Small Molecule Screening in Human Induced Pluripotent Stem Cell-derived Terminal Cell Types

A need for better clinical outcomes has heightened interest in the use of physiologically relevant human cells in the drug discovery process. Patient-specific human induced pluripotent stem cells may offer a relevant, robust, scalable, and cost-effective model of human disease physiology. Small molecule high throughput screening in human induced pluripotent stem cell-derived cells with the intent of identifying novel therapeutic compounds is starting to influence the drug discovery process; however, the use of these cells presents many high throughput screening development challenges. This technology has the potential to transform the way drug discovery is performed.     

Model-organism genomics in veterinary parasite drug-discovery

A recent article about genomic filtering highlights exciting new opportunities for antiparasitic drug discovery resulting from major advances in genomic technologies. In this article, we discuss several approaches in which model-organism genomics and proteomics could be applied to the identification and validation of novel targets for antiparasitic drug discovery in veterinary medicine.     

RNA as a small molecule druggable target

Small molecule drugs have readily been developed against many proteins in the human proteome, but RNA has remained an elusive target for drug discovery. Increasingly, we see that RNA, and to a lesser extent DNA elements, show a persistent tertiary structure responsible for many diverse and complex cellular functions. In this digest, we have summarized recent advances in screening approaches for RNA targets and outlined the discovery of novel, drug-like small molecules against RNA targets from various classes and therapeutic areas. The link of structure, function, and small-molecule Druggability validates now for the first time that RNA can be the targets of therapeutic agents.     

Drug discovery from natural products

Natural product compounds are the source of numerous therapeutic agents. Recent progress to discover drugs from natural product sources has resulted in compounds that are being developed to treat cancer, resistant bacteria and viruses and immunosuppressive disorders. Many of these compounds were discovered by applying recent advances in understanding the genetics of secondary metabolism in actinomycetes, exploring the marine environment and applying new screening technologies. In many instances, the discovery of a novel natural product serves as a tool to better understand targets and pathways in the disease process. This review describes recent progress in drug discovery from natural sources including several examples of compounds that inhibit novel drug targets.     

斑马鱼在新药发现中的应用

在过去20年里,斑马鱼已成为一种重要的模式脊椎动物,在发育、遗传、免疫、肿瘤和毒理等诸多研究领域中被广泛应用。近年来,斑马鱼作为活体模型越来越多地应用于某些生物学过程的药物筛选。通过斑马鱼初步筛选,在药物研发初期可确定化合物的生物学活性、毒性以及副作用等。最近的研究还发现,斑马鱼不仅用于新药筛选,还可用于药物结构的优化。本文重点介绍斑马鱼在新药发现中的应用。     

A system for performing high throughput assays of synaptic function

Unbiased, high-throughput screening has proven invaluable for dissecting complex biological processes. Application of this general approach to synaptic function would have a major impact on neuroscience research and drug discovery. However, existing techniques for studying synaptic physiology are labor intensive and low-throughput. Here, we describe a new high-throughput technology for performing assays of synaptic function in primary neurons cultured in microtiter plates. We show that this system can perform 96 synaptic vesicle cycling assays in parallel with high sensitivity, precision, uniformity, and reproducibility and can detect modulators of presynaptic function. By screening libraries of pharmacologically defined compounds on rat forebrain cultures, we have used this system to identify novel effects of compounds on specific aspects of presynaptic function. As a system for unbiased compound as well as genomic screening, this technology has significant applications for basic neuroscience research and for the discovery of novel, mechanism-based treatments for central nervous system disorders.     

Streamlining lead discovery by aligning in silico and high-throughput screening

Lead discovery in the pharmaceutical environment is largely an industrial-scale process in which it is typical to screen 1-5 million compounds in a matter of weeks using High Throughput Screening (HTS). This process is a very costly endeavor. Typically a HTS campaign of 1 million compounds will cost anywhere from $500000 to $1000000. There is consequently a great deal of pressure to maximize the return on investment by finding fast and more effective ways to screen. A panacea that has emerged over the past few years to help address this issue is in silico screening. In silico screening is now incorporated in all areas of lead discovery; from target identification and library design, to hit analysis and compound profiling. However, as lead discovery has evolved over the past few years, so has the role of in silico screening.     

