Filling the drug discovery gap: is high-content screening the missing link?

Novel strategies for drug repurposing

Synthetic biology, precision medicine, and nanobiotechnology are the three main emerging areas that drive translational innovation toward commercialization. There are several strategies used in precision medicine and drug repurposing is one of the key approaches as it addresses the challenges in drug discovery (high cost and time). Here, we provide a perspective on various new approaches to drug repurposing for cancer precision medicine. We report here our optimized wound healing methodology that can be used to validate drug sensitivity and drug repurposing. Using HeLa as our benchmark, we demonstrated that the assay can be applied to identify drugs that limit cell proliferation. From a future perspective, this assay can be expanded to ex vivo culturing of solid tumors in 2D culture and leukemia in 3D culture.

Blood Milieu in Acute Myocardial Infarction Reprograms Human Macrophages for Trauma Repair

Acute myocardial infarction (AMI) is accompanied by a systemic trauma response that impacts the whole body, including blood. This study addresses whether macrophages, key players in trauma repair, sense and respond to these changes. For this, healthy human monocyte-derived macrophages are exposed to 20% human AMI (n = 50) or control (n = 20) serum and analyzed by transcriptional and multiparameter functional screening followed by network-guided data interpretation and drug repurposing. Results are validated in an independent cohort at functional level (n = 47 AMI, n = 25 control) and in a public dataset. AMI serum exposure results in an overt AMI signature, enriched in debris cleaning, mitosis, and immune pathways. Moreover, gene networks associated with AMI and with poor clinical prognosis in AMI are identified. Network-guided drug screening on the latter unveils prostaglandin E2 (PGE2) signaling as target for clinical intervention in detrimental macrophage imprinting during AMI trauma healing. The results demonstrate pronounced context-induced macrophage reprogramming by the AMI systemic environment, to a degree decisive for patient prognosis. This offers new opportunities for targeted intervention and optimized cardiovascular disease risk management.

Mathematical modeling of the microtubule detyrosination/tyrosination cycle for cell-based drug screening design

Microtubules and their post-translational modifications are involved in major cellular processes. In severe diseases such as neurodegenerative disorders, tyrosinated tubulin and tyrosinated microtubules are in lower concentration. We present here a mechanistic mathematical model of the microtubule tyrosination cycle combining computational modeling and high-content image analyses to understand the key kinetic parameters governing the tyrosination status in different cellular models. That mathematical model is parameterized, firstly, for neuronal cells using kinetic values taken from the literature, and, secondly, for proliferative cells, by a change of two parameter values obtained, and shown minimal, by a continuous optimization procedure based on temporal logic constraints to formalize experimental high-content imaging data. In both cases, the mathematical models explain the inability to increase the tyrosination status by activating the Tubulin Tyrosine Ligase enzyme. The tyrosinated tubulin is indeed the product of a chain of two reactions in the cycle: the detyrosinated microtubule depolymerization followed by its tyrosination. The tyrosination status at equilibrium is thus limited by both reaction rates and activating the tyrosination reaction alone is not effective. Our computational model also predicts the effect of inhibiting the Tubulin Carboxy Peptidase enzyme which we have experimentally validated in MEF cellular model. Furthermore, the model predicts that the activation of two particular kinetic parameters, the tyrosination and detyrosinated microtubule depolymerization rate constants, in synergy, should suffice to enable an increase of the tyrosination status in living cells.

Developing CRISPR/Cas9-Mediated Fluorescent Reporter Human Pluripotent Stem-Cell Lines for High-Content Screening

Application of the CRISPR/Cas9 system to knock in fluorescent proteins to endogenous genes of interest in human pluripotent stem cells (hPSCs) has the potential to facilitate hPSC-based disease modeling, drug screening, and optimization of transplantation therapy. To evaluate the capability of fluorescent reporter hPSC lines for high-content screening approaches, we targeted EGFP to the endogenous OCT4 locus. Resulting hPSC–OCT4–EGFP lines generated expressed EGFP coincident with pluripotency markers and could be adapted to multi-well formats for high-content screening (HCS) campaigns. However, after long-term culture, hPSCs transiently lost their EGFP expression. Alternatively, through EGFP knock-in to the AAVS1 locus, we established a stable and consistent EGFP-expressing hPSC–AAVS1–EGFP line that maintained EGFP expression during in vitro hematopoietic and neural differentiation. Thus, hPSC–AAVS1–EGFP-derived sensory neurons could be adapted to a high-content screening platform that can be applied to high-throughput small-molecule screening and drug discovery campaigns. Our observations are consistent with recent findings indicating that high-frequency on-target complexities appear following CRISPR/Cas9 genome editing at the OCT4 locus. In contrast, we demonstrate that the AAVS1 locus is a safe genomic location in hPSCs with high gene expression that does not impact hPSC quality and differentiation. Our findings suggest that the CRISPR/Cas9-integrated AAVS1 system should be applied for generating stable reporter hPSC lines for long-term HCS approaches, and they underscore the importance of careful evaluation and selection of the applied reporter cell lines for HCS purposes.

