Towards High-Throughput Chemobehavioural Phenomics in Neuropsychiatric Drug Discovery

Methods: A bioinformatic protocol for rapid analysis of zebrafish embryo photo-motory responses (PMR) in neurotoxicity testing

Chemobehavioural phenotyping presents unique opportunities for analyzing neurotoxicants and discovering behavior-modifying neuroceuticals in small aquatic model organisms such as zebrafish (Danio rerio). A recently popularized approach in this field involves the utilization of zebrafish embryos for a photo-motor response (PMR) bioassay. The PMR bioassay entails stimulating zebrafish embryos between 24 and 36 h post fertilization (hpf) with a high-intensity light stimulus, inducing a transient increase in the frequency of photo-induced embryo body flexions. These flexions can be computationally analyzed to derive behavioral signatures, enabling the categorization of neuromodulating chemicals. Despite the significant advantages of the PMR bioassay, its widespread implementation is hindered by lack of well described and straightforward high-throughput bioinformatic analysis of behavioral data. In this methods article, we present an easily implementable bioinformatics protocol specifically designed for rapid behavioral analysis of large cohorts of zebrafish specimens in PMR bioassays. We also address common pitfalls encountered during PMR analysis, discuss its limitations, and propose future directions for developing next-generation biometric analysis techniques in chemobehavioural assays utilizing zebrafish embryos.

A broad-taxa approach as an important concept in ecotoxicological studies and pollution monitoring

Aquatic invertebrates play a pivotal role in (eco)toxicological assessments because they offer ethical, cost-effective and repeatable testing options. Additionally, their significance in the food chain and their ability to represent diverse aquatic ecosystems make them valuable subjects for (eco)toxicological studies. To ensure consistency and comparability across studies, international (eco)toxicology guidelines have been used to establish standardised methods and protocols for data collection, analysis and interpretation. However, the current standardised protocols primarily focus on a limited number of aquatic invertebrate species, mainly from Arthropoda, Mollusca and Annelida. These protocols are suitable for basic toxicity screening, effectively assessing the immediate and severe effects of toxic substances on organisms. For more comprehensive and ecologically relevant assessments, particularly those addressing long-term effects and ecosystem-wide impacts, we recommended the use of a broader diversity of species, since the present choice of taxa exacerbates the limited scope of basic ecotoxicological studies. This review provides a comprehensive overview of (eco)toxicological studies, focusing on major aquatic invertebrate taxa and how they are used to assess the impact of chemicals in diverse aquatic environments. The present work supports the use of a broad-taxa approach in basic environmental assessments, as it better represents the natural populations inhabiting various ecosystems. Advances in omics and other biochemical and computational techniques make the broad-taxa approach more feasible, enabling mechanistic studies on non-model organisms. By combining these approaches with in vitro techniques together with the broad-taxa approach, researchers can gain insights into less-explored impacts of pollution, such as changes in population diversity, the development of tolerance and transgenerational inheritance of pollution responses, the impact on organism phenotypic plasticity, biological invasion outcomes, social behaviour changes, metabolome changes, regeneration phenomena, disease susceptibility and tissue pathologies. This review also emphasises the need for harmonised data-reporting standards and minimum annotation checklists to ensure that research results are findable, accessible, interoperable and reusable (FAIR), maximising the use and reusability of data. The ultimate goal is to encourage integrated and holistic problem-focused collaboration between diverse scientific disciplines, international standardisation organisations and decision-making bodies, with a focus on transdisciplinary knowledge co-production for the One-Health approach.

Artificial intelligence: Machine learning approach for screening large database and drug discovery

Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance due to rapidly accumulating mutations. Virtual screening is the most widely used method in computer aided drug discovery. It has a prominent ability in screening drug targets from large molecular databases. Recently, a number of web servers have developed for quickly screening publicly accessible chemical databases. In a nutshell, deep learning algorithms and artificial neural networks have modernised the field. Several drug discovery processes have used machine learning and deep learning algorithms, including peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modelling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Although there are presently a wide variety of data-driven AI/ML tools available, the majority of these tools have, up to this point, been developed in the context of non-communicable diseases like cancer, and a number of obstacles have prevented the translation of these tools to the discovery of treatments against infectious diseases. In this review various aspects of AI and ML in virtual screening of large databases were discussed. Here, with an emphasis on antivirals as well as other disease, offers a perspective on the advantages, drawbacks, and hazards of AI/ML techniques in the search for innovative treatments.