现代生物学对药物发现的影响

随着后基因组时代的到来,药物发现研究领域不断涌现出一系列新思路、新技术、新方法,从而迅速推进药物发现的多元化发展。一方面,基因组学、蛋白质组学、转录组学、代谢组学、生物信息学、系统生物学等新兴学科的崛起与发展,为药物发现提供更为广泛而深刻的理论基础;另一方面,计算机辅助药物设计、高通量筛选、高内涵筛选、生物芯片、转基因和RNA干扰等高新技术的发展和完善,为药物发现提供了新的技术手段和有力工具,极大地拓宽了药物发现的途径。本文结合近年来现代生物学的研究进展,综述现代生物学对药物发现过程的影响。     

Mechanism-based screening: discovery of the next generation of anthelmintics depends upon more basic research

The therapeutic arsenal for the control of helminth infections contains only a few chemical classes. The development and spread of resistance has eroded the utility of most currently available anthelmintics, at least for some indications, and is a constant threat to further reduce the options for treatment. Discovery and development of novel anthelmintic templates is strategically necessary to preserve the economic and health advantages now gained through chemotherapy. As the costs of development escalate, the question of how best to discover new drugs becomes paramount. Although random screening in infected animals led to the discovery of all currently available anthelmintics, cost constraints and a perception of diminishing returns require new approaches. Taking a cue from drug discovery programmes for human illnesses, we suggest that mechanism-based screening will provide the next generation of anthelmintic molecules. Critical to success in this venture will be the exploitation of the Caenorhabditis elegans genome through bioinformatics and genetic technologies. The greatest obstacle to success in this endeavour is the paucity of information available about the molecular physiology of helminths, making the choice of a discovery target a risky proposition.     

Discovery of veterinary antiparasitic agents in the 21st Century: A view from industry

Discovery of antiparasitic agents is a challenging process, requiring discovery of molecules with the ability to kill parasites but not their hosts. Customer preference is for fewer doses and ease of application, but this is not always compatible with reduced withdrawal times, human food safety and/or user safety. This article describes some of the difficulties faced by researchers in the search for new antiparasitic agents, while highlighting advances that may improve the discovery process and the chance of success in discovering novel drugs.     

Familial Alzheimer’s disease modelling using induced pluripotent stem cell technology

Alzheimer’s disease(AD)is a progressive neurodegenerative disease in which patients exhibit gradual loss of memory that impairs their ability to learn or carry out daily tasks.Diagnosis of AD is difficult,particularly in early stages of the disease,and largely consists of cognitive assessments,with only one in four patients being correctly diagnosed.Development of novel therapeutics for the treatment of AD has proved to be a lengthy,costly and relatively unproductive process with attrition rates of90%.As a result,there are no cures for AD and few treatment options available for patients.Therefore,there is a pressing need for drug discovery platforms that can accurately and reproducibly mimic the AD phenotype and be amenable to high content screening applications.Here,we discuss the use of induced pluripotent stem cells(iPSCs),which can be derived from adult cells,as a method of recapitulation of AD phenotype in vitro.We assess their potential use in high content screening assays and the barriers that exist to realising their full potential in predictive efficacy,toxicology and disease modelling.At present,a number of limitations need to be addressed before the use of iPSC technology can be fully realised in AD therapeutic applications.However,whilst the use of AD-derived iPSCs in drug discovery remains a fledgling field,it is one with immense potential that is likely to reach fruition within the next few years.     

Informatics integration: the bedrock of NCE selection

The life-science domain has been discussing the merits of data integration for several years. Approximately five years ago, knowledge management promised to solve many of the bottlenecks of the drug discovery pipeline. It was envisioned that companies would purchase off-the-shelf software solutions or hire consultants or informaticians to solve their informatics problems. However, knowledge management has not delivered all that it promised. Better investment in integration is required to deliver a system that significantly reduces the time-to-market and R&D overheads, and increase the rate at which novel chemical entities (NCEs) progress through the pipeline. Such investments require strategic decisions that, if implemented successfully, deliver substantial benefits and act as the bedrock for NCE selection.     

虚拟筛选与新药发现

虚拟筛选是创新药物研究的新方法和新技术,近年来引起了研究机构和制药公司的高度重视,并且已经成为一种与高通量筛选互补的实用化工具,加入到了创新药物研究的工作流程(pipeline)中。本文介绍国际上虚拟筛选及其在创新药物发现中应用的研究进展,特别介绍了我国这方面研究的状况。     

Recent Advances in Drug Repositioning for the Discovery of New Anticancer Drugs

Drug repositioning (also referred to as drug repurposing), the process of finding new uses of existing drugs, has been gaining popularity in recent years. The availability of several established clinical drug libraries and rapid advances in disease biology, genomics and bioinformatics has accelerated the pace of both activity-based and in silico drug repositioning. Drug repositioning has attracted particular attention from the communities engaged in anticancer drug discovery due to the combination of great demand for new anticancer drugs and the availability of a wide variety of cell- and target-based screening assays. With the successful clinical introduction of a number of non-cancer drugs for cancer treatment, drug repositioning now became a powerful alternative strategy to discover and develop novel anticancer drug candidates from the existing drug space. In this review, recent successful examples of drug repositioning for anticancer drug discovery from non-cancer drugs will be discussed.     