Past and future of trypanosomatids high-throughput phenotypic screening

Diseases caused by trypanosomatid parasites affect millions of people mainly living in developing countries. Novel drugs are highly needed since there are no vaccines and available treatment has several limitations, such as resistance, low efficacy, and high toxicity. The drug discovery process is often analogous to finding a needle in the haystack. In the last decades a so-called rational drug design paradigm, heavily dependent on computational approaches, has promised to deliver new drugs in a more cost-effective way. Paradoxically however, the mainstay of these computational methods is data-driven, meaning they need activity data for new compounds to be generated and available in databases. Therefore, high-throughput screening (HTS) of compounds still is a much-needed exercise in drug discovery to fuel other rational approaches. In trypanosomatids, due to the scarcity of validated molecular targets and biological complexity of these parasites, phenotypic screening has become an essential tool for the discovery of new bioactive compounds. In this article we discuss the perspectives of phenotypic HTS for trypanosomatid drug discovery with emphasis on the role of image-based, high-content methods. We also propose an ideal cascade of assays for the identification of new drug candidates for clinical development using leishmaniasis as an example.

The right tools for the job: the central role for next generation chemical probes and chemistry-based target deconvolution methods in phenotypic drug discovery

The reconnection of the scientific community with phenotypic drug discovery has created exciting new possibilities to develop therapies for diseases with highly complex biology. It promises to revolutionise fields such as neurodegenerative disease and regenerative medicine, where the development of new drugs has consistently proved elusive. Arguably, the greatest challenge in readopting the phenotypic drug discovery approach exists in establishing a crucial chain of translatability between phenotype and benefit to patients in the clinic. This remains a key stumbling block for the field which needs to be overcome in order to fully realise the potential of phenotypic drug discovery. Excellent quality chemical probes and chemistry-based target deconvolution techniques will be a crucial part of this process. In this review, we discuss the current capabilities of chemical probes and chemistry-based target deconvolution methods and evaluate the next advances necessary in order to fully support phenotypic screening approaches in drug discovery.

[From high content screening to target deconvolution: New insights for phenotypic approaches]

The advent of the molecular biology and the completion of the human genome sequencing prompted the pharmaceutical industry to progressively implement target-centric drug discovery strategies. However, concerns regarding the research and development productivity during the last ten years, combined with technological developments in high-content screening, automation, image analysis and artificial intelligence triggered a renewed interest for the phenotypic drug discovery approaches. Target-centric and phenotypic approaches are more and more considered complementary, hence, positioning the target deconvolution on the critical path. This review analyzes the evolution of the target-centric and phenotypic approaches, focusing more specifically on the high-content screening and the target deconvolution technologies currently available.

Phenotypic screening with target identification and validation in the discovery and development of E3 ligase modulators

The use of phenotypic screening was central to the discovery and development of novel thalidomide analogs, the IMiDs (immunomodulatory drugs) agents. With the discovery that these agents bind the E3 ligase, CRL4^CRBN, and alter its substrate specificity, there has been a great deal of endeavor to discover other small molecules that can modulate alternative E3 ligases. Furthermore, the chemical properties necessary for drug discovery and the rules by which neo-substrates are selected for degradation are being defined in the context of phenotypic alterations in specific cellular systems. This review gives a detailed summary of these recent advances and the methodologies being exploited to understand the mechanism of action of emerging protein degradation therapies.

Image-based profiling for drug discovery: due for a machine-learning upgrade?

Image-based profiling is a maturing strategy by which the rich information present in biological images is reduced to a multidimensional profile, a collection of extracted image-based features. These profiles can be mined for relevant patterns, revealing unexpected biological activity that is useful for many steps in the drug discovery process. Such applications include identifying disease-associated screenable phenotypes, understanding disease mechanisms and predicting a drug's activity, toxicity or mechanism of action. Several of these applications have been recently validated and have moved into production mode within academia and the pharmaceutical industry. Some of these have yielded disappointing results in practice but are now of renewed interest due to improved machine-learning strategies that better leverage image-based information. Although challenges remain, novel computational technologies such as deep learning and single-cell methods that better capture the biological information in images hold promise for accelerating drug discovery.