The technology, opportunities, and challenges of Synthetic Biological Intelligence

Integrating neural cultures developed through synthetic biology methods with digital computing has enabled the early development of Synthetic Biological Intelligence (SBI). Recently, key studies have emphasized the advantages of biological neural systems in some information processing tasks. However, neither the technology behind this early development, nor the potential ethical opportunities or challenges, have been explored in detail yet. Here, we review the key aspects that facilitate the development of SBI and explore potential applications. Considering these foreseeable use cases, various ethical implications are proposed. Ultimately, this work aims to provide a robust framework to structure ethical considerations to ensure that SBI technology can be both researched and applied responsibly.

The Amphibian Short-Term Assay: Evaluation of a New Ecotoxicological Method for Amphibians Using Two Organophosphate Pesticides Commonly Found in Nature-Assessment of Behavioral Traits

Neurotoxic pesticides are used worldwide to protect crops from insects; they are recognized to impact nontarget organisms that live in areas surrounded by treated crops. Many biochemical and cell-based solutions have been developed for testing insecticide neurotoxicity. Nevertheless, such solutions provide a partial assessment of the impact of neurotoxicity, neglecting important phenotypic components such as behavior. Behavior is the apical endpoint altered by neurotoxicity, and scientists are increasingly recommending including behavioral endpoints in available tests or developing new methods for assessing contaminant-induced behavioral changes. In the present study, we extended an existing protocol (the amphibian short-term assay) with a behavioral test. To this purpose, we developed a homemade device along with an open-source computing solution for tracking trajectories of Xenopus laevis tadpoles exposed to two organophosphates insecticides (OPIs), diazinon (DZN) and chlorpyrifos (CPF). The data resulting from the tracking were then analyzed, and the impact of exposure to DZN and CPF was tested on speed- and direction-related components. Our results demonstrate weak impacts of DZN on the behavioral components, while CPF demonstrated strong effects, notably on speed-related components. Our results also suggest a time-dependent alteration of behavior by CPF, with the highest impacts at day 6 and an absence of impact at day 8. Although only two OPIs were tested, we argue that our solution coupled with biochemical biomarkers is promising for testing the neurotoxicity of this pesticide group on amphibians. Environ Toxicol Chem 2023;42:1595-1606. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

Digital Video Acquisition and Optimization Techniques for Effective Animal Tracking in Behavioral Ecotoxicology

Behavioral phenotypic analysis is an emerging and increasingly important toolbox in aquatic ecotoxicology. In this regard digital video recording has recently become a standard in obtaining behavioral data. Subsequent analysis requires applications of specialized software for detecting and reconstructing animal locomotory trajectories as well as extracting quantitative biometric endpoints associated with specific behavioral traits. Despite some profound advantages for behavioral ecotoxicology, there is a notable lack of standardization of procedures and guidelines that would aid in consistently acquiring high-quality digital videos. The latter are fundamental for using animal tracking software successfully and to avoid issues such as identification switching, incorrect interpolation, and low tracking visibility. Achieving an optimized tracking not only saves user time and effort to analyze the results but also provides high-fidelity data with minimal artifacts. In the present study we, for the first time, provide an easily accessible guide on how to set up and optimize digital video acquisition while minimizing pitfalls in obtaining the highest-quality data for subsequent animal tracking. We also discuss straightforward digital video postprocessing techniques that can be employed to further enhance tracking consistency or improve the videos that were acquired in otherwise suboptimal settings. The present study provides an essential guidebook for any aquatic ecotoxicology studies that utilize digital video acquisition systems for evaluation of behavioral endpoints. Environ Toxicol Chem 2022;41:2342-2352. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Targeted Isolation of Antibiotic Brominated Alkaloids from the Marine Sponge Pseudoceratina durissima Using Virtual Screening and Molecular Networking

