Therapeutics promoting the endogenous production of IL-10 have the potential to restore homeostasis in inflammatory disorders such as inflammatory bowel disease (IBD). Here we describe the identification of a series of IL-10 upregulators based on a pyrimidyl-piperidine scaffold through a high throughput phenotypic CD4+ T-cell multiplex assay. In vitro optimization of the initial hit yielded a lead with good potency and an in vitro clearance profile, compound 3-7, which additionally demonstrated efficacy in a murine endotoxin challenge PK-PD mechanistic model. Target deconvolution efforts identified compound 3-7 as a highly selective CDK8/19 inhibitor, and crystallographic studies unveiled its binding mode to the CDK8/Cyclin-C complex, characterized by an unusual water-mediated hydrogen bond to the kinase hinge region.

The Janus family of tyrosine kinases (JAK1, JAK2, JAK3, and TYK2) play an essential role in the receptor signaling of cytokines that have been implicated in the pathogenesis of severe asthma, and there is emerging interest in the development of small-molecule-inhaled JAK inhibitors as treatments. Here, we describe the optimization of a quinazoline series of JAK inhibitors and the results of mouse lung pharmacokinetic (PK) studies where only low concentrations of parent compound were observed. Subsequent investigations revealed that the low exposure was due to metabolism by aldehyde oxidase (AO), so we sought to identify quinazolines that were not metabolized by AO. We found that specific substituents at the quinazoline 2-position prevented AO metabolism and this was rationalized through computational docking studies in the AO binding site, but they compromised kinome selectivity. Results presented here highlight that AO metabolism is a potential issue in the lung.

The development of selective histone deacetylase (HDAC) inhibitors with anti-cancer and anti-inflammatory properties remains challenging in large part owing to the difficulty of probing the interaction of small molecules with megadalton protein complexes. A combination of affinity capture and quantitative mass spectrometry revealed the selectivity with which 16 HDAC inhibitors target multiple HDAC complexes scaffolded by ELM-SANT domain subunits, including a novel mitotic deacetylase complex (MiDAC). Inhibitors clustered according to their target profiles with stronger binding of aminobenzamides to the HDAC NCoR complex than to the HDAC Sin3 complex. We identified several non-HDAC targets for hydroxamate inhibitors. HDAC inhibitors with distinct profiles have correspondingly different effects on downstream targets. We also identified the anti-inflammatory drug bufexamac as a class IIb (HDAC6, HDAC10) HDAC inhibitor. Our approach enables the discovery of novel targets and inhibitors and suggests that the selectivity of HDAC inhibitors should be evaluated in the context of HDAC complexes and not purified catalytic subunits.

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

Stable isotope labeling (SIL) has emerged as a powerful tool to measure the relative quantitative differences between samples in many differential display-type proteomic applications. However, current SIL procedures tend to suffer from the fact that one needs to decide very early in a biochemical strategy whether or not a sample will be subjected to relative quantification. Typically, the entire strategy has to be adapted to the needs of the particular quantification method chosen which might limit the range of biochemical experiments amenable to quantification. Metabolic labeling approaches, albeit very sensitive, can only be applied to studies using appropriate cell culture systems which might not necessarily be compatible with the biological system under investigation. Chemical labeling of complex protein mixtures by, e.g., isotope-coded affinity tags (ICAT), can offer great simplification of protein mixtures but is restricted by the accessibility of the often few suitable peptides (i.e. cysteine containing peptides) for both protein identification and quantification. Here, we describe a post-digest (18)O-labeling method that can circumvent some of the above limitations by separating protein identification from quantification. An aliquot of all samples in a set can be used for rapid protein ID using, e.g., matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS). In a second step, relative quantification is performed using trypsin-catalyzed (18)O incorporation into all tryptic peptides. This two-stage procedure introduces significant experimental flexibility because it enables postponement of the decision about which pairs of samples from a given set of experiments are to be compared until after the protein ID stage. In-gel digested protein quantities between 50 fmol and 15 pmol are amenable to this new method, with a dynamic range of 1:10 within one sample. Accuracy for measured relative abundances is similar to those reported for other SIL strategies (errors typically <20%), and the method is applicable to protein samples from all kinds of tissue or cell culture. This paper presents quantification data for a set of standard proteins, as well as a study of differential complex formation around the NFkappaB transcription factor p65 following stimulation with TNF-alpha.