KD025 Is a Casein Kinase 2 Inhibitor That Protects Against Glucolipotoxicity in ß-Cells.

Glucolipotoxicity (GLT), in which elevated levels of glucose and fatty acids have deleterious effects on ß-cell biology, is thought to be one of the major contributors in progression of type 2 diabetes. In search of novel small molecules that protect ß-cells against GLT, we previously discovered KD025, an inhibitor of Rho-associated coiled-coil-containing kinase isoform 2 (ROCK2), as a GLT-protective compound in INS-1E cells and dissociated human islets. To further understand the mechanism of action of KD025, we found that pharmacological and genetic inhibition of ROCK2 was not responsible for the protective effects of KD025 against GLT. Instead, kinase profiling revealed that KD025 potently inhibits catalytic subunits of casein kinase 2 (CK2), a constitutively active serine/threonine kinase. We experimentally verified that the inhibition of one of the catalytic subunits of casein kinase 2, CK2A1, but not CK2A2, improved cell viability when challenged with GLT. We conclude that KD025 inhibits CK2 to protect ß-cells from GLT.

Fluorescein-based sensors to purify human α-cells for functional and transcriptomic analyses.

Pancreatic α-cells secrete glucagon, an insulin counter-regulatory peptide hormone critical for the maintenance of glucose homeostasis. Investigation of the function of human α-cells remains a challenge due to the lack of cost-effective purification methods to isolate high-quality α-cells from islets. Here, we use the reaction-based probe diacetylated Zinpyr1 (DA-ZP1) to introduce a novel and simple method for enriching live α-cells from dissociated human islet cells with ~95% purity. The α-cells, confirmed by sorting and immunostaining for glucagon, were cultured up to 10 days to form α-pseudoislets. The α-pseudoislets could be maintained in culture without significant loss of viability, and responded to glucose challenge by secreting appropriate levels of glucagon. RNA-sequencing analyses (RNA-seq) revealed that expression levels of key α-cell identity genes were sustained in culture while some of the genes such as DLK1, GSN, SMIM24 were altered in α-pseudoislets in a time-dependent manner. In conclusion, we report a method to sort human primary α-cells with high purity that can be used for downstream analyses such as functional and transcriptional studies.

Excess pancreatic elastase alters acinar-ß cell communication by impairing the mechano-signaling and the PAR2 pathways.

Type 1 (T1D) or type 2 diabetes (T2D) are caused by a deficit of functional insulin-producing ß cells. Thus, the identification of ß cell trophic agents could allow the development of therapeutic strategies to counteract diabetes. The discovery of SerpinB1, an elastase inhibitor that promotes human ß cell growth, prompted us to hypothesize that pancreatic elastase (PE) regulates ß cell viability. Here, we report that PE is up-regulated in acinar cells and in islets from T2D patients, and negatively impacts ß cell viability. Using high-throughput screening assays, we identified telaprevir as a potent PE inhibitor that can increase human and rodent ß cell viability in vitro and in vivo and improve glucose tolerance in insulin-resistant mice. Phospho-antibody microarrays and single-cell RNA sequencing analysis identified PAR2 and mechano-signaling pathways as potential mediators of PE. Taken together, our work highlights PE as a potential regulator of acinar-ß cell crosstalk that acts to limit ß cell viability, leading to T2D.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity.

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

Predicting compound activity from phenotypic profiles and chemical structures.

Predicting assay results for compounds virtually using chemical structures and phenotypic profiles has the potential to reduce the time and resources of screens for drug discovery. Here, we evaluate the relative strength of three high-throughput data sources-chemical structures, imaging (Cell Painting), and gene-expression profiles (L1000)-to predict compound bioactivity using a historical collection of 16,170 compounds tested in 270 assays for a total of 585,439 readouts. All three data modalities can predict compound activity for 6-10% of assays, and in combination they predict 21% of assays with high accuracy, which is a 2 to 3 times higher success rate than using a single modality alone. In practice, the accuracy of predictors could be lower and still be useful, increasing the assays that can be predicted from 37% with chemical structures alone up to 64% when combined with phenotypic data. Our study shows that unbiased phenotypic profiling can be leveraged to enhance compound bioactivity prediction to accelerate the early stages of the drug-discovery process.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity.

Cellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism. Highlights: FALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effectsFALCON is applicable to many and diverse cell typesA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidityNew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for diseaseC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling.

Reference compounds for characterizing cellular injury in high-content cellular morphology assays.

Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.

A general approach to identify cell-permeable and synthetic anti-CRISPR small molecules.

