Proteomic LC-MS approaches combined with genome-annotated databases currently allow identification of thousands of proteins from complex mixtures (1). Approaches have also been developed for relative quantitation using stable isotope labeling (2-4). Recently not only comprehensive quantitation studies between two states (5, 6) but also protein-protein (7, 8), protein-peptide (9), and protein-drug (10) interaction analyses have been reported. So far, however, a comprehensive approach for determining protein concentrations in one sample has not been established. Protein concentrations are one of the most basic and important parameters in quantitative proteomics because the kinetics/dynamics of the cellular proteome is described in terms of changes in the concentrations of proteins in particular compartments. Biological experiments often require at least some information on protein abundance for correct interpretation. In the past, crude quantitative information could be drawn from the intensity of gel staining in comparison to a known amount of marker protein. However, in complex mixture analysis, individual proteins cannot be stained individually, and usually all information about protein abundance is lost. So far, isotope-labeled synthetic peptides have been used as internal standards for absolute quantitation of particular proteins of interest (11,12). This approach is in principle applicable to comprehensive analysis but is hampered by the high cost of isotope-labeled peptides as well as the difficulty of quantitative digestion of proteins in-gel (13).Even a single nano-LC-MS/MS analysis can easily generate a long list of identified proteins with the help of database searching, and additional information can be extracted, such as the hit rank in identification, the probability score, the number of identified peptides per protein, ion counts of identified peptides, LC retention times, and so on. Qualitatively some parameters, such as the hit rank, the score, and the number of peptides per protein (14), can be considered as indicators for protein abundance in the analyzed sample. Among them, the integrated ion counts of the peptides identifying each protein would be the most direct parameter to describe the abundance and has been used to compare protein expression in different states (15). However, a mass spectrometer is not as versatile as an absorbance detector because of limited linearity and possibly because of background and ionization suppression effects (16). Therefore, it is necessary to normalize these parameters to obtain at least approximate quantitative information. The first approach to achieve this, to our knowledge, was to use the number of peptides per protein normalized by the theoretical number of

The current progression from genomics to proteomics is fueled by the realization that many properties of proteins (e.g., interactions, post-translational modifications) cannot be predicted from DNA sequence. Although it has become feasible to rapidly identify proteins from crude cell extracts using mass spectrometry after two-dimensional electrophoretic separation, it can be difficult to elucidate low-abundance proteins of interest in the presence of a large excess of relatively abundant proteins. Therefore, for effective proteome analysis it becomes critical to enrich the sample to be analyzed in subfractions of interest. For example, the analysis of protein kinase substrates can be greatly enhanced by enriching the sample of phosphorylated proteins. Although enrichment of phosphotyrosine-containing proteins has been achieved through the use of high-affinity anti-phosphotyrosine antibodies, the enrichment of phosphoserine/threonine-containing proteins has not been routinely possible. Here, we describe a method for enriching phosphoserine/threonine-containing proteins from crude cell extracts, and for subsequently identifying the phosphoproteins and sites of phosphorylation. The method, which involves chemical replacement of the phosphate moieties by affinity tags, should be of widespread utility for defining signaling pathways and control mechanisms that involve phosphorylation or dephosphorylation of serine/threonine residues.

The Saccharomyces cerevisiae och1 mutant shows a deficiency in the mannose outer chain elongation at the non‐permissive temperature. We have cloned the OCH1 gene by complementation of temperature sensitive (ts) phenotype for growth. The integrant of OCH1 gene in the yeast chromosome can complement the ts phenotype and shows the same mapping position as that of the och1 mutation, indicating that the cloned gene is the true gene for mutation. The OCH1 gene disruptant is not lethal but ts for cell growth, and lacks mannose outer chains. The OCH1 gene sequence predicts a 55 kDa protein consisting of 480 amino acids. It contains four potential asparagine‐linked (N‐linked) glycosylation sites and a single transmembrane region near the N‐terminus. In vitro translation/translocation analysis revealed that the large C‐terminal region of the OCH1 protein is located at the lumenal side of microsomal membranes with some sugar modification, indicating a type II membrane topology. The OCH1 protein was detected in yeast membrane fractions as four forms of 58–66 kDa, which correspond to the size of a glycoprotein containing four N‐linked sugar chains the length of which is almost the same or slightly larger than the inner core (Man8GlcNAc2) formed in the endoplasmic reticulum (ER). Finally, the OCH1 gene was found to encode a novel mannosyltransferase which specifically transfers [14C]mannose to the unique acceptor, the core‐like oligosaccharide of cell wall mannan accumulated in the och1 disruptant.

