has lead to a problem in the validity of the pharmacological data obtained using immortalized cells in as much as such cells do not always reflect the desired clinical efficacy and safety of the compounds under examination. This brief review discusses these issues and describes how they influence the discovery of drugs using modern HTS.     

中草药活性成分的高通量筛选技术研究进展

随着高通量筛选技术的不断发展,该技术已经成为发现新药物的重要途径之一。高通量筛选技术已大量应用于筛选药物活性成分的领域中,但是其中大部分为从化合物库中筛选活性成分,仅有十几篇文献应用于中药活性成分的筛选,而中国传统中草药却是探索和发展新药物的丰富来源。本文通过综述国内外2008年到2017年的相关文献,阐述了分子和细胞水平上的高通量筛选技术在中草药活性成分的筛选及其应用进展,为今后中草药新药研发提供参考。     

Discovery of novel targets with high throughput RNA interference screening

High throughput technologies have the potential to affect all aspects of drug discovery. Considerable attention is paid to high throughput screening (HTS) for small molecule lead compounds. The identification of the targets that enter those HTS campaigns had been driven by basic research until the advent of genomics level data acquisition such as sequencing and gene expression microarrays. Large-scale profiling approaches (e.g., microarrays, protein analysis by mass spectrometry, and metabolite profiling) can yield vast quantities of data and important information. However, these approaches usually require painstaking in silico analysis and low-throughput basic wet-lab research to identify the function of a gene and validate the gene product as a potential therapeutic drug target. Functional genomic screening offers the promise of direct identification of genes involved in phenotypes of interest. In this review, RNA interference (RNAi) mediated loss-of-function screens will be discussed and as well as their utility in target identification. Some of the genes identified in these screens should produce similar phenotypes if their gene products are antagonized with drugs. With a carefully chosen phenotype, an understanding of the biology of RNAi and appreciation of the limitations of RNAi screening, there is great potential for the discovery of new drug targets.     

Screening of enzyme inhibitors from traditional Chinese medicine

Traditional Chinese medicine (TCM) has been used for more than 4000 years. By comparison with large combinatorial chemistry libraries and natural products of the West for high-throughput screening (HTS) of new drugs discovery, an advantage of TCM is that the preparation has clear efficacies on the therapy of some diseases. Although the effective components are not clear, the clear efficacies of TCM have been identified for long time practice, Therefore, TCMs should be valuable lead compound libraries with a definite therapy efficacy from the viewpoint of HTS. Nevertheless, current HTS technologies are not easily adapted to investigate TCMs because they are designed for screening a relatively pure known chemical at a known concentration. In contrast, TCMs are mixtures of unknown compounds in unknown concentrations that may differ markedly between samples from different plants. This article reviews the current and future researches on the enzyme inhibitors screening from TCM.     

Chemogenomics and parasitology: small molecules and cell-based assays to study infectious processes

Infectious diseases caused by protozoan parasites--malaria, sleeping sickness, leishmaniasis, Chagas' disease, toxoplasmosis--remain chronic problems for humanity. We lack vaccines and have limited drug options effective against protozoa. Research into anti-protozoan drugs has accelerated with improved in vitro cultivation methods, enhanced genetic accessibility, completed genome sequences for key protozoa, and increased prominence of protozoan diseases on the agendas of well-resourced public figures and foundations. Concurrent advances in high-throughput screening (HTS) technologies and availability of diverse small molecule libraries offer the promise of accelerated discovery of new drug targets and new drugs that will reduce disease burdens imposed on humanity by parasitic protozoa. We provide a status report on HTS technologies in hand and cell-based assays under development for biological investigations and drug discovery directed toward the three best-characterized parasitic protozoa: Trypanosoma brucei, Plasmodium falciparum, and Toxoplasma gondii. We emphasize cell growth assays and new insights into parasite cell biology speeding development of better cell-based assays, useful in primary screens for anti-protozoan drug leads and secondary screens to decipher mechanisms of action of leads identified in growth assays. Small molecules that interfere with specific aspects of protozoan biology, identified in such screens, will be valuable tools for dissecting parasite cell biology and developing anti-protozoan drugs. We discuss potential impacts on drug development of new consortia among academic, corporate, and public partners committed to discovery of new, effective anti-protozoan drugs.     

