Gene expression profiling and therapeutic interventions in neurodegenerative diseases: a comprehensive study on potentiality and limits

Introduction: Neurodegenerative diseases are incurable debilitating disorders of the nervous system that affect approximately 30 million people worldwide. Despite profuse efforts attempting to define the molecular mechanisms underlying neurodegeneration, many aspects of these pathologies remain elusive. The novelty of their mechanisms represents a challenge to biology, to their related biomarkers identification and drug discovery. Because of their multifactorial aspects and complexity, gene expression analysis platforms have been extensively used to investigate altered pathways during degeneration and to identify potential biomarkers and drug targets.

Areas covered: This work offers an overview of the gene expression profiling studies carried out on Alzheimer's disease, Huntington's disease, Parkinson's disease and prion disease specimens. Therapeutic approaches are also discussed.

Expert opinion: Although many therapeutic approaches have been tested, some of them acting on several altered cellular pathways, no effective cures for these neurodegenerative diseases have been identified. Microarray technology must be associated with functional proteomics and physiology in an effort to identify specific and selective biomarkers and druggable targets, thus allowing the successful discovery of disease-modifying therapeutic treatments.     

Genome-wide association studies: progress and potential for drug discovery and development

Although genetic studies have been critically important for the identification of therapeutic targets in Mendelian disorders, genetic approaches aiming to identify targets for common, complex diseases have traditionally had much more limited success. However, during the past year, a novel genetic approach - genome-wide association (GWA) - has demonstrated its potential to identify common genetic variants associated with complex diseases such as diabetes, inflammatory bowel disease and cancer. Here, we highlight some of these recent successes, and discuss the potential for GWA studies to identify novel therapeutic targets and genetic biomarkers that will be useful for drug discovery, patient selection and stratification in common diseases.     

New approaches for pediatric rhabdomyosarcoma drug discovery: targeting combinatorial signaling

Introduction: Rhabdomyosarcomas (RMS) are rare heterogeneous pediatric tumors that are treated by surgery, chemotherapy and irradiation. New therapeutic approaches are needed, especially in the advanced stages to target the pro-oncogenic signals. Exploring the molecular interactions of the regulatory signals and their roles in the developmental aspects of different subtypes of RMS is essential to identify potential targets and develop new therapeutic drugs. Areas covered: Insights into different drug discovery approaches are discussed with specific emphasis on gene expression profiling, fusion protein, role of small interfering RNA (siRNA)- and microRNA (miRNA)-based discovery approaches, targeting cancer stem cells, and in vitro and in vivo model systems. Targeting some overexpressed signals along with the possibilities of combination therapy of validated drug targets is discussed. Additionally, methods to overcome the limitations of discovery-based research are briefly discussed. Expert opinion: Due to drug resistance, ineffective therapy in advanced stages and relapse, there is a demand to explore new drug targets and discovery approaches. Implementing miRNA-based profiling would reveal the extent of miR-based regulation, various biomarkers and potential targets in RMS. A suitable combination of innovative techniques and the use of model systems might assist the identification and validation of novel targets and drug discovery methods. Combining specific drugs along with type-specific target inhibition of overexpressed mRNAs through siRNA approaches would enable the development of personalized therapy.     

Metabolomics of airways disease in cystic fibrosis

While discovery metabolomic studies have identified many potential biomarkers of cystic fibrosis (CF) airways disease, relatively few have been validated. We review the recent literature to identify the most promising metabolomic findings as those repeatedly observed over multiple studies. Reproducible metabolomic findings include increased airway amino acids and small peptides in CF airways, as well as changes in phospholipids and sphingolipids. Other commonly altered pathways include adenosine metabolism, polyamine synthesis, and oxidative stress. These pathways represent potential biomarkers and therapeutic targets, though findings require reevaluation in the era of highly effective modulator therapies. Analysis of airway biomarkers in exhaled breath holds promise for non-invasive detection, though technical challenges will need to be overcome.     

