Introduction to biological complexity as a missing link in drug discovery

Non-thermal disruption of β-adrenergic receptor-activated Ca2+ signalling and apoptosis in human ES-derived cardiomyocytes by microwave electric fields at 2.4 GHz

The ubiquity of wireless electronic-device connectivity has seen microwaves emerge as one of the fastest growing forms of electromagnetic exposure. A growing evidence-base refutes the claim that wireless technologies pose no risk to human health at current safety levels designed to limit thermal (heating) effects. The potential impact of non-thermal effects of microwave exposure, especially in electrically-excitable tissues (e.g., heart), remains controversial. We exposed human embryonic stem-cell derived cardiomyocytes (CM), under baseline and beta-adrenergic receptor (β-AR)-stimulated conditions, to microwaves at 2.4 GHz, a frequency used extensively in wireless communication (e.g., 4G, Bluetooth™ and WiFi). To control for any effect of sample heating, experiments were done in CM subjected to matched rates of direct heating or CM maintained at 37 °C. Detailed profiling of the temporal and amplitude features of Ca²⁺ signalling in CM under these experimental conditions was reconciled with the extent and spatial clustering of apoptosis. The data show that exposure of CM to 2.4 GHz EMF eliminated the normal Ca²⁺ signalling response to β-AR stimulation and provoked spatially-clustered apoptosis. This is first evidence that non-thermal effects of 2.4 GHz microwaves might have profound effects on human CM function, responsiveness to activation, and survival.

Network modeling helps to tackle the complexity of drug-disease systems

From the (patho)physiological point of view, diseases can be considered as emergent properties of living systems stemming from the complexity of these systems. Complex systems display some typical features, including the presence of emergent behavior and the organization in successive hierarchic levels. Drug treatments increase this complexity scenario, and from some years the use of network models has been introduced to describe drug-disease systems and to make predictions about them with regard to several aspects related to drug discovery. Here, we review some recent examples thereof with the aim to illustrate how network science tools can be very effective in addressing both tasks. We will examine the use of bipartite networks that lead to the important concept of "disease module", as well as the introduction of more articulated models, like multi-scale and multiplex networks, able to describe disease systems at increasing levels of organization. Examples of predictive models will then be discussed, considering both those that exploit approaches purely based on graph theory and those that integrate machine learning methods. A short account of both kinds of methodological applications will be provided. Finally, the point will be made on the present situation of modeling complex drug-disease systems highlighting some open issues. This article is categorized under: Neurological Diseases > Computational Models Infectious Diseases > Computational Models Cardiovascular Diseases > Computational Models.

Anticancer activity and metabolic profile alterations by ortho-topolin riboside in in vitro and in vivo models of non-small cell lung cancer

Lung cancer has the highest incidence and mortality rates among all types of cancer worldwide, and 80%-85% of patients with lung cancer are diagnosed with non-small cell lung cancer (NSCLC), which has 5-year survival rate of only 5% at advanced stages. Development of new therapeutic agents and strategies is required to enhance the treatment efficiency in patients with NSCLC. Metabolic alterations and anticancer effects of plant hormones and their derivatives have not been investigated in NSCLC in vitro and in vivo. The present study investigated the cytotoxic effects of 11 plant hormones and their derivatives against NSCLC cell lines; ortho-topolin riboside (oTR) showed the highest cytotoxicity among all tested compounds against NSCLC cells. Alteration of metabolites and lipids was investigated using gas chromatography-mass spectrometry and nano electrospray ionization-mass spectrometry in oTR-treated NSCLC cells and a xenograft mouse model. oTR reduced amino acid and pyrimidine synthesis in NSCLC cells and xenograft tumors. Moreover, oTR reduced glycolytic function and decreased mitochondrial respiration function by inhibiting glutamine and fatty acid oxidation. Increased levels of phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine species suggested that oTR might act as a fatty acid oxidation inhibitor. In addition, the increased level of phosphatidylserine species implied that phosphatidylserine-mediated apoptosis occurred in oTR-treated NSCLC cells and xenograft tumor. The antiproliferative and apoptotic effects of oTR were mediated by the reduced p-ERK and p-AKT levels and increased cleaved Caspase-3 levels, respectively. This is the first study to investigate the metabolic alterations and anticancer activity of oTR in in vitro and in vivo models of NSCLC. Our results provide basis for the development of oTR-based therapeutic agent for patients with NSCLC.

Single-Target Versus Multi-Target Drugs Versus Combinations of Drugs With Multiple Targets: Preclinical and Clinical Evidence for the Treatment or Prevention of Epilepsy

Rationally designed multi-target drugs (also termed multimodal drugs, network therapeutics, or designed multiple ligands) have emerged as an attractive drug discovery paradigm in the last 10-20 years, as potential therapeutic solutions for diseases of complex etiology and diseases with significant drug-resistance problems. Such agents that modulate multiple targets simultaneously are developed with the aim of enhancing efficacy or improving safety relative to drugs that address only a single target or to combinations of single-target drugs. Although this strategy has been proposed for epilepsy therapy >25 years ago, to my knowledge, only one antiseizure medication (ASM), padsevonil, has been intentionally developed as a single molecular entity that could target two different mechanisms. This novel drug exhibited promising effects in numerous preclinical models of difficult-to-treat seizures. However, in a recent randomized placebo-controlled phase IIb add-on trial in treatment-resistant focal epilepsy patients, padsevonil did not separate from placebo in its primary endpoints. At about the same time, a novel ASM, cenobamate, exhibited efficacy in several randomized controlled trials in such patients that far surpassed the efficacy of any other of the newer ASMs. Yet, cenobamate was discovered purely by phenotype-based screening and its presumed dual mechanism of action was only described recently. In this review, I will survey the efficacy of single-target vs. multi-target drugs vs. combinations of drugs with multiple targets in the treatment and prevention of epilepsy. Most clinically approved ASMs already act at multiple targets, but it will be important to identify and validate new target combinations that are more effective in drug-resistant epilepsy and eventually may prevent the development or progression of epilepsy.

