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Excessive activity of the hormone angiotensin II (AngII) is known to contribute to the pathogenesis of multiple cardiovascular diseases, including atherosclerosis, vascular remodeling, and hypertension, primarily through inducing gene expression changes. In this study, we identified LMCD1 (LIM and cysteine-rich domains 1, also known as Dyxin), primarily recognized as a transcription co-factor involved in various oncogenic processes, cardiac hypertrophy, and vascular remodeling, as a potential key factor in AngII-mediated effects in vascular smooth muscle cells (VSMCs). We demonstrated that AngII upregulates LMCD1 expression in primary rat VSMCs through type 1 angiotensin receptor (AT1-R) activation, leading to calcium signaling and p38 MAPK pathway activation. Additionally, we also demonstrated in A7r5 vascular smooth muscle cells that LMCD1 protein overexpression results in enhanced cell proliferation and cell migration. Our findings provide insights into the mechanisms by which AngII mediates changes in LMCD1 expression. The elevated expression of LMCD1 enhanced the cell proliferation and migration in VSMCs in vitro experiments, suggesting that LMCD1 may be an important factor in vascular remodeling and the pathogenesis of severe cardiovascular diseases. These results raise the possibility that LMCD1 could be a promising pharmacological target in the cardiovascular dysfunctions associated with AT1-R overactivation.

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts.

BackgroundOsteoclasts play a crucial role in the maintenance, repair, and remodeling of bones of the adult vertebral skeleton due to their bone resorption capability. Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are associated with increased activity of osteoclasts.ObjectivesOur study aimed to investigate the dynamic proteomic changes during osteoclast differentiation in healthy donors, in RA, and PsA.MethodsBlood samples of healthy donors, RA, and PsA patients were collected, and monocytes were isolated and differentiated into osteoclasts in vitro using macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor κB ligand (RANK-L). Mass spectrometry-based proteomics was used to analyze proteins from cell lysates. The expression changes were analyzed with Gene Set Enrichment Analysis (GSEA).ResultsThe analysis of the proteomic changes revealed that during the differentiation of the human osteoclasts, expression of the proteins involved in metabolic activity, secretory function, and cell polarity is increased; by contrast, signaling pathways involved in the immune functions are downregulated. Interestingly, the differences between cells of healthy donors and RA/PsA patients are most pronounced after the final steps of differentiation to osteoclasts. In addition, both in RA and PsA the differentiation is characterized by decreased metabolic activity, associated with various immune pathway activities; furthermore by accelerated cytokine production in RA.ConclusionsOur results shed light on the characteristic proteomic changes during human osteoclast differentiation and expression differences in RA and PsA, which reveal important pathophysiological insights in both diseases.

The urine concentrating function of the kidney is essential to maintain the water homeostasis of the human body. It is mainly regulated by the arginine-vasopressin (AVP), which targets the type 2 vasopressin receptor (V2R) in the kidney. The inability of V2R to respond to AVP stimulation leads to decreased urine concentration and congenital nephrogenic diabetes insipidus (NDI). NDI is characterized by polyuria, polydipsia, and hyposthenuria. In this study, we identified a point mutation (S127F) in the AVPR2 gene of an NDI patient, and we characterized the impaired function of the V2R mutant in HEK293 cells. Based on our data, the S127F-V2R mutant is almost exclusively located intracellularly in the endoplasmic reticulum (ER), and very few receptors were detected at the cell surface, where the receptor can bind to AVP. The overexpressed S127F-V2R mutant receptor has negligible cAMP generation capability compared to the wild-type receptor in response to AVP stimulation. Since certain misfolded mutant proteins, that are retained in the ER, can be rescued by pharmacological chaperones, we examined the potential rescue effects of two pharmacochaperones on the S127F-V2R. We found that pretreatment with both tolvaptan (an established V2R inverse agonist) and MCF14 compound (a cell-permeable high-affinity agonist for the V2R) were capable of partially restoring the cAMP generating function of the receptor in response to vasopressin stimulation. According to our data, both cell permeant agonists and antagonists can function as pharmacochaperones, and serve as the starting compounds to develop medicines for patients carrying the S127F mutation.

Angiotensin II (AngII) is a vasoactive peptide hormone, which, under pathological conditions, contributes to the development of cardiovascular diseases. Oxysterols, including 25-hydroxycholesterol (25-HC), the product of cholesterol-25-hydroxylase (CH25H), also have detrimental effects on vascular health by affecting vascular smooth muscle cells (VSMCs). We investigated AngII-induced gene expression changes in VSMCs to explore whether AngII stimulus and 25-HC production have a connection in the vasculature. RNA-sequencing revealed that Ch25h is significantly upregulated in response to AngII stimulus. The Ch25h mRNA levels were elevated robustly (~50-fold) 1 h after AngII (100 nM) stimulation compared to baseline levels. Using inhibitors, we specified that the AngII-induced Ch25h upregulation is type 1 angiotensin II receptor- and Gq/11 activity-dependent. Furthermore, p38 MAPK has a crucial role in the upregulation of Ch25h. We performed LC-MS/MS to identify 25-HC in the supernatant of AngII-stimulated VSMCs. In the supernatants, 25-HC concentration peaked 4 h after AngII stimulation. Our findings provide insight into the pathways mediating AngII-induced Ch25h upregulation. Our study elucidates a connection between AngII stimulus and 25-HC production in primary rat VSMCs. These results potentially lead to the identification and understanding of new mechanisms in the pathogenesis of vascular impairments.