药物发现中常用化合物库特征描述与对比分析

随着计算技术的发展和分子模拟软件的日趋成熟, 虚拟筛选已经在药物发现过程中发挥着越来越重要的作用. 在虚拟筛选过程中, 所使用化合物库的质量对先导化合物发现的成功率起着至关重要的作用. 本文通过对已知药物库、天然产物库、中药原植物化学成分库、筛选常用商业化合物库以及研究者所在实验室建立的化合物库的分析比较, 从化合物库的分子多样性、化学空间和分子骨架等多个方面提取并对比每一种化合物库的特征, 发现了已知药物库与中药原植物化学成分库的特征相似性, 揭示了中药原植物化学成分库作为筛选库的类药性优势, 并且深化了对几种筛选用化合物库特征的认识和理解.     

Modern drug discovery technologies: opportunities and challenges in lead discovery

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.     

临近闪烁分析法在高通量筛选中的应用

起源于放射性免疫分析的临近闪烁分析法(scintillation proximity assay,SPA)是一种均相、灵敏、快速和简便的基于闪烁载体的分析平台。该平台可用于筛选药物靶点的先导化合物和研究其生理过程。由于无需分离,易于固定药物靶点和检测其活性,SPA成为一种重要的高通量筛选方法。由于放射性标记分子和亲和标签分子的多样化和商业化、以及液闪计数器和液相操作等技术的发展,SPA已经广泛用于受体结合、高通量药物筛选、酶分析、放射性免疫分析、蛋白质-蛋白质相互作用和细胞水平分析等方面。本文阐述了SPA原理,讨论了其关键技术(包括闪烁载体、液闪计数器和放射性标记分子),分析了其评价体系;同时简述了SPA分析的发展, 并介绍了其在高通量筛选中的应用实例, 归纳了存在的问题,给出了未来的发展趋势。目前,基于SPA和荧光分析方法已成为高通量药物筛选的热点研究领域, 这些筛选技术的革新必然提升我们对细胞体系生物学的全面理解和促进先导化合物筛选过程的显著进步。     

Integration of NMR and high-throughput screening

NMR-based screening has become a powerful method for the identification and analysis of low-molecular weight organic compounds that bind to protein targets and can be utilized in drug discovery programs. In particular, heteronuclear NMR-based screening can yield information about both the affinity and binding location of potential lead compounds. In addition, heteronuclear NMR-based screening has wide applications in complementing and facilitating conventional high-throughout screening programs. This article will describe several strategies for the integration of NMR-based screening and high-throughput screening. The marriage of these two techniques promises to be of tremendous benefit in the triage of hits that come from HTS, and can aid the medicinal chemist in the identification of quality leads that have high potential for further optimization.     

In vitro high throughput screening of compounds for favorable metabolic properties in drug discovery

Drug metabolism can have profound effects on the pharmacological and toxicological profile of therapeutic agents. In the pharmaceutical industry, many in vitro techniques are in place or under development to screen and optimize compounds for favorable metabolic properties in the drug discovery phase. These in vitro technologies are meant to address important issues such as: (1) is the compound a potent inhibitor of drug metabolising enzymes (DMEs)? (2) does the compound induce the expression of DMEs? (3) how labile is the compound to metabolic degradation? (4) which specific enzyme(s) is responsible for the compound's biotransformation? and (5) to which metabolites is the compound metabolized? Answers to these questions provide a basis for judging whether a compound is likely to have acceptable pharmacokinetic properties in vivo. To address these issues on the increasing number of compounds inundating the drug discovery programs, high throughput assays are essential. A combination of biochemical advances in the understanding of the function and regulation of DMEs (in particular, cytochromes P450, CYPs) and automated analytical technologies are revolutionizing drug metabolism research. Automated LC-MS based metabolic stability, fluorescence, radiometric and LC-MS based CYP inhibition assays are now in routine use. Automatible models for studying CYP induction based on enzyme activity, quantitative RT-PCR and reporter gene systems are being developed. We will review the utility and limitations of these HTS approaches and highlight on-going developments and emerging technologies to answer metabolism questions at the different stages of the drug discovery process.     