Many targeted natural product isolation approaches rely on the use of pre-existing bioactivity information to inform the strategy used for the isolation of new bioactive compounds. Bioactivity information can be available either in the form of prior assay data or via Structure Activity Relationship (SAR) information which can indicate a potential chemotype that exhibits a desired bioactivity. The work described herein utilizes a unique method of targeted isolation using structure-based virtual screening to identify potential antibacterial compounds active against MRSA within the marine sponge order Verongiida. This is coupled with molecular networking-guided, targeted isolation to provide a novel drug discovery procedure. A total of 12 previously reported bromotyrosine-derived alkaloids were isolated from the marine sponge species Pseudoceratina durissima, and the compound, (+)-aeroplysinin-1 (1) displayed activity against the MRSA pathogen (MIC: <32 µg/mL). The compounds (1−3, 6 and 9) were assessed for their central nervous system (CNS) interaction and behavioral toxicity to zebrafish (Danio rerio) larvae, whereby several of the compounds were shown to induce significant hyperactivity. Anthelmintic activity against the parasitic nematode Haemonchus contorutus was also evaluated (2−4, 6−8).

Beyond the behavioural phenotype: Uncovering mechanistic foundations in aquatic eco-neurotoxicology

During the last decade, there has been an increase in awareness of how anthropogenic pollution can alter behavioural traits of diverse aquatic organisms. Apart from understanding profound ecological implications, alterations in neuro-behavioural indices have emerged as sensitive and physiologically integrative endpoints in chemical risk assessment. Accordingly, behavioural ecotoxicology and broader eco-neurotoxicology are becoming increasingly popular fields of research that span a plethora of fundamental laboratory experimentations as well as applied field-based studies. Despite mounting interest in aquatic behavioural ecotoxicology studies, there is, however, a considerable paucity in deciphering the mechanistic foundations underlying behavioural alterations upon exposure to pollutants. The behavioural phenotype is indeed the highest-level integrative neurobiological phenomenon, but at its core lie myriads of intertwined biochemical, cellular, and physiological processes. Therefore, the mechanisms that underlie changes in behavioural phenotypes can stem among others from dysregulation of neurotransmitter pathways, electrical signalling, and cell death of discrete cell populations in the central and peripheral nervous systems. They can, however, also be a result of toxicity to sensory organs and even metabolic dysfunctions. In this critical review, we outline why behavioural phenotyping should be the starting point that leads to actual discovery of fundamental mechanisms underlying actions of neurotoxic and neuromodulating contaminants. We highlight potential applications of the currently existing and emerging neurobiology and neurophysiology analytical strategies that should be embraced and more broadly adopted in behavioural ecotoxicology. Such strategies can provide new mechanistic discoveries instead of only observing the end sum phenotypic effects.

Impact of test chamber design on spontaneous behavioral responses of model crustacean zooplankton Artemia franciscana

The use of small aquatic model organisms to investigate the behavioral effects of chemical exposure is becoming an integral component of aquatic ecotoxicology research and neuroactive drug discovery. Despite the increasing use of invertebrates for behavioral phenotyping in toxicological studies and chemical risk assessments, little is known regarding the potential for environmental factors-such as geometry, size, opacity and depth of test chambers-to modulate common behavioral responses. In this work, we demonstrate that test chamber geometry, size, opacity and depth can affect spontaneous, unstimulated behavioral responses of euryhaline crustacean Artemia franciscana first instar larval stages. We found that in the absence of any obvious directional cues, A. franciscana exhibited a strong innate wall preference behavior. Using different test chamber sizes and geometries, we found both increased wall preference and lowered overall distance traveled by the test shrimp in a smaller chamber with sharper-angled vertices. It was also determined through quantifiable changes in the chambers' color that the A. franciscana early larval stages can perceive, differentiate and react to differences in color or perhaps rather to light transmittance of the test chambers. The interaction between innate edge preference and positive phototaxis could be consistently altered with a novel photic stimulus system. We also observed a strong initial preference for depth in A. franciscana first instar larval stages, which diminished through the acclimatization. We postulate that the impact of test chamber designs on neurobehavioral baseline responses warrants further investigation, in particular considering the increased interest in behavioral eco-neurotoxicology applications.