"Two-Cell Assemblage" Assay: A Simple in vitro Method for Screening Hair Growth-Promoting Compounds

Alopecia arises due to inadequate hair follicle (HF) stem cell activation or proliferation, resulting in prolongation of the telogen phase of the hair cycle. Increasing therapeutic and cosmetic demand for alleviating alopecia has driven research toward the discovery or synthesis of novel compounds that can promote hair growth by inducing HF stem cell activation or proliferation and initiating the anagen phase. Although several methods for evaluating the hair growth-promoting effects of candidate compounds are being used, most of these methods are difficult to use for large scale simultaneous screening of various compounds. Herein, we introduce a simple and reliable in vitro assay for the simultaneous screening of the hair growth-promoting effects of candidate compounds on a large scale. In this study, we first established a 3D co-culture system of human dermal papilla (hDP) cells and human outer root sheath (hORS) cells in an ultra-low attachment 96-well plate, where the two cell types constituted a polar elongated structure, named "two-cell assemblage (TCA)." We observed that the long axis length of the TCA gradually increased for 5 days, maintaining biological functional integrity as reflected by the increased expression levels of hair growth-associated genes after treatment with hair growth-promoting molecules. Interestingly, the elongation of the TCA was more prominent following treatment with the hair growth-promoting molecules (which occurred in a dose-dependent manner), compared to the control group (p < 0.05). Accordingly, we set the long axis length of the TCA as an endpoint of this assay, using a micro confocal high-content imaging system to measure the length, which can provide reproducible and reliable results in an adequate timescale. The advantages of this assay are: (i) it is physiologically and practically advantageous as it uses 3D cultured two-type human cells which are easily available; (ii) it is simple as it uses length as the only endpoint; and (iii) it is a high throughput system, which screens various compounds simultaneously. In conclusion, the "TCA" assay could serve as an easy and reliable method to validate the hair growth-promoting effect of a large volume of library molecules.

Future Perspective of Diabetic Animal Models

Objective

The need of today’s research is to develop successful and reliable diabetic animal models for understanding the disease susceptibility and pathogenesis. Enormous success of animal models had already been acclaimed for identifying key genetic and environmental factors like Idd loci and effects of microorganisms including the gut microbiota. Furthermore, animal models had also helped in identifying many therapeutic targets and strategies for immune-intervention. In spite of a quite success, we have acknowledged that many of the discovered immunotherapies are working on animals and did not have a significant impact on human. Number of animal models were developed in the past to accelerate drug discovery pipeline. However, due to poor initial screening and assessment on inequivalent animal models, the percentage of drug candidates who succeeded during clinical trials was very low. Therefore, it is essential to bridge this gap between pre-clinical research and clinical trial by validating the existing animal models for consistency.

Results and Conclusion

In this review, we have discussed and evaluated the significance of animal models on behalf of published data on PUBMED. Amongst the most popular diabetic animal models, we have selected six animal models (e.g. BioBreeding rat, “LEW IDDM rat”, “Nonobese Diabetic (NOD) mouse”, “STZ RAT”, “LEPR Mouse” and “Zucker Diabetic Fatty (ZDF) rat” and ranked them as per their published literature on PUBMED. Moreover, the vision and brief imagination for developing an advanced and robust diabetic model of 21^st century was discussed with the theme of one mice-one human concept including organs-on-chips.

Phenotypic Screening in C. elegans as a Tool for the Discovery of New Geroprotective Drugs

Population aging is one of the largest challenges of the 21st century. As more people live to advanced ages, the prevalence of age-related diseases and disabilities will increase placing an ever larger burden on our healthcare system. A potential solution to this conundrum is to develop treatments that prevent, delay or reduce the severity of age-related diseases by decreasing the rate of the aging process. This ambition has been accomplished in model organisms through dietary, genetic and pharmacological interventions. The pharmacological approaches hold the greatest opportunity for successful translation to the clinic. The discovery of such pharmacological interventions in aging requires high-throughput screening strategies. However, the majority of screens performed for geroprotective drugs in C. elegans so far are rather low throughput. Therefore, the development of high-throughput screening strategies is of utmost importance.