秀丽隐杆线虫（Caenorhabditis elegans）在药物筛选中的应用

基于靶点的体外药物筛选操作相对简单,成本较低,但是由于药物在体内的作用并不仅仅取决于其与靶点的作用程度,吸收、分布、代谢、排泄特征和毒性均会对早期先导物能否进入临床使用产生极大的影响,因此,药物的体内筛选受到重视。本文重点综述了秀丽隐杆线虫（C.elegans）在抗衰老、抗感染药物筛选中的应用情况。秀丽隐杆线虫结构简单、易于培养和可实现高通量筛选,在未来的药物筛选中必将发挥更重要的作用。     

Minireview: Challenges of High Throughput Screening Against Cell Surface Receptors

Abstract

Excessive or inappropriate activation of cell surface receptors can mediate the development of disease. Receptors, therefore, are a focus for drug discovery activities. Empirical screening is important in the search for novel compounds acting at receptors. Technical developments and the application of molecular biology have facilitated access to receptors of interest and have provided efficient screening methods capable of very high throughput. Reliability in high throughput screening requires the use of appropriate methodology, good screen design and effective validation and quality control processes. Validation should aim to establish that the basic experimental design is sound. In developing software to handle high throughput screening data, a fundamental requirement is to provide performance monitoring and error trapping facilities. Additional requirements are automatic data capture from instruments, on-line data reduction and analysis and transfer of results to central databases. As data volumes increase through effective high throughput screening, conventional interrogation methods become less appropriate and are being augmented by newer computing techniques referred to as knowledge mapping or database mining. Targeting cell surface receptors has been very successful as an approach to drug discovery. If the challenges of high throughput empirical screening are addressed effectively, cell surface receptors will provide new opportunities for improved therapy in the coming years.     

基于机器学习的药物-靶标相互作用预测*

近年来,随着计算机硬件、软件工具和数据丰度的不断突破,以机器学习为代表的人工智能技术在生物、基础医学和药学等领域的应用不断拓展和融合,极大地推动了这些领域的发展,尤其是药物研发领域的变革。其中,药物-靶标相互作用(drug-target interactions, DTI)的识别是药物研发领域中的重要难题和人工智能技术交叉融合的热门方向,研究人员在DTI预测方面做了大量的工作,构建了许多重要的数据库,开发或拓展了各类机器学习算法和工具软件。对基于机器学习的DTI预测的基本流程进行了介绍,并对利用机器学习预测DTI的研究进行了回顾,同时对不同的机器学习方法运用于DTI预测的优缺点进行了简单总结,以期对开发更加有效的预测算法和DTI预测的发展提供帮助。     

RGD三肽的潜在作用靶标预测与计算机模拟分析

化学基因组技术是药物作用靶标确认、药物分子在通路中的作用的确证等方面有重要应用,可为新药研发和老药新用提供理论依据,并可降低药物发现中的高额成本.精氨酸-甘氨酸-天冬氨酸(RGD)三肽被证明是与细胞粘附受体特异性结合的特征序列,在生理学上扮演者重要角色.本研究利用化学基因组学中的其中一种方法即基于反向对接和药效团反向匹配搜索技术来研究RGD三肽的潜在作用靶标,并进行计算机模拟分析.反向匹配搜索结果发现计算得到的关键性靶标及其涉及的相关疾病与实验报道的RGD的药理活性相吻合,包括具有抗凝血、抗肿瘤作用,与肾及心血管作用有关等,而且还发现RGD可能是一个潜在的神经氨酸酶的抑制剂.     

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.     

天然活性成分作用靶点识别及确证方法的研究进展

药物靶标的发现和验证是新药研发的关键环节,对新药创制具有源头创新意义。天然产物是新药创制的重要来源,识别其作用靶点不仅为临床预防治疗提供可能新策略,也为进一步阐释中草药及其复方的作用特点及分子机制提供参考依据。随着生命科学和信息学的发展,药物靶点的识别及确证方法不断涌现,生物信息学、网络药理学、蛋白质组学、亲和色谱、药物亲和稳定性、芯片技术、基因敲除技术、RNA干扰等技术的广泛应用,越来越多的天然活性成分的靶点得以识别和验证。因此,本文对近五年来天然活性成分作用靶点识别及确证方法做一简要综述,以供参考。