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

Medicinal plants have been explored therapeutically in traditional medicines and are a valuable source for drug discovery. Insufficient knowledge about the molecular mechanism of these medicinal plants limits the scope of their application and hinders the effort to design new drugs using the therapeutic principles of herbal medicines. This problem can be partially alleviated if efficient methods for rapid identification of protein targets of herbal ingredients can be introduced. Efforts have been directed at developing efficient computer methods for facilitating target identification. Various methods being explored or under investigation are reviewed here. So far, one computer method, INVDOCK, has been specifically used for automated drug target identification. Its usefulness in the identification of therapeutic targets of medicinal herbal ingredients as well as synthetic chemicals is reviewed. The majority of INVDOCK identified therapeutic targets of several well-known medicinal herbal ingredients have been found to be confirmed or implicated by experiments, which suggests the potential of in silico methods in facilitating the study of molecular mechanism of medicinal plants.     

High-content analysis of kinase activity in cells

High-content analysis (HCA) is a term used to describe techniques involving multiplexed analysis of fluorescent markers to measure multiple cellular responses to biological stimuli or drug treatment. HCA is usually based on automated microscopy or related technologies, and its value lies in providing multiparametric information on single cells within a population. During the last decade, several HCA approaches have been developed and applied to assess cellular mechanism of action of pharmacologically relevant compounds identified through biochemical screening or similar in vitro methods. With automation and instrument development, these approaches have evolved to the extent that the technique is now routinely used in screening applications, including primary HTS on compound collections. Here, we review the field and discuss in particular the application of HCA to the discovery of small molecule inhibitors targeting kinases which are implicated in Oncology.     

Optical chemical biosensors for high-throughput screening of drugs

Optical biosensors have been commercially available since the early 1990s, and have been used extensively in many areas of research in the life sciences. Optical biosensors developed for drug analysis generally exploit the high selectivity of the antigen-antibody and drug-protein interaction. Optical biosensors can be made based on optical diffraction or electro-chemiluminescence. High-throughput screening, (HTS) which includes automated preparation of a large number of samples and then screening of their properties in multi-well plates, improves the efficiency of research in many scientific areas, e.g., catalyst screening, food processing, chemical synthesis, drug discovery, absorption, distribution, metabolism, and excretion and toxicological and cell based screening. The three most common detection techniques used in HTS are UV-VIS absorbance, fluorescence and luminescence. In this review, we summarize some recent trends and developments in the construction of optical chemical biosensors used in high-throughput screening of drugs. Also, we have included environmental, biological and other medical applications of biosensors.     