Phenotype-Based HPLC-Q-TOF-MS/MS Coupled With Zebrafish Behavior Trajectory Analysis System for the Identification of the Antidepressant Components in Methanol Extract of Anshen Buxin Six Pills

Phenotype screening has become an important tool for the discovery of active components in traditional Chinese medicine. Anshen Buxin Six Pills (ASBX) are a traditional Mongolian medicine used for the treatment of neurosis in clinical settings. However, its antidepressant components have not been explicitly identified and studied. Here, the antidepressant effect of ASBX was evaluated in adult zebrafish. High performance liquid chromatography-mass spectrometry (HPLC-Q-TOF-MS/MS) was combined with zebrafish behavior trajectory analysis to screen and identify the antidepressant-active extract fraction and active components of ASBX. Finally, the antidepressant effect of the active ingredients were verified by the behavior, pathology, biochemical indices and protein level of adult fish. The novel tank driving test (NTDT) showed that ASBX can effectively improve the depressive effect of reserpine on zebrafish. Petroleum ether and dichloromethane extracts of ASBX were screened as antidepressant active extracts. Costunolide (COS) and dehydrocostus lactone (DHE) were screened as the active components of ASBX. COS had been shown to significantly improve the depressive behavior, nerve injury and neurotransmitter levels (5-hydroxytryptamine (5-HT) and norepinephrine (NE)) of zebrafish by inhibiting the high expression of serotonin transporter and norepinephrine transporter induced by reserpine suggesting the antidepressant effect of COS may be related to its effect on 5-HT and NE pathways. This study provided a phenotype based screening method for antidepressant components of traditional Chinese medicines, so as to realize the separation, identification and activity screening of components at the same time.

Anticonvulsant activity of melatonin and its success in ameliorating epileptic comorbidity-like symptoms in zebrafish

Epilepsy is one of common neurological disorders, greatly distresses the well-being of the sufferers. Melatonin has been used in clinical anti-epileptic studies, but its effect on epileptic comorbidities is unknown, and the underlying mechanism needs further investigation. Herein, by generating PTZ-induced zebrafish seizure model, we carried out interdisciplinary research using neurobehavioral assays, bioelectrical detection, molecular biology, and network pharmacology to investigate the activity of melatonin as well as its pharmacological mechanisms. We found melatonin suppressed seizure-like behavior by using zebrafish regular locomotor assays. Zebrafish freezing and bursting activity assays revealed the ameliorative effect of melatonin on comorbidity-like symptoms. The preliminary screening results of neurobehavioral assays were further verified by the expression of key genes involved in neuronal activity, neurodevelopment, depression and anxiety, as well as electrical signal recording from the midbrain of zebrafish. Subsequently, network pharmacology was introduced to identify potential targets of melatonin and its pathways. Real-time qPCR and protein-protein interaction (PPI) were conducted to confirm the underlying mechanisms associated with glutathione metabolism. We also found that melatonin receptors were involved in this process, which were regulated in response to melatonin exposure before PTZ treatment. The antagonists of melatonin receptors affected anticonvulsant activity of melatonin. Overall, current study revealed the considerable ameliorative effects of melatonin on seizure and epileptic comorbidity-like symptoms and unveiled the underlying mechanism. This study provides an animal model for the clinical application of melatonin in the treatment of epilepsy and its comorbidities.

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries

The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted. The critical point to consider the drug design is to use the available data resources and to find new and novel leads. Once the drug target is identified, several interdisciplinary areas work together with artificial intelligence (AI) and machine learning (ML) methods to get enriched drugs. These AI and ML methods are applied in every step of the computer-aided drug design, and integrating these AI and ML methods results in a high success rate of hit compounds. In addition, this AI and ML integration with high-dimension data and its powerful capacity have taken a step forward. Clinical trials output prediction through the AI/ML integrated models could further decrease the clinical trials cost by also improving the success rate. Through this review, we discuss the backend of AI and ML methods in supporting the computer-aided drug design, along with its challenge and opportunity for the pharmaceutical industry. From the available information or data, the AI and ML based prediction for the high throughput virtual screening. After this integration of AI and ML, the success rate of hit identification has gained a momentum with huge success by providing novel drugs.

