Drug discovery and development for neglected parasitic diseases

Diseases caused by tropical parasites affect hundreds of millions of people worldwide but have been largely neglected for drug development because they affect poor people in poor regions of the world. Most of the current drugs used to treat these diseases are decades old and have many limitations, including the emergence of drug resistance. This review will summarize efforts to reinvigorate the drug development pipeline for these diseases, which is driven in large part by support from major philanthropies. The organisms responsible for these diseases have a fascinating biology, and many potential biochemical targets are now apparent. These neglected diseases present unique challenges to drug development that are being addressed by new consortia of scientists from academia and industry.     

In silico identification of common putative drug targets in <Emphasis Type="Italic">Leptospira interrogans</Emphasis>

Infectious diseases are the leading causes of death worldwide. Hence, there is a need to develop new antimicrobial agents. Traditional method of drug discovery is time consuming and yields a few drug targets with little intracellular information for guiding target selection. Thus, focus in drug development has been shifted to computational comparative genomics for identifying novel drug targets. Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. Availability of L. interrogans serovars and human genome sequences facilitated to search for novel drug targets using bioinformatics tools. The genome sequence of L. interrogans serovar Copenhageni has 5,124 genes while that of serovar Lai has 4,727 genes. Through subtractive genomic approach 218 genes in serovar Copenhageni and 158 genes in serovar Lai have been identified as putative drug targets. Comparative genomic approach had revealed that 88 drug targets were common to both the serovars. Pathway analysis using the Kyoto Encyclopaedia of Genes and Genomes revealed that 66 targets are enzymes and 22 are non-enzymes. Sixty two common drug targets were predicted to be localized in cytoplasm and 16 were surface proteins. The identified potential drug targets form a platform for further investigation in discovery of novel therapeutic compounds against Leptospira.     

Functional genomics: identifying drug targets for parasitic diseases

The genomic sequences of parasitic diseases are rapidly becoming available and, recently, the full sequence of Plasmodium falciparum has been published. Much has been promised from this genomic revolution including the identification of new drug targets and novel chemotherapeutic treatments for the control of parasitic diseases. The challenge to use this information efficiently will require functional genomics tools such as bioinformatics, microarrays, proteomics and chemical genomics to identify potential drug targets, and to allow the development of optimized lead compounds. The information generated from these tools will provide a crucial link from genomic analysis to drug discovery.     

Mitochondriotropic Liposomes

Mitochondrial dysfunction contributes to a large variety of human disorders, ranging from neurodegenerative and neuromuscular diseases, obesity, and diabetes to ischemia-reperfusion injury and cancer. Increasing pharmacological efforts toward therapeutic interventions have been made leading to the emergence of “Mitochondrial Medicine” as a new field of biomedical research. The identification of molecular mitochondrial drug targets in combination with the development of methods for selectively delivering biologically active molecules to the site of mitochondria will eventually launch a multitude of new therapies for the treatment of mitochondria-related diseases, which are based either on the selective protection, repair, or eradication of cells. Yet, while tremendous efforts are being undertaken to identify new mitochondrial drugs and drug targets, the development of mitochondria-specific drug carrier systems is lagging behind. To ensure a high efficiency of current and future mitochondrial therapeutics, delivery systems need to be developed, which are able to selectively transport biologically active molecules to and into mitochondria within living human cells. In this study we present the first data demonstrating that conventional liposomes can be rendered mitochondria-specific via the attachment of known mitochondriotropic residues to the liposomal surface.     

Mitochondriotropic liposomes

Mitochondrial dysfunction contributes to a large variety of human disorders, ranging from neurodegenerative and neuromuscular diseases, obesity, and diabetes to ischemia-reperfusion injury and cancer. Increasing pharmacological efforts toward therapeutic interventions have been made leading to the emergence of "Mitochondrial Medicine" as a new field of biomedical research. The identification of molecular mitochondrial drug targets in combination with the development of methods for selectively delivering biologically active molecules to the site of mitochondria will eventually launch a multitude of new therapies for the treatment of mitochondria-related diseases, which are based either on the selective protection, repair, or eradication of cells. Yet, while tremendous efforts are being undertaken to identify new mitochondrial drugs and drug targets, the development of mitochondria-specific drug carrier systems is lagging behind. To ensure a high efficiency of current and future mitochondrial therapeutics, delivery systems need to be developed, which are able to selectively transport biologically active molecules to and into mitochondria within living human cells. In this study we present the first data demonstrating that conventional liposomes can be rendered mitochondria-specific via the attachment of known mitochondriotropic residues to the liposomal surface.     

Will genetics really revolutionize the drug discovery process?