超高效液相色谱-四极杆-飞行时间质谱法快速筛查和确证渔药中86种非法添加化学品

建立了超高效液相色谱-四极杆-飞行时间质谱法快速筛查与确证渔药中86种非法添加禁限用药物的方法。渔药以80%(v/v)乙腈水溶液进行提取,通过稀释降低基质效应,采用ACQUITY PREMIER HSS T3色谱柱进行分离,以甲醇和0.1%甲酸水溶液作为流动相进行梯度洗脱,采用电喷雾双喷离子源(Dual AJS ESI)正离子模式分析检测。建立了86种药物的一级精确质量数据库和二级碎片质谱库。在全扫描采集模式下,以化合物的色谱保留时间、精确质量数、同位素分布和同位素丰度比定性;在Target MS/MS采集模式下,通过二级碎片离子的匹配进一步确证化合物,以准分子离子峰的峰面积定量,实现渔药样品中多目标药物的快速定性定量分析。86种药物在各自的线性范围内均呈现良好的线性关系,相关系数均大于0.99,中草药制剂和抗生素粉剂的定量限(LOQ)范围分别为1~15 mg/kg和5~75 mg/kg,添加回收率范围为76.8%~112.1%,相对标准偏差(RSD, n=3)小于11.7%。该方法快速、简便、准确、灵敏,适用于不同种类渔药中禁限用非法添加药物的高通量筛查。将该方法应用于浙江省渔用投入品质量安全监督抽检项目中,共筛查60个样品,其中8种中草药制剂筛查出说明书中未明确标明的药物成分,1种抗生素粉剂未检出有效成分。该研究为渔药的质量安全监控提供了有效的技术手段。     

Integration of virtual and high throughput screening in lead discovery settings

In the last decade mass screening strategies became the main source of leads in drug discovery settings. Although high throughput (HTS) and virtual screening (VS) realize the same concept the different nature of these lead discovery strategies (experimental vs theoretical) results that they are typically applied separately. The majority of drug leads are still identified by hit-to-lead optimization of screening hits. Structural information on the target as well as on bound ligands, however, make structure-based and ligand-based virtual screening available for the identification of alternative chemical starting points. Although, the two techniques have rarely been used together on the same target, here we review the existing prominent studies on their true integration. Various approaches have been shown to apply the combination of HTS and VS and to better use them in lead generation. Although several attempts on their integration have only been considered at a conceptual level, there are numerous applications underlining its relevance that early-stage pharmaceutical drug research could benefit from a combined approach.     

Machine Learning Methods in Drug Discovery

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high through-put computational analysis of databases used for both lead and target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. The use of these virtual screening and encompassing online information has also been highlighted in developing lead synthesis pathways. In this review, machine learning and deep learning algorithms utilized in drug discovery and associated techniques will be discussed. The applications that produce promising results and methods will be reviewed.     

局部直线筛选法的建立及其改进研究

目前针对中药掺杂样品的检测手段有很多种,光谱法由于其快速、简便、高通量、经济等多个指标上的优势,发展成为现场快速筛选方法的可能性较大.本课题组近期的研究成果—局部直线筛选法(LSLS),仅利用待测中药与化学药物的各一张红外光谱,通过提取差谱计算过程中的特征吸收峰信息的变化规律,进行掺杂物的判定.其后的M-LSLS方法在此基础上,做了插值、二阶导数等预处理的改进.最近的W-LSLS法结合前两种方法的优点,引入峰强-峰形加权、峰位校正等手段,实现了较好的判别,灵敏度、专属性和准确性均有明显提高.本类方法适用于大量中药样品是否掺杂化学药物的初筛,可为基层药检提供一种新的支撑技术.     

Recent Analytical Method for Detection of Chemical Adulterants in Herbal Medicine

Herbal medicine has become popular in recent years as an alternative medicine. The problem arises when herbal medicines contain an undeclared synthetic drug that is illegally added, since it is a natural product that does not contain any chemical drugs due to the potential cause of harmful effects. Supervision of herbal medicines is important to ensure that these herbal medicines are still safe to use. Thus, developing a reliable analytical technique for the determination of adulterated drugs in herbal medicine is gaining interest. This review aims to provide a recent analytical method that has been used within the past 5 years (2016–2021) for the determination of chemical adulterants in herbal medicine.     

Strategic pooling of compounds for high-throughput screening.

Bringing new medicines to the market depends on the rapid discovery of new and effective drugs, often initiated through the biological testing of many thousands of compounds in high-throughput screening (HTS). Mixing compounds together into pools for screening is one way to accelerate this process and reduce costs. This paper contains both theoretical and experimental data which suggest that careful selection of compounds to be pooled together is necessary in order to reduce the risk of reactivity between compounds within the pools.