Advances in real-time monitoring of water quality using automated analysis of animal behaviour

Monitoring of freshwater quality and its potential sudden contamination is integral to human health, sustainable economic development and prediction of pollutant impact on aquatic ecosystems. Although there have been significant advances in technologies for automated sampling and continuous analysis of water physicochemical parameters, the current capabilities for real-time warning against rapidly developing unknown mixtures of chemical hazards are still limited. Conventional chemical analysis systems are not suitable for assessing unknown mixtures of chemicals as well as additive and/or synergetic effects on biological systems. From the perspective of neurotoxicology the acute exposures to chemical agents that affect nervous system and can enter the freshwater supplies accidentally or as a result of deliberate action, can only be reliably assessed using appropriate functional biological models. In this regard real-time biological early warning systems (BEWS), that can continuously monitor behavioural and/or physiological parameters of suitable aquatic bioindicator species, have been historically proposed to fill the gap and supplement conventional water quality test strategies. Alterations in sub-lethal neuro-behavioural traits have been proven as very sensitive and physiologically relevant endpoints that can provide highly integrative water quality sensing capabilities. Although BEWS are commonly regarded as non-specific and lacking both quantitative and qualitative detection capabilities, their advantages, if properly designed and implemented, lie in continuous sensing and early-warning information about sudden alteration in water quality parameters. In this work we review the future prospects of real-time biological early warning systems as well as recent developments that are anchored in historical successes and practical deployment examples. We concentrate on technologies utilizing analysis of behavioural and physiological endpoints of animal bioindicators and highlight the existing challenges, barriers to future development and demonstrate how recent advances in inexpensive electronics and multidisciplinary bioengineering can help revitalize the BEWS field.

Applications of advanced neuro-behavioral analysis strategies in aquatic ecotoxicology

Despite mounting evidence of pleiotropic ecological risks, the understanding of the eco-neurotoxic impact of most industrially relevant chemicals is still very limited. In particularly the acute and chronic exposures to industrial pollutants on nervous systems and thus potential alterations in ecological fitness remain profoundly understudied. Since the behavioral phenotype is the highest-level and functional manifestation of integrated neurological functions, the alterations in neuro-behavioral traits have been postulated as very sensitive and physiologically integrative endpoints to assess eco-neurotoxicological risks associated with industrial pollutants. Due to a considerable backlog of risk assessments of existing and new production chemicals there is a need for a paradigm shift from high cost, low throughput ecotoxicity test models to next generation systems amenable to higher throughput. In this review we concentrate on emerging aspects of laboratory-based neuro-behavioral phenotyping approaches that can be amenable for rapid prioritizing pipelines. We outline the importance of development and applications of innovative neuro-behavioral assays utilizing small aquatic biological indicators and demonstrate emerging concepts of high-throughput chemo-behavioral phenotyping. We also discuss new analytical approaches to effectively and rapidly evaluate the impact of pollutants on higher behavioral functions such as sensory-motor assays, decision-making and cognitive behaviors using innovative model organisms. Finally, we provide a snapshot of most recent analytical approaches that can be applied to elucidate mechanistic rationale that underlie the observed neuro-behavioral alterations upon exposure to pollutants. This review is intended to outline the emerging opportunities for innovative multidisciplinary research and highlight the existing challenges as well barriers to future development.

Toward High-Throughput Fish Embryo Toxicity Tests in Aquatic Toxicology

Addressing the shift from classical animal testing to high-throughput in vitro and/or simplified in vivo proxy models has been defined as one of the upcoming challenges in aquatic toxicology. In this regard, the fish embryo toxicity test (FET) has gained significant popularity and wide standardization as one of the sensitive alternative approaches to acute fish toxicity tests in chemical risk assessment and water quality evaluation. Nevertheless, despite the growing regulatory acceptance, the actual manipulation, dispensing, and analysis of living fish embryos remains very labor intensive. Moreover, the FET is commonly performed in plastic multiwell plates under static or semistatic conditions, potentially inadequate for toxicity assessment of some organic, easily degradable or highly adsorptive toxicants. Recent technological advances in the field of mechatronics, fluidics and digital vision systems demonstrate promising future opportunities for automation of many analytical stages in embryo toxicity testing. In this review, we highlight emerging advances in fluidic and laboratory automation systems that can prospectively enable high-throughput FET testing (HT-FET) akin to pipelines commonly found in in vitro drug discovery pipelines. We also outline the existing challenges, barriers to future development and provide an outlook of ground-breaking fluidic technologies in embryo toxicity testing.

