Caenorhabditis elegans: a versatile platform for drug discovery

Drug discovery and drug target identification are two intimately linked facets of intervention strategies aimed at effectively combating pathological conditions in humans. Simple model organisms provide attractive platforms for devising and streamlining efficient drug discovery and drug target identification methodologies. The nematode worm Caenorhabditis elegans has emerged as a particularly convenient and versatile tool that can be exploited to achieve these goals. Although C. elegans is a relatively modern addition to the arsenal of model organisms, its biology has already been investigated to an exceptional level. This, coupled with effortless handling and a notable low cost of cultivation and maintenance, allows seamless implementation of high-throughput drug screening approaches as well as in-depth genetic and biochemical studies of the molecular pathways targeted by specific drugs. In this review, we introduce C. elegans as a model organism with significant advantages toward the identification of molecular drug targets. In addition, we discuss the value of the worm in the development of drug screening and drug evaluation protocols. The unique features of C. elegans, which greatly facilitate drug studies, hold promise for both deciphering disease pathogenesis and formulating educated and effective therapeutic interventions.     

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。     

Genetic strategies for antibacterial drug discovery

The availability of genome sequences is revolutionizing the field of microbiology. Genetic methods are being modified to facilitate rapid analysis at a genome-wide level and are blossoming for human pathogens that were previously considered intractable. This revolution coincided with a growing concern about the emergence of microbial drug resistance, compelling the pharmaceutical industry to search for new antimicrobial agents. The availability of the new technologies, combined with many genetic strategies, has changed the way that researchers approach antibacterial drug discovery.     

Anti-MRSA agent discovery using Caenorhabditis elegans -based high-throughput screening

Staphylococcus aureus is a leading cause of hospital- and community-acquired infections. Despite current advances in antimicrobial chemotherapy, the infections caused by S. aureus remain challenging due to their ability to readily develop resistance. Indeed, antibiotic resistance, exemplified by methicillin-resistant S. aureus (MRSA) is a top threat to global health security. Furthermore, the current rate of antibiotic discovery is much slower than the rate of antibiotic-resistance development. It seems evident that the conventional in vitro bacterial growth-based screening strategies can no longer effectively supply new antibiotics at the rate needed to combat bacterial antibiotic-resistance. To overcome this antibiotic resistance crisis, screening assays based on host–pathogen interactions have been developed. In particular, the free-living nematode Caenorhabditis elegans has been used for drug screening against MRSA. In this review, we will discuss the general principles of the C. elegans-based screening platform and will highlight its unique strengths by comparing it with conventional antibiotic screening platforms. We will outline major hits from high-throughput screens of more than 100,000 small molecules using the C. elegans–MRSA infection assay and will review the mode-of-action of the identified hit compounds. Lastly, we will discuss the potential of a C. elegans-based screening strategy as a paradigm shift screening platform.     

C. elegans: model host and tool for antimicrobial drug discovery

For almost four decades, the nematode Caenorhabditis elegans has been of great value in many fields of biological research. It is now used extensively in studies of microbial pathogenesis and innate immunity. The worm lacks an adaptive immune system and relies solely on its innate immune defences to cope with pathogen attack. Infectious microbes, many of which are of clinical interest, trigger specific mechanisms of innate immunity, and provoke the expression of antifungal or antibacterial polypeptides. In this review, we highlight some of these families of antimicrobial peptides (AMPs) and proteins that are candidates for the development of novel antibiotics. In addition, we describe how systems of C. elegans infection provide an increasing number of possibilities for large-scale in vivo screens for the discovery of new antimicrobial drugs. These systems open promising perspectives for innovative human therapies.     

Molecular imaging strategies for drug discovery and development

Recent advances in non-invasive molecular imaging provide exciting opportunities for discovery, validation and development of novel therapeutics. As the arsenal of detection devices and strategies, injectable probes, genetically encoded reporters and animal models rapidly expands, molecular imaging is becoming indispensable for drug discovery and development. Not only do such strategies reduce the time, cost and workload associated with conventional destructive end-point assays, but they also enable spatial and temporal monitoring of in vivo gene expression, signaling pathways, biochemical reactions and targets as they relate to the pharmacokinetics and pharmacodynamics of novel drugs.     

npr-1 Regulates foraging and dispersal strategies in Caenorhabditis elegans

Wild isolates of Caenorhabditis elegans differ in their tendency to aggregate on food [1, 2]. Most quantitative variation in this behavior is explained by a polymorphism at a single amino acid in the G protein-coupled receptor NPR-1: gregarious strains carry the 215F allele, and solitary strains carry the 215V allele [2]. Although npr-1 regulates a behavioral syndrome with potential adaptive implications, the evolutionary causes and consequences of this natural polymorphism remain unclear. Here we show that npr-1 regulates two behaviors that can promote coexistence of the two alleles. First, gregarious and solitary worms differ in their responses to food such that they can partition a single, continuous patch of food. Second, gregarious worms disperse more readily from patch to patch than do solitary worms, which can cause partitioning of a fragmented resource. The dispersal propensity of both gregarious and solitary worms increases with density. npr-1-dependent dispersal is independent of aggregation and could be part of a food-searching strategy. The gregarious allele is favored in a fragmented relative to a continuous food environment in competition experiments. We conclude that the npr-1 polymorphism could be maintained by a trade-off between dispersal and competitive ability.     

Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening

Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities.     

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.     

Systems modeling: a pathway to drug discovery

Systems modeling is emerging as a valuable tool in therapeutics. This is seen by the increasing use of clinically relevant computational models and a rise in systems biology companies working with the pharmaceutical industry. Systems models have helped understand the effects of pharmacological intervention at receptor, intracellular and intercellular communication stages of cell signaling. For instance, angiogenesis models at the ligand-receptor interaction level have suggested explanations for the failure of therapies for cardiovascular disease. Intracellular models of myeloma signaling have been used to explore alternative drug targets and treatment schedules. Finally, modeling has suggested novel approaches to treating disorders of intercellular communication, such as diabetes. Systems modeling can thus fill an important niche in therapeutics by making drug discovery a faster and more systematic process.     

Virtual screening strategies in drug discovery

The identification of novel therapeutic targets and characterization of their 3D structures is increasing at a dramatic rate. Computational screening methods continue to be developed and improved as credible and complementary alternatives to high-throughput biochemical compound screening (HTS). While the majority of drug candidates currently being developed have been found using HTS methods, high-throughput docking and pharmacophore-based searching algorithms are gaining acceptance and becoming a major source of lead molecules in drug discovery. Refinements and optimization of high-throughput docking methods have lead to improvements in reproducing experimental data and in hit rates obtained, validating their use in hit identification. In parallel with virtual screening methods, concomitant developments in cheminformatics including identification, design and manipulation of drug-like small molecule libraries have been achieved. Herein, currently used in silico screening techniques and their utility on a comparative and target dependent basis is discussed.     

Deriving Schwann cells from hPSCs enables disease modeling and drug discovery for diabetic peripheral neuropathy

1. Download : Download high-res image (316KB)
2. Download : Download full-size image

     

Metabolic network modeling and simulation for drug targeting and discovery

Systems biology has greatly contributed toward the analysis and understanding of biological systems under various genotypic and environmental conditions on a much larger scale than ever before. One of the applications of systems biology can be seen in unraveling and understanding complicated human diseases where the primary causes for a disease are often not clear. The in silico genome-scale metabolic network models can be employed for the analysis of diseases and for the discovery of novel drug targets suitable for treating the disease. Also, new antimicrobial targets can be discovered by analyzing, at the systems level, the genome-scale metabolic network of pathogenic microorganisms. Such applications are possible as these genome-scale metabolic network models contain extensive stoichiometric relationships among the metabolites constituting the organism's metabolism and information on the associated biophysical constraints. In this review, we highlight applications of genome-scale metabolic network modeling and simulations in predicting drug targets and designing potential strategies in combating pathogenic infection. Also, the use of metabolic network models in the systematic analysis of several human diseases is examined. Other computational and experimental approaches are discussed to complement the use of metabolic network models in the analysis of biological systems and to facilitate the drug discovery pipeline.     

Homology modeling of nematode Caenorhabditis elegans CED3 protein-inhibitor complex

CED3 protein, the product of a gene necessary for programmed cell death in the nematode Caenorhabditis elegans, is related to a highly specific cysteine protease family i.e., caspases. A tertiary-structural model has been constructed of a complex of the CED3 protein with tetrapeptide-aldehyde inhibitor, Ac-DEVD-CHO. The conformation of CED3 protein active site and the general binding features of inhibitor residues are similar to those observed in other caspases. The loop segment (Phe380-Pro387) binds with the P4 Asp in a different fashion compared to caspase-3. The comparative modeling of active sites from caspase-3 and CED3 protein indicated that although these enzymes require Asp at the position P4, variation could occur in the binding of this residue at the S4 subsite. This model allowed the definition of substrate specificity of CED3 protein from the structural standpoint and provided insight in designing of mutants for structure-function studies of this classical caspase homologue.     

Macromolecular therapeutics: emerging strategies for drug discovery in the postgenome era

The postgenome era offers a plethora of potential therapeutic targets. Many of these targets will be addressable using small organic molecules as drug candidates. However, certain aspects of cell function, particularly those that rely on protein-protein or protein-nucleic acid interactions, will be difficult to influence using small molecules. Thus, the possibility of using highly specific macromolecules as potential therapeutic agents is an intriguing concept. Recent developments in several areas of research have brought this possibility closer to fruition. Peptide and nucleic acid combinatorial libraries allow the generation of novel molecules having exquisite selectivity. Structural information and molecular modeling also contribute to the design of new macromolecules with therapeutic potential. Perhaps most importantly, approaches for delivering macromolecules into the cell interior have been developed and applied with considerable success. Thus, the therapeutic use of macromolecules, including oligonucleotides, peptides, and proteins, may be an idea whose time has come.