Emerging therapeutic targets for treatment of leishmaniasis

Introduction: Parasitic diseases that pose a threat to human life include leishmaniasis – caused by protozoan parasite Leishmania species. Existing drugs have limitations due to deleterious side effects like teratogenicity, high cost and drug resistance. This calls for the need to have an insight into therapeutic aspects of disease.

Areas covered: We have identified different drug targets via. molecular, imuunological, metabolic as well as by system biology approaches. We bring these promising drug targets into light so that they can be explored to their maximum. In an effort to bridge the gaps between existing knowledge and prospects of drug discovery, we have compiled interesting studies on drug targets, thereby paving the way for establishment of better therapeutic aspects.

Expert opinion: Advancements in technology shed light on many unexplored pathways. Further probing of well established pathways led to the discovery of new drug targets. This review is a comprehensive report on current and emerging drug targets, with emphasis on several metabolic targets, organellar biochemistry, salvage pathways, epigenetics, kinome and more. Identification of new targets can contribute significantly towards strengthening the pipeline for disease elimination.     

New approaches for pediatric rhabdomyosarcoma drug discovery: targeting combinatorial signaling

Introduction: Rhabdomyosarcomas (RMS) are rare heterogeneous pediatric tumors that are treated by surgery, chemotherapy and irradiation. New therapeutic approaches are needed, especially in the advanced stages to target the pro-oncogenic signals. Exploring the molecular interactions of the regulatory signals and their roles in the developmental aspects of different subtypes of RMS is essential to identify potential targets and develop new therapeutic drugs.

Areas covered: Insights into different drug discovery approaches are discussed with specific emphasis on gene expression profiling, fusion protein, role of small interfering RNA (siRNA)- and microRNA (miRNA)-based discovery approaches, targeting cancer stem cells, and in vitro and in vivo model systems. Targeting some overexpressed signals along with the possibilities of combination therapy of validated drug targets is discussed. Additionally, methods to overcome the limitations of discovery-based research are briefly discussed.

Expert opinion: Due to drug resistance, ineffective therapy in advanced stages and relapse, there is a demand to explore new drug targets and discovery approaches. Implementing miRNA-based profiling would reveal the extent of miR-based regulation, various biomarkers and potential targets in RMS. A suitable combination of innovative techniques and the use of model systems might assist the identification and validation of novel targets and drug discovery methods. Combining specific drugs along with type-specific target inhibition of overexpressed mRNAs through siRNA approaches would enable the development of personalized therapy.     

Application of proteomic technologies in the drug development process

Proteins are the principal targets of drug discovery. Most large pharmaceutical companies now have a proteomics-oriented biotech or academic partner or have started their own proteomics division. Common applications of proteomics in the drug industry include target identification and validation, identification of efficacy and toxicity biomarkers from readily accessible biological fluids, and investigations into mechanisms of drug action or toxicity. Target identification and validation involves identifying proteins whose expression levels or activities change in disease states. These proteins may serve as potential therapeutic targets or may be used to classify patients for clinical trials. Proteomics technologies may also help identify protein-protein interactions that influence either the disease state or the proposed therapy. Efficacy biomarkers are used to assess whether target modulation has occurred. They are used for the characterization of disease models and to assess the effects and mechanism of action of lead candidates in animal models. Toxicity (safety) biomarkers are used to screen compounds in pre-clinical studies for target organ toxicities as well as later on in development during clinical trials. Complementary approaches such as metabolomics and genomics can be used in conjunction with proteomics throughout the drug development process to create more of a unified, systems biology approach.     