Emerging prospects of integrated bioanalytical systems in neuro-behavioral toxicology

Neurotoxicity effects of industrial contaminants are currently significantly under investigated and require innovative analytical approaches to assess health and environmental risks at individual, population and ecosystem levels. Behavioral changes assessed using small aquatic invertebrates as standard biological indicators of the aggregate toxic effects, have been broadly postulated as highly integrative indicators of neurotoxicity with physiological and ecological relevance. Despite recent increase in understanding of the emerging value of behavioral biotests, their wider implementation especially in high-throughput environmental risk assessment assays, is largely limited by the lack of advances in analytical technologies. To date, most of the behavioral biotests have only been performed with larger-volumes and lacked dynamic flow-through conditions. They also lack features necessary for development of higher throughput neuro-behavioral ecotoxicity assays such as miniaturization and integration of automated components. We postulate that some contemporary analytical limitations can be effectively addressed by innovative Lab-on-a-Chip (LOC) technologies, an emerging and multidisciplinary field poised to bring significant miniaturization to aquatic ecotoxicity testing. Recent developments in this emerging field demonstrate particular opportunities to study a plethora of behavioral responses of small model organisms in a high-throughput fashion. In this review, we highlight recent advances in this budding new interdisciplinary field of research. We also outline the existing challenges, barriers to development and provide a future outlook in the evolving field of neurobehavioral ecotoxicology.

Single-cell infrared phenomics: phenotypic screening with infrared microspectroscopy

We conceptually demonstrate single-cell infrared phenomics as a novel strategy of phenotypic screening with infrared microspectroscopy. Based on this development, the cancer cell HepG2 glycocalyx was first identified as a potential target of protopanaxadiol, an herbal medicine. These findings provide a powerful tool to accurately evaluate the cell stress response and to largely expand the phenotypic screening toolkit for drug discovery.

The Resurrection of Phenotypic Drug Discovery

Prior to genetic mapping, the majority of drug discovery efforts involved phenotypic screening, wherein compounds were screened in either in vitro or in vivo models thought to mimic the disease state of interest. While never completely abandoning phenotypic approaches, the labor intensive nature of such tests encouraged the pharmaceutical industry to move away from them in favor of target-based drug discovery, which facilitated throughput and allowed for the efficient screening of large numbers of compounds. However, a consequence of reliance on target-based screening was an increased number of failures in clinical trials due to poor correlation between novel mechanistic targets and the actual disease state. As a result, the field has seen a recent resurrection in phenotypic drug discovery approaches. In this work, we highlight some recent phenotypic projects from our industrial past and in our current academic drug discovery environment that have provided encouraging results.

Kinase-Based Screening of Marine Natural Extracts Leads to the Identification of a Cytotoxic High Molecular Weight Metabolite from the Mediterranean Sponge Crambe tailliezi

Regulated cell death (RCD) results from the activation of one or more signal transduction modules both in physiological or pathological conditions. It is now established that RCD is involved in numerous human diseases, including cancer. As regulated cell death processes can be modulated by pharmacological tools, the research reported here aims to characterize new marine compounds acting as RCD modulators. Protein kinases (PKs) are key signaling actors in various RCDs notably through the control of either mitosis (e.g., the PKs Aurora A and B) or necroptosis (e.g., RIPK1 and RIPK3). From the primary screening of 27 various extracts of marine organisms collected in the Mediterranean Sea, an extract and subsequently a purified high molecular weight compound dubbed P3, were isolated from the marine sponge Crambe tailliezi and characterized as a selective inhibitor of PKs Aurora A and B. Furthermore, P3 was shown to induce apoptosis and to decrease proliferation and mitotic index of human osteosarcoma U-2 OS cells.