The need to control the activity and fidelity of CRISPR-associated nucleases has resulted in a demand for inhibitory anti-CRISPR molecules. The small-molecule inhibitor discovery platforms available at present are not generalizable to multiple nuclease classes, only target the initial step in the catalytic activity and require high concentrations of nuclease, resulting in inhibitors with suboptimal attributes, including poor potency. Here we report a high-throughput discovery pipeline consisting of a fluorescence resonance energy transfer-based assay that is generalizable to contemporary and emerging nucleases, operates at low nuclease concentrations and targets all catalytic steps. We applied this pipeline to identify BRD7586, a cell-permeable small-molecule inhibitor of SpCas9 that is twofold more potent than other inhibitors identified to date. Furthermore, unlike the reported inhibitors, BRD7586 enhanced SpCas9 specificity and its activity was independent of the genomic loci, DNA-repair pathway or mode of nuclease delivery. Overall, these studies describe a general pipeline to identify inhibitors of contemporary and emerging CRISPR-associated nucleases.

SMNDC1 links chromatin remodeling and splicing to regulate pancreatic hormone expression.

Insulin expression is primarily restricted to the pancreatic ß cells, which are physically or functionally depleted in diabetes. Identifying targetable pathways repressing insulin in non-ß cells, particularly in the developmentally related glucagon-secreting α cells, is an important aim of regenerative medicine. Here, we perform an RNA interference screen in a murine α cell line to identify silencers of insulin expression. We discover that knockdown of the splicing factor Smndc1 triggers a global repression of α cell gene-expression programs in favor of increased ß cell markers. Mechanistically, Smndc1 knockdown upregulates the ß cell transcription factor Pdx1 by modulating the activities of the BAF and Atrx chromatin remodeling complexes. SMNDC1's repressive role is conserved in human pancreatic islets, its loss triggering enhanced insulin secretion and PDX1 expression. Our study identifies Smndc1 as a key factor connecting splicing and chromatin remodeling to the control of insulin expression in human and mouse islet cells.

Phenotypic Screening for Small Molecules that Protect ß-Cells from Glucolipotoxicity.

Type 2 diabetes is marked by progressive ß-cell failure, leading to loss of ß-cell mass. Increased levels of circulating glucose and free fatty acids associated with obesity lead to ß-cell glucolipotoxicity. There are currently no therapeutic options to address this facet of ß-cell loss in obese type 2 diabetes patients. To identify small molecules capable of protecting ß-cells, we performed a high-throughput screen of 20,876 compounds in the rat insulinoma cell line INS-1E in the presence of elevated glucose and palmitate. We found 312 glucolipotoxicity-protective small molecules (1.49% hit rate) capable of restoring INS-1E viability, and we focused on 17 with known biological targets. 16 of the 17 compounds were kinase inhibitors with activity against specific families including but not limited to cyclin-dependent kinases (CDK), PI-3 kinase (PI3K), Janus kinase (JAK), and Rho-associated kinase 2 (ROCK2). 7 of the 16 kinase inhibitors were PI3K inhibitors. Validation studies in dissociated human islets identified 10 of the 17 compounds, namely, KD025, ETP-45658, BMS-536924, AT-9283, PF-03814735, torin-2, AZD5438, CP-640186, ETP-46464, and GSK2126458 that reduced glucolipotoxicity-induced ß-cell death. These 10 compounds decreased markers of glucolipotoxicity including caspase activation, mitochondrial depolarization, and increased calcium flux. Together, these results provide a path forward toward identifying novel treatments to preserve ß-cell viability in the face of glucolipotoxicity.

Small-molecule discovery in the pancreatic beta cell.

The pancreatic beta cell is the only cell type in the body responsible for insulin secretion, and thus plays a unique role in the control of glucose homeostasis. The loss of beta-cell mass and function plays an important role in both type 1 and type 2 diabetes. Thus, using chemical biology to identify small molecules targeting the beta cell could be an important component to developing future therapeutics for diabetes. This strategy provides an attractive path toward increasing beta-cell numbers in vivo. A regenerative strategy involves enhancing proliferation, differentiation, or neogenesis. On the other hand, protecting beta cells from cell death, or improving maturity and function, could preserve beta-cell mass. Here, we discuss the current state of chemical matter available to study beta-cell regeneration, and how they were discovered.

Long-Term Safety and Efficacy of Tocilizumab in Early Systemic Sclerosis-Interstitial Lung Disease: Open-Label Extension of a Phase 3 Randomized Controlled Trial.