We have developed a simple, highly specific enrichment procedure for phosphopeptides, by increasing the specificity of an immobilized metal affinity column (IMAC) without using any chemical reaction. The method employs a biphasic IMAC-C18 tip, in which IMAC beads are packed on an Empore C18 disk in a 200-microL pipet tip. Phosphopeptides are separated from non-phosphopeptides on the IMAC in an optimized solvent without any chemical reaction, then desorbed from the IMAC using a phosphate buffer, reconcentrated, and desalted on the C18 disk. The increase in selectivity was achieved by (a) using a strong acid to discriminate phosphates from carboxyl groups of peptides and (b) using a high concentration of acetonitrile to remove hydrophobic non-phosphopeptides. The entire procedure was optimized by using known phosphoproteins such as Akt1 kinase and protein kinase A. Although it was difficult to detect phosphopeptides in MALDI-MS spectra of tryptic peptide mixtures before enrichment, after the IMAC procedure, we could successfully detect phosphopeptides with almost no non-phosphopeptides. Next, we constructed an array of IMAC-IMAC/C18 tips, such that number of arrayed tips on a 96-well plate could easily be changed depending on the loading amount of sample. Applying this approach to mouse forebrain resulted in the identification of 162 phosphopeptides (166 phosphorylation sites) from 135 proteins using nano-LC/MS.

Described herein is the discovery of a novel series of antitumor sulfonamides targeting G1 phase of the cell cycle. Cell cycle control in G1 phase has attracted considerable attention in recent cancer research, because many of the important proteins involved in G1 progression or G1/S transition have been found to play a crucial role in proliferation, differentiation, transformation, and programmed cell death (apoptosis). We previously reported our first antitumor sulfonamide E7010 as a novel tubulin polymerization inhibitor. Interestingly enough, continuous research on structurally related compounds led us to the finding of another class of antitumor sulfonamides that block cell cycle progression of P388 murine leukemia cells in G1 phase, but not in M phase. Of the compounds examined, N-(3-chloro-7-indolyl)-1,4-benzenedisulfonamide (E7070) showed significant antitumor activity against HCT116 human colon carcinoma both in vitro (IC(50) 0.11 microg/mL in cell proliferation assay) and in vivo (not only growth suppression but also a marked reduction of tumor size in nude mice). Because of its promising efficacy against human tumor xenografts and its unique mode of action, E7070 is currently undergoing phase I clinical trials in European countries.

An important challenge for proteomics is to be able to compare absolute protein levels across biological samples. Here we introduce an approach based on the use of culture-derived isotope tags (CDITs) for quantitative tissue proteome analysis. We cultured Neuro2A cells in a stable isotope-enriched medium and mixed them with mouse brain samples to serve as internal standards. Using CDITs, we identified and quantified a total of 1,000 proteins, 97-98% of which were expressed in both mouse whole brain and Neuro2A cells. CDITs also allow comprehensive and absolute protein quantification. Synthetic unlabeled peptides were used to quantify the corresponding proteins labeled with stable isotopes in Neuro2A cells, and the results were used to obtain the absolute amounts of 103 proteins in mouse whole brain. The expression levels correlated well with those in Neuro2A cells. Thus, the use of CDITs allows both relative and absolute quantitative proteome studies.

We have developed a systematic strategy for drug target identification. This consists of the following sequential steps: (1) enrichment of total binding proteins using two differential affinity matrixes upon which are immobilized positive and negative chemical structures for drug activity, respectively; (2) covalent labeling of the proteins with a new cleavable isotope-coded affinity tag (ICAT) reagent, followed by proteolysis of the combined proteins; (3) isolation, identification, and relative quantification of the tagged peptides by liquid chromatography-mass spectrometry; (4) array-based transcription profiling to select candidate proteins; and (5) confirmation of direct interaction between the activity-associated structure and the selected proteins by using surface plasmon resonance. We present a typical application to identify the primary binding protein of a novel class of anticancer agents exemplified by E7070. Our results suggest that this approach provides a new aspect of quantitative proteomics to find specific binding proteins from protein mixture and should be applicable to a wide variety of biologically active small molecules with unidentified target proteins.

High-sensitivity, high-throughput analysis of proteins for proteomics studies is usually performed by polyacrylamide gel electrophoresis in combination with mass spectrometry. However, the quality of the data obtained depends on the in-gel digestion procedure employed. This work describes an improvement in the in-gel digestion efficiency for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) analysis. A dramatic improvement in the coverage of tryptic peptides was observed when n-octyl glucoside was added to the buffer. Whole cell extracted proteins from S. cerevisiae were separated by two-dimensional gel electrophoresis and stained with silver. Protein spots were identified using our improved in-gel digestion method and MALDI-TOFMS. In addition, the mass spectra obtained by using the matrix alpha-cyano-4-hydroxycinnamic acid (CHCA) were compared with those obtained using 2,5-dihydroxybenzoic acid (DHB). The DHB matrix usually gave more peaks, which led to higher sequence coverage and, consequently, to higher confidence in protein identification. This improved in-gel digestion protocol is simple and useful for protein identification by MALDI-TOFMS.