Genetics has played only a modest role in drug discovery, but new technologies will radically change this. Whole genome sequencing will identify new drug discovery targets, and emerging methods for the determination of gene function will increase the ability to select robust targets. Detection of single nucleotide polymorphisms and common polymorphisms will enhance the investigation of polygenic diseases and the use of genetics in drug development. Oligonucleotide arraying technologies will allow analysis of gene expression patterns in novel ways.     

Multicomponent phytotherapeutic approach gaining momentum: Is the “one drug to fit all” model breaking down?

Natural product based drugs constitute a substantial proportion of the pharmaceutical market particularly in the therapeutic areas of infectious diseases and oncology. The primary focus of any drug development program so far has been to design selective ligands (drugs) that act on single selective disease targets to obtain highly efficacious and safe drugs with minimal side effects. Although this approach has been successful for many diseases, yet there is a significant decline in the number of new drug candidates being introduced into clinical practice over the past few decades. This serious innovation deficit that the pharmaceutical industries are facing is due primarily to the post-marketing failures of blockbuster drugs. Many analysts believe that the current capital-intensive model-“the one drug to fit all” approach will be unsustainable in future and that a new “less investment, more drugs” model is necessary for further scientific growth. It is now well established that many diseases are multi-factorial in nature and that cellular pathways operate more like webs than highways. There are often multiple ways or alternate routes that may be switched on in response to the inhibition of a specific target. This gives rise to the resistant cells or resistant organisms under the specific pressure of a targeted agent, resulting in drug resistance and clinical failure of the drug. Drugs designed to act against individual molecular targets cannot usually combat multifactorial diseases like cancer, or diseases that affect multiple tissues or cell types such as diabetes and immunoinflammatory diseases. Combination drugs that affect multiple targets simultaneously are better at controlling complex disease systems and are less prone to drug resistance. This multicomponent therapy forms the basis of phytotherapy or phytomedicine where the holistic therapeutic effect arises as a result of complex positive (synergistic) or negative (antagonistic) interactions between different components of a cocktail. In this approach, multicomponent therapy is considered to be advantageous for multifactorial diseases, instead of a “magic bullet” the metaphor of a “herbal shotgun” might better explain the state of affairs. The different interactions between various components might involve the protection of an active substance from decomposition by enzymes, modification of transport across membranes of cells or organelles, evasion of multidrug resistance mechanisms among others.     

Proteomics and the blood–brain barrier: how recent findings help drug development

The drug discovery and development processes are divided into different stages separated by milestones to indicate that significant progress has been made and that certain criteria for target validation, hits, leads and candidate drugs have been met. Proteomics is a promising approach for the identification of protein targets and biochemical pathways involved in disease process and thus plays an important role in several stages of the drug development. The blood–brain barrier is considered as a major bottleneck when trying to target new compounds to treat neurodegenerative diseases. Based on the survey of recent findings and with a projection on expected improvements, this report attempt to address how proteomics participates in drug development.     

基于组合药物网络的复杂疾病药物组合模式研究

人体作为一个复杂的功能系统。疾病的发生和发展,尤其是复杂疾病,其病理过程往往涉及多环节、多系统。单一药物难以满足复杂疾病的治疗要求,组合药物成为未来药物发展的新趋势。本文在构建组合药物网络的基础上进行MCODE算法聚类,得到33个独立且内部联系紧密的药物模块。其中26组药物模块用于治疗单一复杂疾病。通过详细分析癌症、疼痛、银屑病、细菌感染、类风湿性关节炎、化疗呕吐这六种复杂疾病,归纳总结出这六种疾病的药物组合模式,从而提出复杂疾病多角度的治疗策略。     

Network medicine

To more effectively target complex diseases like cancer, diabetes and schizophrenia, we may need to rethink our strategies for drug development and the selection of molecular targets for pharmacological treatments. Here, we discuss the potential use of protein signaling networks as the targets for new therapeutic intervention. We argue that by targeting the architecture of aberrant signaling networks associated with cancer and other diseases new therapeutic strategies can be implemented. Transforming medicine into a network driven endeavour will require quantitative measurements of cell signaling processes; we will describe how this may be performed and combined with new algorithms to predict the trajectories taken by a cellular system either in time or through disease states. We term this approach, network medicine.     

Modern approaches to drug discovery and design: setting the scene

The raison d'ítre for the drug discovery and development process is to provide safe and effective treatments for diseases. Bringing a new drug to market, however, is a time-consuming and expensive process and it remains an imperative for drug companies that they identify ways in which they can accelerate the identification of potential targets and their screening and development in order to maintain a competitive edge. Successful drug discovery efforts include biochemical, biophysical, genetic and immunological approaches, targeting such processes as signal transduction, cell cycle control, apoptosis, gene regulation and metastasis. As the number of these biological targets increases, reliance on bioinformatics and chemoinformatics to improve decision making, by identifying characteristics of successful drugs and sharing knowledge gained within the scientific community, has become a burgeoning area in the post-genomic era of drug discovery.     