(1) Adeno-associated viruses (AAV) are safe and efficient gene therapy vectors with promising results in the treatment of several diseases. Extracellular vesicles (EV) are phospholipid bilayer-surrounded structures carrying several types of lipids, proteins, and nucleic acids with the ability to cross biological barriers. EV-associated AAVs might serve as new and efficient gene therapy vectors considering that they carry the benefits of both AAVs and EVs. (2) We tested vesicle-associated AAVs and vesicles mixed with AAVs on two major cell types of the central nervous system: a neural cell line (N2A) and primary astrocyte cells. (3) In contrast to previously published in vivo observations, the extracellular vesicle packaging did not improve but, in the case of primary astrocyte cells, even inhibited the infection capacity of the AAV particles. The observed effect was not due to the inhibitory effects of the vesicles themselves, since mixing the AAVs with extracellular vesicles did not change the effectiveness. (4) Our results suggest that improvement of the in vivo efficacy of the EV-associated AAV particles is not due to the enhanced interaction between the AAV and the target cells, but most likely to the improved delivery of the AAVs through tissue barriers and to the shielding of AAVs from neutralizing antibodies.

Activation of the type I angiotensin receptor (AT1-R) in vascular smooth muscle cells (VSMCs) plays a crucial role in the regulation of blood pressure; however, it is also responsible for the development of pathological conditions such as vascular remodeling, hypertension and atherosclerosis. Stimulation of the VSMC by angiotensin II (AngII) promotes a broad variety of biological effects, including gene expression changes. In this paper, we have taken an integrated approach in which an analysis of AngII-induced gene expression changes has been combined with the use of small-molecule inhibitors and lentiviral-based gene silencing, to characterize the mechanism of signal transduction in response to AngII stimulation in primary rat VSMCs. We carried out Affymetrix GeneChip experiments to analyze the effects of AngII stimulation on gene expression; several genes, including DUSP5, DUSP6, and DUSP10, were identified as upregulated genes in response to stimulation. Since various dual-specificity MAPK phosphatase (DUSP) enzymes are important in the regulation of mitogen-activated protein kinase (MAPK) signaling pathways, these genes have been selected for further analysis. We investigated the kinetics of gene-expression changes and the possible signal transduction processes that lead to altered expression changes after AngII stimulation. Our data shows that the upregulated genes can be stimulated through multiple and synergistic signal transduction pathways. We have also found in our gene-silencing experiments that epidermal growth factor receptor (EGFR) transactivation is not critical in the AngII-induced expression changes of the investigated genes. Our data can help us understand the details of AngII-induced long-term effects and the pathophysiology of AT1-R. Moreover, it can help to develop potential interventions for those symptoms that are induced by the over-functioning of this receptor, such as vascular remodeling, cardiac hypertrophy or atherosclerosis.

G protein-coupled receptors (GPCRs) regulate every aspect of kidney function by mediating the effects of various endogenous and exogenous substances. A key concept in GPCR function is biased signalling, whereby certain ligands may selectively activate specific pathways within the receptor’s signalling repertoire. For example, different agonists may induce biased signalling by stabilizing distinct active receptor conformations — a concept that is supported by advances in structural biology. However, the processes underlying functional selectivity in receptor signalling are extremely complex, involving differences in subcellular compartmentalization and signalling dynamics. Importantly, the molecular mechanisms of spatiotemporal bias, particularly its connection to ligand binding kinetics, have been detailed for GPCRs critical to kidney function, such as the AT1 angiotensin receptor (AT1R), V2 vasopressin receptor (V2R) and the parathyroid hormone 1 receptor (PTH1R). This expanding insight into the multifaceted nature of biased signalling paves the way for innovative strategies for targeting GPCR functions; the development of novel biased agonists may represent advanced pharmacotherapeutic approaches to the treatment of kidney diseases and related systemic conditions, such as hypertension, diabetes and heart failure.G protein-coupled receptors (GPCRs) elicit cellular responses to an array of stimuli to regulate the function of virtually all organs. The diverse functions of GPCRs are determined by their expression profiles and their ability to adopt different active and inactive conformations, resulting in functional selectivity or biased signalling. This Review describes the mechanisms and consequences of biased GPCR signalling with a focus on GPCRs of relevance to the kidney.

It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors (“garlic,” “fish,” “sweet,” “fruit,” “burnt,” “spices,” “flower,” and “sour”). Regularized linear models performed nearly as well as random forest–based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule.

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. Resistance to first line treatment is a major hurdle in cancer treatment, that can be overcome with drug combinations. Here, the authors provide a large drug combination screen across cancer cell lines to benchmark crowdsourced methods and to computationally predict drug synergies.