Network analysis has diverse roles in drug discovery

Computational biologists use network analysis to uncover relationships between various data types of interest for drug discovery. For example, signalling and metabolic pathways are commonly used to understand disease states and drug mechanisms. However, several other flavours of network analysis techniques are also applicable in a drug discovery context. Recent advances include networks that encompass relationships between diseases, molecular mechanisms and gene targets. Even social networks that mirror interactions within the scientific community are helping to foster collaborations and novel research. We review how these different types of network analysis approaches facilitate drug discovery and their associated challenges.     

Drug discovery approaches to irritable bowel syndrome

Introduction: Irritable bowel syndrome (IBS) is defined by symptoms of abdominal pain and altered bowel habits without detectable organic disease. Antidepressants and serotonin receptor modulators are used to treat IBS, but rare serious adverse events highlight the safety hurdle. Newer drugs with secretory and motility effects via local gut mechanisms have been successfully approved for IBS, often by registering first in a related, non-IBS condition to optimize dosing, formulation and therapeutic window.

Areas covered: This review looks at approaches for novel IBS drug discovery. The underlying pathologies can be tackled locally from the ‘outside-in’ (intestinal lumen, mucosa and neuromuscular) to identify therapeutic targets. The article discusses the mechanisms associated with bile acid malabsorption, microbial dysbiosis, decreased intestinal barrier function, immune dysregulation, motility and visceral hypersensitivity.

Expert opinion: Challenges for new drug discovery are the unknown mechanisms underlying IBS, making it difficult to predict clinically efficacious molecular targets, limited options for translational research and disease progression biomarkers. Drugs acting locally via multiple targets (e.g., eluxadoline [The U.S. Food and Drug Administration approved Viberzi (eluxadoline) for IBS-D on May 27th 2015], crofelemer) to validated mechanisms are proving successful with tolerable safety margins. Novel mechanisms, identified and optimized based on the emerging role of nutrient signaling, probiotics or microbial products, are promising. Therapeutic treatment earlier in disease progression may improve response and have longer term benefits.     

Using Drosophila models of neurodegenerative diseases for drug discovery

Introduction: Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and Huntington's disease are increasing in prevalence as our aging population increases in size. Despite this, currently there are no disease-modifying drugs available for the treatment of these conditions. Drosophila melanogaster is a highly tractable model organism that has been successfully used to emulate various aspects of these diseases in vivo. These Drosophila models have not been fully exploited in drug discovery and design strategies. Areas covered: This review explores how Drosophila models can be used to facilitate drug discovery. Specifically, we review their uses as a physiologically-relevant medium to high-throughput screening tool for the identification of therapeutic compounds and discuss how they can aid drug discovery by highlighting disease mechanisms that may serve as druggable targets in the future. The reader will appreciate how the various attributes of Drosophila make it an unsurpassed model organism and how Drosophila models of neurodegeneration can contribute to drug discovery in a variety of ways. Expert opinion: Drosophila models of human neurodegenerative diseases can make a significant contribution to the unmet need of disease-modifying therapeutic intervention for the treatment of these increasingly common neurodegenerative conditions.     

Tumour heterogeneity and drug resistance: personalising cancer medicine through functional genomics

Intrinsic and acquired drug resistance leads to the eventual failure of cancer treatment regimens in the majority of advanced solid tumours. Understanding drug resistance mechanisms will prove vital in the future development of personalised therapeutic approaches. Functional genomics technologies may permit the discovery of predictive biomarkers by unravelling pathways involved in drug resistance and allow the systematic identification of novel therapeutic targets. Such technologies offer the opportunity to develop personalised treatments and diagnostic tools that may improve the survival and quality of life of patients with cancer. However, despite progress in biomarker and drug target discovery, inter-tumour and intra-tumour molecular heterogeneity will limit the effective treatment of this disease. Combining an improved understanding of cancer cell survival mechanisms associated with intra-tumour heterogeneity and drug resistance may allow the selection of patients for specific treatment regimens that will maximise benefit, limit the acquisition of drug resistance and lessen the impact of deleterious side effects.     

