Identification of 4-amino-2-Pyridones as new potent PCSK9 inhibitors: From phenotypic hit discovery to in vivo tolerability

Among the strategies to overcome the underperformance of statins in cardiovascular diseases (CVDs), the development of drugs targeting the Proprotein Convertase Subtilisin-like Kexin type 9 (PCSK9) is considered one of the most promising. However, only anti-PCSK9 biological drugs have been approved to date, and orally available small-molecules for the treatment of hypercholesterolemic conditions are still missing on the market. In the present work, we describe the application of a phenotypic approach to the identification and optimization of 4-amino-2-pyridone derivatives as a new chemotype with anti-PCSK9 activity. Starting from an in-house collection of compounds, functional assays on HepG2 cells followed by a chemistry-driven hit optimization campaign, led to the potent anti-PCSK9 candidate 5c. This compound, at 5 μM, totally blocked PCSK9 secretion from HepG2 cells, significantly increased LDL receptor (LDLR) expression, and acted cooperatively with simvastatin by reducing its induction of PCSK9 expression. Finally, compound 5c also proved to be well tolerated in C57BL/6J mice at the tested concentration (40 mg/kg) with no sign of toxicity or behavior modifications.

A Robust Phenotypic Screening Assay Utilizing Human Podocytes to Identify Agents that Modulate Lipid Droplets

Lipid droplets (LDs), initially thought to be mere lipid storage structures, are highly dynamic organelles with complex functions that control cell fate and behavior. In recent years, their relevance as therapeutic targets for a wide array of human diseases has been well established. Consequently, efforts to develop tools to study them have intensified, including assays that can accurately track LD levels in clinically relevant cell-based models. We previously reported that LD accumulation destines podocytes for lipotoxicity and cell death in renal diseases of metabolic and nonmetabolic origin. We also showed that LD accumulation in those cells serves as both a marker for disease progression and as a therapeutic target. Here, we describe a robust phenotypic screening method, using differentiated human podocytes, for identifying small-molecule compounds that rescue podocytes from LD accumulation and lipotoxicity under cellular stress. Major assay advances include 1) the use of a solvatochromic dye to improve LD staining, reduce background noise, and improve detection accuracy, 2) use of confocal imaging to reduce vertical overlap of LDs and enable accurate counting, 3) combining membrane and cytoskeleton stains to improve cell segmentation in confocal mode, and 4) use of an optimized spot detection algorithm that requires minimal configuration per individual run. The assay is robust and yields a Z-factor that is consistently >0.5.

Evidence for anti-inflammatory effects and modulation of neurotransmitter metabolism by Salvia officinalis L

Background

Cognitive health is of great interest to society, with neuroinflammation and systemic inflammation age-related risk factors that are linked to declines in cognitive performance. Several botanical ingredients have been suggested to have benefits in this area including Salvia officinalis (sage), which has shown anti-inflammatory effects and exhibited promising cognitive improvements in multiple human studies. The current study demonstrates anti-inflammatory effects for S. officinalis across a broad set of in vitro models in human cells, and adds further evidence to support modulation of acetylcholine and monoamine neurostransmitter levels as mechanisms that contribute towards the benefits of the herb on cognitive health.

Methods

The effect of S. officinalis extract on release of multiple cytokines and chemokines was measured in human primary intestinal epithelial cells treated with or without LPS stimulation, and Blood Brain Barrier (BBB) cells in presence or absence of recombinant IL-17A and/or Human IL-17RA/IL-17R Antibody. Antioxidant effects were also assessed in BBB cells incubated with the extract and H₂O₂. The anti-inflammatory effects of S. officinalis extract were further assessed based on clinically-relevant biomarker readouts across 12 human primary cell-based disease models of the BioMAP Diversity PLUS panel.

