Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV.

The emergence and global spread of SARS-CoV-2 has resulted in the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. Here we report a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactomes of both viruses, as well as their influence on the transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon infection with SARS-CoV-2 and SARS-CoV at different levels and enabled identification of distinct and common molecular mechanisms of these closely related coronaviruses. The TGF-ß pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy was specifically dysregulated by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that could be targeted by existing drugs and may be used to guide rational design of virus- and host-directed therapies, which we exemplify by identifying inhibitors of kinases and matrix metalloproteases with potent antiviral effects against SARS-CoV-2.

Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors.

Medicinal chemistry has discovered thousands of potent protein and lipid kinase inhibitors. These may be developed into therapeutic drugs or chemical probes to study kinase biology. Because of polypharmacology, a large part of the human kinome currently lacks selective chemical probes. To discover such probes, we profiled 1,183 compounds from drug discovery projects in lysates of cancer cell lines using Kinobeads. The resulting 500,000 compound-target interactions are available in ProteomicsDB and we exemplify how this molecular resource may be used. For instance, the data revealed several hundred reasonably selective compounds for 72 kinases. Cellular assays validated GSK986310C as a candidate SYK (spleen tyrosine kinase) probe and X-ray crystallography uncovered the structural basis for the observed selectivity of the CK2 inhibitor GW869516X. Compounds targeting PKN3 were discovered and phosphoproteomics identified substrates that indicate target engagement in cells. We anticipate that this molecular resource will aid research in drug discovery and chemical biology.

Optimization of the Lead Compound NVP-BHG712 as a Colorectal Cancer Inhibitor.

The ephrin type-A receptor 2 (EPHA2) kinase belongs to the largest family of receptor tyrosine kinases. There are several indications of an involvement of EPHA2 in the development of infectious diseases and cancer. Despite pharmacological potential, EPHA2 is an under-examined target protein. In this study, we synthesized a series of derivatives of the inhibitor NVP-BHG712 and triazine-based compounds. These compounds were evaluated to determine their potential as kinase inhibitors of EPHA2, including elucidation of their binding mode (X-ray crystallography), affinity (microscale thermophoresis), and selectivity (Kinobeads assay). Eight inhibitors showed affinities in the low-nanomolar regime (KD <10 nM). Testing in up to seven colon cancer cell lines that express EPHA2 reveals that several derivatives feature promising effects for the control of human colon carcinoma. Thus, we have developed a set of powerful tool compounds for fundamental new research on the interplay of EPH receptors in a cellular context.

Discovery of Potent and Exquisitely Selective Inhibitors of Kinase CK1 with Tunable Isoform Selectivity.

Casein kinases 1 (CK1) are key signaling molecules that have emerged recently as attractive therapeutic targets in particular for the treatment of hematological malignancies. Herein, we report the identification of a new class of potent and highly selective inhibitors of CK1α, δ and ϵ. Based on their optimal in vitro and in vivo profiles and their exclusive selectivity, MU1250, MU1500 and MU1742 were selected as quality chemical probes for those CK1 isoforms. At proper concentrations, MU1250 and MU1500 allow for specific targeting of CK1δ or dual inhibition of CK1δ/ϵ in cells. The compound MU1742 also efficiently inhibits CK1α and, to our knowledge, represents the first potent and highly selective inhibitor of this enzyme. In addition, we demonstrate that the central 1H-pyrrolo[2,3-b]pyridine-imidazole pharmacophore can be used as the basis of highly selective inhibitors of other therapeutically relevant protein kinases, e.g. p38α, as exemplified by the compound MU1299.

ProteomicsDB: a multi-omics and multi-organism resource for life science research.

ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

CiRCus: A Framework to Enable Classification of Complex High-Throughput Experiments.

Despite the increasing use of high-throughput experiments in molecular biology, methods for evaluating and classifying the acquired results have not kept pace, requiring significant manual efforts to do so. Here, we present CiRCus, a framework to generate custom machine learning models to classify results from high-throughput proteomics binding experiments. We show the experimental procedure that guided us to the layout of this framework as well as the usage of the framework on an example data set consisting of 557 166 protein/drug binding curves achieving an AUC of 0.9987. By applying our classifier to the data, only 6% of the data might require manual investigation. CiRCus bundles two applications, a minimal interface to label a training data set (CindeR) and an interface for the generation of random forest classifiers with optional optimization of pretrained models (CurveClassification). CiRCus is available on https://github.com/kusterlab accompanied by an in-depth user manual and video tutorial.

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics.

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS.

Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC-MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC-MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC-MS/MS is suitable for a broad range of proteomic applications.

Repurposing human kinase inhibitors to create an antibiotic active against drug-resistant Staphylococcus aureus, persisters and biofilms.

New drugs are desperately needed to combat methicillin-resistant Staphylococcus aureus (MRSA) infections. Here, we report screening commercial kinase inhibitors for antibacterial activity and found the anticancer drug sorafenib as major hit that effectively kills MRSA strains. Varying the key structural features led to the identification of a potent analogue, PK150, that showed antibacterial activity against several pathogenic strains at submicromolar concentrations. Furthermore, this antibiotic eliminated challenging persisters as well as established biofilms. PK150 holds promising therapeutic potential as it did not induce in vitro resistance, and shows oral bioavailability and in vivo efficacy. Analysis of the mode of action using chemical proteomics revealed several targets, which included interference with menaquinone biosynthesis by inhibiting demethylmenaquinone methyltransferase and the stimulation of protein secretion by altering the activity of signal peptidase IB. Reduced endogenous menaquinone levels along with enhanced levels of extracellular proteins of PK150-treated bacteria support this target hypothesis. The associated antibiotic effects, especially the lack of resistance development, probably stem from the compound's polypharmacology.