Druggable genome in attention deficit/hyperactivity disorder and its co-morbid conditions. New avenues for treatment

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder with only symptomatic care available. Genome-wide association (GWA) studies can provide a starting point in the search for novel drug targets and possibilities of drug repurposing. Here, we explored the druggable genome in ADHD by utilising GWA studies on ADHD and its co-morbid conditions. First, we explored whether the genes targeted by current ADHD drugs show association with the disorder and/or its co-morbidities. Second, we aimed to identify genes and pathways involved in the biological processes underlying ADHD that can be targeted by pharmacological agents. These ADHD-associated druggable genes and pathways were also examined in co-morbidities of ADHD, as commonalities in their aetiology and management may lead to novel pharmacological insights. Strikingly, none of the genes encoding targets of first-line pharmacotherapeutics for ADHD were significantly associated with the disorder, suggesting that FDA-approved ADHD drugs may act through different mechanisms than those underlying ADHD. In the examined druggable genome, three loci on chromosomes 1, 4 and 12 revealed significant association with ADHD and contained nine druggable genes, five of which encode established drug targets for malignancies, autoimmune and neurodevelopmental disorders. To conclude, we present a framework to assess the druggable genome in a disorder, exemplified by ADHD. We highlight signal transduction and cell adhesion as potential novel avenues for ADHD treatment. Our findings add to knowledge on known ADHD drugs and present the exploration of druggable genome associated with ADHD, which may offer interventions at the aetiological level of the disorder.

Suppression of Drug-Resistant Non-Small-Cell Lung Cancer with Inhibitors Targeting Minichromosomal Maintenance Protein

Drug resistance has been a major threat in cancer therapies that necessitates the development of new strategies to overcome this problem. We report here a cell-based high-throughput screen of a library containing two-million molecules for the compounds that inhibit the proliferation of non-small-cell lung cancer (NSCLC). Through the process of phenotypic screening, target deconvolution, and structure-activity relationship (SAR) analysis, a compound of furanonaphthoquinone-based small molecule, AS4583, was identified that exhibited potent activity in tyrosine kinase inhibitor (TKI)-sensitive and TKI-resistant NSCLC cells (IC₅₀ = 77 nM) and in xenograft mice. The mechanistic studies revealed that AS4583 inhibited cell-cycle progression and reduced DNA replication by disrupting the formation of the minichromosomal maintenance protein (MCM) complex. Subsequent SAR study of AS4583 gave compound RJ-LC-07-48 which exhibited greater potency in drug-resistant NSCLC cells (IC₅₀ = 17 nM) and in mice with H1975 xenograft tumor.

Drug discovery strategies for acute radiation syndrome

Introduction: There are at the minimum two major, quite different approaches to advance drug discovery. The first being the target-based drug discovery (TBDD) approach that is commonly referred to as the molecular approach. The second approach is the phenotype-based drug discovery (PBDD), also known as physiology-based drug discovery or empirical approach. Area covered: The authors discuss, herein, the need for developing radiation countermeasure agents for various sub-syndromes of acute radiation syndromes (ARS) following TBDD and PBDD approaches. With time and continuous advances in radiation countermeasure drug development research, the expectation is to have multiple radiation countermeasure agents for each sub-syndrome made available to radiation exposed victims. Expert opinion: The majority of the countermeasures currently being developed for ARS employ the PBDD approach, while the TBDD approach is clearly under-utilized. In the future, an improved drug development strategy might be a 'hybrid' strategy that is more reliant on TBDD for the initial drug discovery via large-scale screening of potential candidate agents, while utilizing PBDD for secondary screening of those candidates, followed by tertiary analytics phase in order to pinpoint efficacious candidates that target the specific sub-syndromes of ARS.

Connect and Conquer: Collectivized Behavior of Mitochondria and Bacteria

The connectedness of signaling components in network structures is a universal feature of biologic information processing. Such organization enables the transduction of complex input stimuli into coherent outputs and is essential in modulating activities as diverse as the cooperation of bacteria within populations and the dynamic organization of mitochondria within cells. Here, we highlight some common principles that underpin collectivization in bacteria and mitochondrial populations and the advantages conferred by such behavior. We discuss the concept that bacteria and mitochondria act as signal transducers of their localized metabolic environments to bring about energy-dependent clustering to modulate higher-order function across multiple scales.

Developments with 3D bioprinting for novel drug discovery

Introduction: Although there have been significant contributions from the pharmaceutical industry to clinical practice, several diseases remain unconquered, with the discovery of new drugs remaining a paramount objective. The actual process of drug discovery involves many steps including pre-clinical and clinical testing, which are highly time- and resource-consuming, driving researchers to improve the process efficiency. The shift of modelling technology from two-dimensions (2D) to three-dimensions (3D) is one of such advancements. 3D Models allow for close mimicry of cellular interactions and tissue microenvironments thereby improving the accuracy of results. The advent of bioprinting for fabrication of tissues has shown potential to improve 3D culture models. Areas covered: The present review provides a comprehensive update on a wide range of bioprinted tissue models and appraise them for their potential use in drug discovery research. Expert opinion: Efficiency, reproducibility, and standardization are some impediments of the bioprinted models. Vascularization of the constructs has to be addressed in the near future. While much progress has already been made with several seminal works, the next milestone will be the commercialization of these models after due regulatory approval.