Multi-line fluorescence scanning microscope for multi-focal imaging with unlimited field of view

Confocal scanning microscopy is the de facto standard modality for fluorescence imaging. Point scanning, however, leads to a limited throughput and makes the technique unsuitable for fast multi-focal scanning over large areas. We propose an architecture for multi-focal fluorescence imaging that is scalable to large area imaging. The design is based on the concept of line scanning with continuous 'push broom' scanning. Instead of a line sensor, we use an area sensor that is tilted with respect to the optical axis to acquire image data from multiple depths inside the sample simultaneously. A multi-line illumination where the lines span a plane conjugate to the tilted sensor is created by means of a diffractive optics design, implemented on a spatial light modulator. In particular, we describe a design that uses higher order astigmatism to generate focal lines of substantially constant peak intensity along the lines. The proposed method is suitable for fast 3D image acquisition with unlimited field of view, it requires no moving components except for the sample scanning stage, and provides intrinsic alignment of the simultaneously scanned focal slices. As proof of concept, we have scanned 9 focal slices simultaneously over an area of 36 mm² at 0.29 µm pixel size in object space. The projected ultimate throughput that can be realized with the proposed architecture is in excess of 100 Mpixel/s.

Chemical biology approaches targeting the actin cytoskeleton through phenotypic screening

The actin cytoskeleton is dysregulated in cancer, yet this critical cellular machinery has not translated as a druggable clinical target due to cardio-toxic side-effects. Many actin regulators are also considered undruggable, being structural proteins lacking clear functional sites suitable for targeted drug design. In this review, we discuss opportunities and challenges associated with drugging the actin cytoskeleton through its structural regulators, taking tropomyosins as a target example. In particular, we highlight emerging data acquisition and analysis trends driving phenotypic, imaging-based compound screening. Finally, we consider how the confluence of these trends is now bringing functionally integral machineries such as the actin cytoskeleton, and associated structural regulatory proteins, into an expanded repertoire of druggable targets with previously unexploited clinical potential.

High Content Screening in NHBE cells shows significantly reduced biological activity of flavoured e-liquids, when compared to cigarette smoke condensate

There is scientific agreement that the detrimental effects of cigarettes are produced by the formation of Harmful and Potentially Harmful Constituents from tobacco combustion and not by nicotine. For this reason numerous public health bodies and governments worldwide have indicated that e-cigarettes have a central role to play in tobacco harm reduction. In this study, high content screening (HCS) was used to compare the effects of neat e-liquids and 3R4F reference cigarette smoke condensate (CSC), which served as a positive control, in Normal Human Bronchial Epithelial (NHBE) cells. The endpoints measured covered cellular health, energy production and oxidative stress. Base liquids, with or without nicotine, and commercial, flavoured, nicotine-containing e-liquids (CFs), had little or no effect on cell viability and most HCS endpoints even at significantly higher concentrations (typically 100 times or higher) than 3R4F CSC. CSC induced a dose-dependent decrease of cell viability and triggered the response in all HCS endpoints. Effects of CFs were typically observed at or above 1%. CF Menthol was the most active flavour, with minimum effective concentrations 43 to 659 times higher than corresponding 3R4F CSC concentrations. Our results show a lower biological activity of e-liquids compared to cigarette smoke condensate in this experimental setting, across wide range of cellular endpoints.

Precision medicine review: rare driver mutations and their biophysical classification

How can biophysical principles help precision medicine identify rare driver mutations? A major tenet of pragmatic approaches to precision oncology and pharmacology is that driver mutations are very frequent. However, frequency is a statistical attribute, not a mechanistic one. Rare mutations can also act through the same mechanism, and as we discuss below, “latent driver” mutations may also follow the same route, with “helper” mutations. Here, we review how biophysics provides mechanistic guidelines that extend precision medicine. We outline principles and strategies, especially focusing on mutations that drive cancer. Biophysics has contributed profoundly to deciphering biological processes. However, driven by data science, precision medicine has skirted some of its major tenets. Data science embodies genomics, tissue- and cell-specific expression levels, making it capable of defining genome- and systems-wide molecular disease signatures. It classifies cancer driver genes/mutations and affected pathways, and its associated protein structural data guide drug discovery. Biophysics complements data science. It considers structures and their heterogeneous ensembles, explains how mutational variants can signal through distinct pathways, and how allo-network drugs can be harnessed. Biophysics clarifies how one mutation—frequent or rare—can affect multiple phenotypic traits by populating conformations that favor interactions with other network modules. It also suggests how to identify such mutations and their signaling consequences. Biophysics offers principles and strategies that can help precision medicine push the boundaries to transform our insight into biological processes and the practice of personalized medicine. By contrast, “phenotypic drug discovery,” which capitalizes on physiological cellular conditions and first-in-class drug discovery, may not capture the proper molecular variant. This is because variants of the same protein can express more than one phenotype, and a phenotype can be encoded by several variants.