Rationale: Tocilizumab, an anti-IL-6 receptor antibody, had no statistically significant effect on skin sclerosis but preserved lung function over 48 weeks in patients with early systemic sclerosis (SSc)-associated interstitial lung disease (ILD) in a phase 3 randomized controlled trial. Objectives: Assess long-term safety and efficacy of tocilizumab. Methods: Adults with diffuse cutaneous SSc for ⩽60 months and elevated acute-phase reactants, including those with ILD, received weekly placebo or tocilizumab 162 mg subcutaneously in the 48-week, double-blind period and then open-label tocilizumab from Weeks 48 to 96 (placebo-tocilizumab; continuous-tocilizumab). Measurements and Main Results: Eighty-two of 107 patients in the placebo-tocilizumab group and 85 of 105 patients in the continuous-tocilizumab group completed 96 weeks. Mean age and disease duration were 48 years and 23 months; high-resolution computed tomography revealed ILD in 61%. Mean (95% confidence interval [CI]) change in modified Rodnan skin score from baseline to week 96 was -8.4 (-10.0 to -6.8) for placebo-tocilizumab and -9.6 (-10.9 to -8.4) for continuous-tocilizumab. Mean (95% CI) change in FVC (percent predicted) from baseline to week 96 was -3.3 (-5.1 to -1.5) for placebo-tocilizumab and -0.5 (-2.4 to 1.3) for continuous-tocilizumab among completers and, in a post hoc analysis, -4.1 (-6.7 to -1.6) and -0.6 (-3.1 to 2.0), respectively, among completers with ILD (mean [95% CI] change from Weeks 48 to 96: 0.9 [-0.8 to 2.7] and -0.4 [-2.3 to 1.5], respectively). Rates per 100 patient-years of serious adverse events from Weeks 48 to 96 were 14.8 for placebo-tocilizumab and 15.8 for continuous-tocilizumab. Conclusions: Tocilizumab preserved lung function, slowing decline in FVC, in patients with SSc, including those with ILD. Long-term safety was consistent with the known safety profile of tocilizumab. Clinical trial registered with www.clinicaltrials.gov (NCT02453256).

Computational repurposing of therapeutic small molecules from cancer to pulmonary hypertension.

Cancer therapies are being considered for treating rare noncancerous diseases like pulmonary hypertension (PH), but effective computational screening is lacking. Via transcriptomic differential dependency analyses leveraging parallels between cancer and PH, we mapped a landscape of cancer drug functions dependent upon rewiring of PH gene clusters. Bromodomain and extra-terminal motif (BET) protein inhibitors were predicted to rely upon several gene clusters inclusive of galectin-8 (LGALS8). Correspondingly, LGALS8 was found to mediate the BET inhibitor­dependent control of endothelial apoptosis, an essential role for PH in vivo. Separately, a piperlongumine analog's actions were predicted to depend upon the iron-sulfur biogenesis gene ISCU. Correspondingly, the analog was found to inhibit ISCU glutathionylation, rescuing oxidative metabolism, decreasing endothelial apoptosis, and improving PH. Thus, we identified crucial drug-gene axes central to endothelial dysfunction and therapeutic priorities for PH. These results establish a wide-ranging, network dependency platform to redefine cancer drugs for use in noncancerous conditions.

Addressing Compound Reactivity and Aggregation Assay Interferences: Case Studies of Biochemical High-Throughput Screening Campaigns Benefiting from the National Institutes of Health Assay Guidance Manual Guidelines.

Compound-dependent assay interferences represent a continued burden in drug and chemical probe discovery. The open-source National Institutes of Health/National Center for Advancing Translational Sciences (NIH/NCATS) Assay Guidance Manual (AGM) established an "Assay Artifacts and Interferences" section to address different sources of artifacts and interferences in biological assays. In addition to the frequent introduction of new chapters in this important topic area, older chapters are periodically updated by experts from academia, industry, and government to include new technologies and practices. Section chapters describe many best practices for mitigating and identifying compound-dependent assay interferences. Using two previously reported biochemical high-throughput screening campaigns for small-molecule inhibitors of the epigenetic targets Rtt109 and NSD2, the authors review best practices and direct readers to high-yield resources in the AGM and elsewhere for the mitigation and identification of compound-dependent reactivity and aggregation assay interferences.

The Use of Informer Sets in Screening: Perspectives on an Efficient Strategy to Identify New Probes.

Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the "wrong" compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating "informer sets" for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.

An expanded universe of cancer targets.

The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.