Chemoproteomic Selectivity Profiling of PIKK and PI3K Kinase Inhibitors.

Chemical proteomic approaches utilizing immobilized, broad-selective kinase inhibitors (Kinobeads) have proven valuable for the elucidation of a compound's target profile under close-to-physiological conditions and often revealed potentially synergistic or toxic off-targets. Current Kinobeads enrich more than 300 native protein kinases from cell line or tissue lysates but do not systematically cover phosphatidylinositol 3-kinases (PI3Ks) and phosphatidylinositol 3-kinase-related kinases (PIKKs). Some PIKKs and PI3Ks show aberrant activation in many human diseases and are indeed validated drug targets. Here, we report the development of a novel version of Kinobeads that extends kinome coverage to these proteins. This is achieved by inclusion of two affinity probes derived from the clinical PI3K/MTOR inhibitors Omipalisib and BGT226. We demonstrate the utility of the new affinity matrix by the profiling of 13 clinical and preclinical PIKK/PI3K inhibitors. The large discrepancies between the PI3K affinity values obtained and reported results from recombinant assays led us to perform a phosphoproteomic experiment showing that the chemoproteomic assay is the better approximation of PI3K inhibitor action in cellulo. The results further show that NVP-BEZ235 is not a PI3K inhibitor. Surprisingly, the designated ATM inhibitor CP466722 was found to bind strongly to ALK2, identifying a new chemotype for drug discovery to treat fibrodysplasia ossificans progressiva.

Adaptive Resistance to EGFR-Targeted Therapy by Calcium Signaling in NSCLC Cells.

Targeted therapies against oncogenic receptor tyrosine kinases (RTK) show promising results in the clinic. Unfortunately, despite the initial positive response, most patients develop therapeutic resistance. Most research has focused on acquired resistance occurring after an extensive time of treatment; however, the question remains as to how cells can survive an initial treatment, as early resistance to apoptosis will enable cells to develop any growth-stimulating mechanism. Here, the non-small cell lung cancer (NSCLC) PC9 cell line was used to systematically profile, by mass spectrometry, changes in the proteome, kinome, and phosphoproteome during early treatment with the EGFR inhibitor afatinib. Regardless of the response, initial drug-sensitive cells rapidly adapt to targeted therapy, and within days, cells regained the capacity to proliferate, despite persisting target inhibition. These data reveal a rapid reactivation of mTOR and MAPK signaling pathways after initial inhibition and an increase in abundance and activity of cytoskeleton and calcium signaling-related proteins. Pharmacologic inhibition of reactivated pathways resulted in increased afatinib efficacy. However more strikingly, cells that were restricted from accessing extracellular calcium were extremely sensitive to afatinib treatment. These findings were validated using three additional inhibitors tested in four different NSCLC cell lines, and the data clearly indicated a role for Ca2+ signaling during the development of adaptive resistance. From a therapeutic point of view, the increased inhibitor efficacy could limit or even prevent further resistance development.Implications: Combined targeting of calcium signaling and RTKs may limit drug resistance and improve treatment efficacy. Mol Cancer Res; 16(11); 1773-84. ©2018 AACR.

Diethylhexylphthalate extracted by typical newborn lipid emulsions from polyvinylchloride infusion systems causes significant changes in histology of rabbit liver.

BACKGROUND: Looking for a candidate substance inducing hepatobiliary dysfunction under parenteral nutrition (PN) in newborns, we recently discovered that newborn infusions extract large amounts of the plasticizer diethylhexylphthalate (DEHP) from commonly used polyvinylchloride (PVC) infusion lines. This plasticizer is well known to be genotoxic and teratogenic in animals and to cause changes in various organs and enzyme systems even in humans. The aim of this study was to examine the effect of DEHP, extracted in the same way and in the same amount as in newborns, on livers of young rabbits. METHODS: Prepubertal rabbits received lipid emulsion through central IV lines continuously for 3 weeks either via PVC or polyethylene (PE) infusion systems. Livers were examined after 1 and 3 weeks by light and electron microscopy. RESULTS: By light microscopy, hydropic degeneration, single-cell necrosis, fibrosis, and bile duct proliferation were observed more in the PVC group. Electron microscopy revealed multiple nuclear changes, clusters and atypical forms of peroxisomes, proliferation of smooth endoplasmic reticulum, increased deposition of lipofuscin, and a mild perisinusoidal fibrosis only in the PVC group. These changes, which are generally regarded as reaction upon a toxic stimulus, could be exclusively attributed to DEHP. CONCLUSIONS: This investigation proved that DEHP produces toxin-like changes in livers of young rabbits in the same dose, duration, and method of administration as in newborn infants. For this reason, it is likely that DEHP is the substance that causes hepatobiliary dysfunction in newborns under PN. Possible modes of action of DEHP are proposed.

The target landscape of clinical kinase drugs.

Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making.