PREDICT: a method for inferring novel drug indications with application to personalized medicine

Inferring potential drug indications, for either novel or approved drugs, is a key step in drug development. Previous computational methods in this domain have focused on either drug repositioning or matching drug and disease gene expression profiles. Here, we present a novel method for the large‐scale prediction of drug indications (PREDICT) that can handle both approved drugs and novel molecules. Our method is based on the observation that similar drugs are indicated for similar diseases, and utilizes multiple drug–drug and disease–disease similarity measures for the prediction task. On cross‐validation, it obtains high specificity and sensitivity (AUC=0.9) in predicting drug indications, surpassing existing methods. We validate our predictions by their overlap with drug indications that are currently under clinical trials, and by their agreement with tissue‐specific expression information on the drug targets. We further show that disease‐specific genetic signatures can be used to accurately predict drug indications for new diseases (AUC=0.92). This lays the computational foundation for future personalized drug treatments, where gene expression signatures from individual patients would replace the disease‐specific signatures.     

Liposomes and liposome-like vesicles for drug and DNA delivery to mitochondria

Mitochondrial research is presently one of the fastest growing disciplines in biomedicine. Since the early 1990s, it has become increasingly evident that mitochondrial dysfunction contributes to a large variety of human disorders, ranging from neurodegenerative and neuromuscular diseases, obesity, and diabetes to ischemia-reperfusion injury and cancer. Most remarkably, mitochondria, the "power house" of the cell, have also become accepted as the "motor of cell death" reflecting their recognized key role during apoptosis. Based on these recent exciting developments in mitochondrial research, increasing pharmacological efforts have been made leading to the emergence of "Mitochondrial Medicine" as a whole new field of biomedical research. The identification of molecular mitochondrial drug targets in combination with the development of methods for selectively delivering biologically active molecules to the site of mitochondria will eventually launch a multitude of new therapies for the treatment of mitochondria-related diseases, which are based either on the selective protection, repair, or eradication of cells. Yet, while tremendous efforts are being undertaken to identify new mitochondrial drugs and drug targets, the development of mitochondria-specific drug carrier systems is lagging behind. To ensure a high efficiency of current and future mitochondrial therapeutics, colloidal vectors, i.e., delivery systems, need to be developed able to selectively transport biologically active molecules to and into mitochondria within living human cells. Here we review ongoing efforts in our laboratory directed toward the development of different phospholipid- and non-phospholipid-based mitochondriotropic drug carrier systems.     

Liposomes and Liposome-like Vesicles for Drug and DNA Delivery to Mitochondria

Mitochondrial research is presently one of the fastest growing disciplines in biomedicine. Since the early 1990s, it has become increasingly evident that mitochondrial dysfunction contributes to a large variety of human disorders, ranging from neurodegenerative and neuromuscular diseases, obesity, and diabetes to ischemia-reperfusion injury and cancer. Most remarkably, mitochondria, the “power house” of the cell, have also become accepted as the “motor of cell death” reflecting their recognized key role during apoptosis. Based on these recent exciting developments in mitochondrial research, increasing pharmacological efforts have been made leading to the emergence of “Mitochondrial Medicine” as a whole new field of biomedical research. The identification of molecular mitochondrial drug targets in combination with the development of methods for selectively delivering biologically active molecules to the site of mitochondria will eventually launch a multitude of new therapies for the treatment of mitochondria-related diseases, which are based either on the selective protection, repair, or eradication of cells. Yet, while tremendous efforts are being undertaken to identify new mitochondrial drugs and drug targets, the development of mitochondria-specific drug carrier systems is lagging behind. To ensure a high efficiency of current and future mitochondrial therapeutics, colloidal vectors, i.e., delivery systems, need to be developed able to selectively transport biologically active molecules to and into mitochondria within living human cells. Here we review ongoing efforts in our laboratory directed toward the development of different phospholipid- and non-phospholipid-based mitochondriotropic drug carrier systems.     