Results

S. officinalis showed significant attenuation of the release of most cytokines/chemokines into apical media in LPS-stimulated intestinal cells, but small increases in the release of markers including IL-6, IL-8 in basolateral media; where TNF-α was the only marker to be significantly reduced. S. officinalis attenuated the release of CRP and VCAM-1 from BBB cells under IL-17A induced conditions, and also decreased H₂O₂ induced ROS overproduction in these cells. Phenotypic profiling with the BioMAP Diversity PLUS Panel identified additional anti-inflammatory mediators, and based on a similarity search analysis suggested potential mechanistic similarity to caffeic acid and drugs known to inhibit COMT and MAO activity to modulate monoamine metabolism. Subsequent in vitro assessment showed that S. officinalis was able to inhibit the activity of these same enzymes.

Conclusions

S. officinalis extract showed anti-inflammatory effects across multiple human cell lines, which could potentially reduce peripheral inflammation and support cognitive health. S. officinalis extract also showed the ability to inhibit enzymes related to the metabolism of monoamine neurotransmitters, suggesting possible dopaminergic and serotonergic effects acting alongside proposed cholinergic effects to mediate acute cognitive performance benefits previously demonstrated for the extract.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03605-1.

elegans as an in vivo model system for the phenotypic drug discovery for treating paraquat poisoning

BACKGROUND

Paraquat (PQ) is an effective and widely used herbicide and causes numerous fatalities by accidental or voluntary ingestion. However, neither the final cytotoxic mechanism nor effective treatments for PQ poisoning have been discovered. Phenotypic drug discovery (PDD), which does not rely on the molecular mechanism of the diseases, is having a renaissance in recent years owing to its potential to address the incompletely understood complexity of diseases. Herein, the C. elegans PDD model was established to pave the way for the future phenotypic discovery of potential agents for treating PQ poisoning.

METHODS

C. elegans were treated with PQ-containing solid medium followed by statistical analysis of worm survival, pharyngeal pumping, and movement ability. Furthermore, coenzyme Q10 (CoQ10) was used to test the C. elegans model of PQ poisoning by measuring the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), mitochondrial morphology, and worm survival rate. Additionally, we used the classic mice model of PQ intoxication to evaluate the validity of the C. elegans model of PQ poisoning by measuring the effect of CoQ10 as a potential antidote for PQ poisoning.

RESULTS

In the C. elegans model of PQ poisoning, 5 mg/mL PQ increased the levels of ROS, MDA content, mitochondrial fragments, which significantly shortened the lifespan, while CoQ10 alleviated these phenotypes. In the mice model of PQ poisoning, CoQ10 increased the chance of survival in PQ poisoned mice while reducing ROS, MDA content in lung tissue and inhibiting PQ-induced lung edema. Moreover, CoQ10 alleviated the lung morphopathological changes induced by PQ.

CONCLUSION

Here we established a C. elegans model of PQ poisoning, whose validity was confirmed by the classic mice model of PQ intoxication.

Development of a chemogenomics library for phenotypic screening

With the development of advanced technologies in cell-based phenotypic screening, phenotypic drug discovery (PDD) strategies have re-emerged as promising approaches in the identification and development of novel and safe drugs. However, phenotypic screening does not rely on knowledge of specific drug targets and needs to be combined with chemical biology approaches to identify therapeutic targets and mechanisms of actions induced by drugs and associated with an observable phenotype. In this study, we developed a system pharmacology network integrating drug-target-pathway-disease relationships as well as morphological profile from an existing high content imaging-based high-throughput phenotypic profiling assay known as “Cell Painting”. Furthermore, from this network, a chemogenomic library of 5000 small molecules that represent a large and diverse panel of drug targets involved in diverse biological effects and diseases has been developed. Such a platform and a chemogenomic library could assist in the target identification and mechanism deconvolution of some phenotypic assays. The usefulness of the platform is illustrated through examples.

Discovery and mechanism of action studies of 4,6-diphenylpyrimidine-2-carbohydrazides as utrophin modulators for the treatment of Duchenne muscular dystrophy

Duchenne muscular dystrophy is a fatal disease with no cure, caused by lack of the cytoskeletal protein dystrophin. Upregulation of utrophin, a dystrophin paralogue, offers a potential therapy independent of mutation type. The failure of first-in-class utrophin modulator ezutromid/SMT C1100 in Phase II clinical trials necessitates development of compounds with better efficacy, physicochemical and ADME properties and/or complementary mechanisms. We have discovered and performed a preliminary optimisation of a novel class of utrophin modulators using an improved phenotypic screen, where reporter expression is derived from the full genomic context of the utrophin promoter. We further demonstrate through target deconvolution studies, including expression analysis and chemical proteomics, that this compound series operates via a novel mechanism of action, distinct from that of ezutromid.