Multi-target therapeutics: when the whole is greater than the sum of the parts

Drugs designed to act against individual molecular targets cannot usually combat multigenic diseases such as cancer, or diseases that affect multiple tissues or cell types such as diabetes and immunoinflammatory disorders. Combination drugs that impact multiple targets simultaneously are better at controlling complex disease systems, are less prone to drug resistance and are the standard of care in many important therapeutic areas. The combination drugs currently employed are primarily of rational design, but the increased efficacy they provide justifies in vitro discovery efforts for identifying novel multi-target mechanisms. In this review, we discuss the biological rationale for combination therapeutics, review some existing combination drugs and present a systematic approach to identify interactions between molecular pathways that could be leveraged for therapeutic benefit.     

Strategies and techniques for multi-component drug design from medicinal herbs and traditional chinese medicine

Many common diseases like diabetes, cardiovascular disease, and cancer are caused or exacerbated by disparate physiological, pathological, environmental, and lifestyle factors. However, the chief aim of current drug discovery approaches is to search for single-entity drugs that interact with well-defined molecular targets (a single receptor or enzyme). The concept of multi-target drugs or multi-component therapy is gaining increased attention with the discovery that many diseases (like hypertension) are best treated by multi-drug or multi-target therapies. Traditional medicines, such as traditional Chinese medicine (TCM) and Indian Ayurveda, have been re-evaluated and are becoming important resources for the discovery of bioactive molecules with therapeutic effects and for designing multi-targets drugs. This article provides an overview of new strategies and techniques to design therapeutic regimes that comprise more than one active ingredient to produce synergistic effects by simultaneously interacting with multiple molecular targets. Advances in phytochemistry, high throughput screening, DNA sequencing, systems biology, and bioinformatics can reveal the chemical composition and molecular mechanisms of TCM and together provide a new template for the early stages of drug discovery. Meanwhile, clinical knowledge of TCM provides a promising framework for multi-component drug design. A renaissance of multi-component drug discovery inspired by traditional medicine is possible.     

Genomics strategies for antifungal drug discovery--from gene discovery to compound screening

The use of genomics tools to discover new genes, to decipher pathways or to assign a function to a gene is just beginning to have an impact. Genomics approaches have been applied to both antibacterial and antifungal target discovery in order to identify a new generation of antibiotics. This review discusses genomics approaches for antifungal drug discovery, focusing on the areas of gene discovery, target validation, and compound screening. A variety of methods to identify fungal genes of interest are discussed, as well as methods for obtaining full-length sequences of these genes. One approach is well-suited to organisms having few introns (Candida albicans), and another for organisms with many introns (Aspergillus fumigatus). To validate broad spectrum fungal targets, the yeast Saccharomyces cerevisiae was used as a model system to rapidly identify genes essential for growth and viability of the organism. Validated targets were then exploited for high-throughput compound screening.     

Emerging applications of kinetic biomarkers in preclinical and clinical drug development

The cost of drug discovery and development is increasing, while the rate of new drug approvals is declining. In contrast to major technological advances with in silico and in vitro screening tools, there have been almost no advances in the tools available for establishing the actions of agents in the complex biochemical networks characteristic of fully assembled living systems. The resulting poor capacity to predict clinical response underlies the high attrition rate of leads at every step of drug development. A potential solution would be provided by kinetic biomarkers (in vivo measurement of fluxes though the key pathways that drive disease processes and therapeutic response). Novel approaches using stable isotope labeling with mass spectrometric analysis have recently emerged for measuring molecular kinetics relevant to drug targets with some applications to drug development. This review discusses the general principles of kinetic biomarkers, providing examples where kinetics have generated meaningful insights into drug activity and highlighting areas where the application of kinetic biomarkers may be particularly useful for future drug discovery and development. Stable isotope mass spectrometric technologies may provide a parallel efficiency for converting molecules into approved drugs with sufficient throughput and reproducibility to maintain pace with the modern engine for generating leads.