Genomics, systems biology and drug development for infectious diseases

Although a variety of drugs are available for many infectious diseases that predominantly affect the developing world reasons remain for continuing to search for new chemotherapeutics. First, the development of microbial resistance has made some of the most effective and inexpensive drug regimes unreliable and dangerous to use on severely ill patients. Second, many existing antimicrobial drugs show toxicity or are too expensive for countries where the per capita income is in the order of hundreds of dollars per year. In recognition of this, new publicly and privately financed drug discovery efforts have been established to identify and develop new therapies for diseases such as tuberculosis, malaria and AIDS. This in turn, has intensified the need for tools to facilitate drug identification for those microbes whose molecular biology is poorly understood, or which are difficult to grow in the laboratory. While much has been written about how functional genomics can be used to find novel protein targets for chemotherapeutics this review will concentrate on how genome-wide, systems biology approaches may be used following whole organism, cell-based screening to understand the mechanism of drug action or to identify biological targets of small molecules. Here we focus on protozoan parasites, however, many of the approaches can be applied to pathogenic bacteria or parasitic helminths, insects or disease-causing fungi.     

基于SVM 的药物靶点预测方法及其应用

目的:基于已知药物靶点和潜在药物靶点蛋白的一级结构相似性,结合SVM技术研究新的有效的药物靶点预测方法。方法:构造训练样本集,提取蛋白质序列的一级结构特征,进行数据预处理,选择最优核函数,优化参数并进行特征选择,训练最优预测模型,检验模型的预测效果。以G蛋白偶联受体家族的蛋白质为预测集,应用建立的最优分类模型对其进行潜在药物靶点挖掘。结果:基于SVM所建立的最优分类模型预测的平均准确率为81.03%。应用最优分类器对构造的G蛋白预测集进行预测,结果发现预测排位在前20的蛋白质中有多个与疾病相关。特别的,其中有两个G蛋白在治疗靶点数据库(TTD)中显示已作为临床试验的药物靶点。结论:基于SVM和蛋白质序列特征的药物靶点预测方法是有效的,应用该方法预测出的潜在药物靶点能够为发现新的药靶提供参考。     

Predict potential drug targets from the ion channel proteins based on SVM

The identification of molecular targets is a critical step in the drug discovery and development process. Ion channel proteins represent highly attractive drug targets implicated in a diverse range of disorders, in particular in the cardiovascular and central nervous systems. Due to the limits of experimental technique and low-throughput nature of patch-clamp electrophysiology, they remain a target class waiting to be exploited. In our study, we combined three types of protein features, primary sequence, secondary structure and subcellular localization to predict potential drug targets from ion channel proteins applying classical support vector machine (SVM) method. In addition, our prediction comprised two stages. In stage 1, we predicted ion channel target proteins based on whole-genome target protein characteristics. Firstly, we performed feature selection by Mann-Whitney U test, then made predictions to identify potential ion channel targets by SVM and designed a new evaluating indicator Q to prioritize results. In stage 2, we made a prediction based on known ion channel target protein characteristics. Genetic algorithm was used to select features and SVM was used to predict ion channel targets. Then, we integrated results of two stages, and found that five ion channel proteins appeared in both prediction results including CGMP-gated cation channel beta subunit and Gamma-aminobutyric acid receptor subunit alpha-5, etc., and four of which were relative to some nerve diseases. It suggests that these five proteins are potential targets for drug discovery and our prediction strategies are effective.     

Current strategies for identifying and validating targets for new treatment-shortening drugs for TB

There is an urgent need for new drugs to treat tuberculosis. During the last forty years the only drugs to have been developed are variations on existing ones, but new drug candidates must offer improvements over existing agents. In particular, we require new drugs having novel mechanisms of action that are active against drug-resistant strains and also kill persistent bacilli, thus shortening the length of chemotherapy. Recent advances in our understanding of the biology of Mycobacterium tuberculosis, in particularly the availability of the genome sequence coupled with development of new genetic tools, have greatly contributed to the discovery of potential drug targets for new antituberculars. However, although many potential new drug targets have been identified, greater effort is required in target validation to show properly that they are essential for bacterial growth and survival. In this review, the current drug development pipeline and the strategies employed to identify and validate novel tuberculosis drug targets are presented.     

Target discovery and validation in the post-genomic era

The recent publication of the human genome sequence provides an opportunity both to combat diseases that are presently considered as pharmaceutically intractable and also to improve current therapies for many common human diseases. The identification of every human gene by ongoing bioinformatic efforts has the potential, when combined with functional genomic approaches, to pinpoint the molecular basis of every human disease, and to discover appropriate intervention points. This exciting prospect is directly relevant to the successful development of effective therapeutics because the past record of drug discovery suggests that 30%–40% of experimental drugs fail because an inappropriate biological target was pursued. The major impact of genomic information may therefore be to reduce this biological failure rate by earlier definition of drug targets related to disease susceptibility or progression. This paper briefly reviews some of the approaches that can be used to identify biologically relevant drug targets.