Recent advances in phenotypic drug discovery

There is a great need for innovative new medicines to treat unmet medical needs. The discovery and development of innovative new medicines is extremely difficult, costly, and inefficient. In the last decade, phenotypic drug discovery (PDD) was reintroduced as a strategy to provide first-in-class medicines. PDD uses empirical, target-agnostic lead generation to identify pharmacologically active molecules and novel therapeutics which work through unprecedented drug mechanisms. The economic and scientific value of PDD is exemplified through game-changing medicines for hepatitis C virus, spinal muscular atrophy, and cystic fibrosis. In this short review, recent advances are noted for the implementation and de-risking of PDD (for compound library selection, biomarker development, mechanism identification, and safety studies) and the potential for artificial intelligence. A significant barrier in the decision to implement PDD is balancing the potential impact of a novel mechanism of drug action with an under-defined scientific path forward, with the desire to provide infrastructure and metrics to optimize return on investment, which a known mechanism provides. A means to address this knowledge gap in the future is to empower precompetitive research utilizing the empirical concepts of PDD to identify new mechanisms and pharmacologically active compounds.

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.

Detection and Quantification of Lipid Droplets in Differentiated Human Podocytes

Lipid droplets (LDs) are dynamic organelles that regulate the storage and homeostasis of intracellular triglycerides and other neutral lipids. Studies show that the number, morphology, and subcellular localization of LDs are altered in a growing number of diseases. As such, methodologies for imaging and quantifying LDs have become essential tools for detecting changes in cellular lipid metabolism, which could be an important indicator of disease onset or progression. We previously reported on the accumulation of LDs in podocytes of the kidney glomerulus in nephrological diseases of metabolic and non-metabolic origin. Here, we describe a high-content analysis (HCA) method for automated detection and quantification of LDs in differentiated human podocytes.

Utilization of Multidimensional Data in the Analysis of Ultra-High-Throughput High Content Phenotypic Screens

High Content Screening (HCS) platforms can generate large amounts of multidimensional data. To take full advantage of all the rich contextual information provided by these screens, a combination of traditional as well as nontraditional hit identification and prioritization strategies is required. Here, we describe the workflow and analytics of multidimensional high content data to differentiate, group, and prioritize hits.

An Endothelial Cell/Mesenchymal Stem Cell Coculture Cord Formation Assay to Model Vascular Biology In Vitro

Blood vessels are crucial components for normal tissue development and homeostasis, so it is not surprising that endothelial dysfunction and dysregulation results in a variety of different pathophysiological conditions. The large number of vascular-related disorders and the emergence of angiogenesis as a major hallmark of cancer has led to significant interest in the development of drugs that target the vasculature. While several in vivo models exist to study developmental and pathological states of blood vessels, few in vitro assays have been developed that capture the significant complexity of the vascular microenvironment. Here, we describe a high content endothelial colony forming cells (ECFC)/adipose-derived stem cell (ADSC) coculture assay that captures many elements of in vivo vascular biology and is ideal for in vitro screening of compounds for pro- or anti-angiogenic activities.

A phenotypic drug discovery study on thienodiazepine derivatives as inhibitors of T cell proliferation induced by CD28 co-stimulation leads to the discovery of a first bromodomain inhibitor

A phenotypic screening of thienodiazepines derived from a hit compound found through a binding assay targeting co-stimulatory molecules on T cells and antigen presenting cells successfully led to the discovery of a thienotriazolodiazepine compound (7f) possessing potent immunosuppressive activity. A chemical biology approach has succeeded in revealing that 7f is a first inhibitor of epigenetic bromodomain-containing proteins. 7f is expected to become an anti-cancer agent as well as an immunosuppressive agent.