Application of proteomic profiling based on 2D-DIGE for classification of compounds according to the mechanism of action

[Development of Decomposition Approach for Comprehensive Understanding of Drug Effects]

As the term polypharmacology suggests, there are multiple actions of small-molecule compounds. We proposed a decomposition and understanding concept that sheds light on the small effects in comparison to the large effects by decomposing these multiple effects. This concept was embodied by describing the effects of the compounds in a transcriptome profile, followed by factor analysis to extract latent variables as decomposed effects. Application of this approach to public datasets resulted in the inferences of compound effects consistent with existing knowledge such as gene ontologies and pathways. In one experimental validation, the potential inducibility of endoplasmic reticulum stress of several commercial drugs was detected by decomposition. Another study successfully discriminated the effects of a natural product and its derivatives despite their structural similarity. In the era of big data, it is important to infer conceptual elements composed of measurable elements as a higher layer than the given data of a specimen, which can expand our perception and understanding of the specimen. This review introduces an example of such a philosophy by applying it to the multiple effects of drugs to contribute to the understanding.

Identification of Dihydroorotate Dehydrogenase Inhibitors─Indoluidins─That Inhibit Cancer Cell Growth

Dihydroorotate dehydrogenase (DHODH) catalyzes the rate-limiting step in de novo pyrimidine biosynthesis and is a promising cancer treatment target. This study reports the identification of indoluidin D and its derivatives as inhibitors of DHODH. Cell-based phenotypic screening revealed that indoluidin D promoted myeloid differentiation and inhibited the proliferation of acute promyelocytic leukemia HL-60 cells. Indoluidin D also suppressed cell growth in various other types of cancer cells. Cancer cell sensitivity profiling with JFCR39 and proteomic profiling with ChemProteoBase revealed that indoluidin D is a DHODH inhibitor. Indoluidin D inhibited human DHODH activity in vitro; the DHODH reaction product orotic acid rescued indoluidin D-induced cell differentiation. We synthesized several indoluidin D diastereomer derivatives and demonstrated that stereochemistry was vital to their molecular activity. The indoluidin D derivative indoluidin E showed similar activity to its parent compound and suppressed tumor growth in a murine lung cancer xenograft model. Hence, indoluidin D and its derivatives selectively inhibit DHODH and suppress cancer cell growth.

Identification of a Small-Molecule Glucose Transporter Inhibitor, Glutipyran, That Inhibits Cancer Cell Growth

Cancer cells reprogram their metabolism to survive and grow. Small-molecule inhibitors targeting cancer are useful for studying its metabolic pathways and functions and for developing anticancer drugs. Here, we discovered that glutipyran and its derivatives inhibit glycolytic activity and cell growth in human pancreatic cancer cells. According to proteomic profiling of glutipyran-treated cells using our ChemProteoBase, glutipyran was clustered within the group of endoplasmic reticulum (ER) stress inducers that included glycolysis inhibitors. Glutipyran inhibited glucose uptake and suppressed the growth of various cancer cells, including A431 cells that express glucose transporter class I (GLUT1) and DLD-1 GLUT1 knockout cells. When cotreated with the mitochondrial respiration inhibitor metformin, glutipyran exhibited a synergistic antiproliferative effect. Metabolome analysis revealed that glutipyran markedly decreased most metabolites of the glycolytic pathway and the pentose phosphate pathway. Glutipyran significantly suppressed tumor growth in a xenograft mouse model of pancreatic cancer. These results suggest that glutipyran acts as a broad-spectrum GLUT inhibitor and reduces cancer cell growth.

Decomposition Profile Data Analysis for Deep Understanding of Multiple Effects of Natural Products

It is difficult to understand the entire effect of a natural product because such products generally have multiple effects. We propose a strategy to understand these effects effectively by decomposing them with a profile data analysis method we developed. A transcriptome profile data set was obtained from a public database and analyzed. Considering their high similarity in structure and transcriptome profile, we focused on rescinnamine and syrosingopine. Decomposed effects predicted clear differences between the compounds. Two of the decomposed effects, SREBF1 activation and HDAC inhibition, were investigated experimentally because the relationship between these effects and the compounds had not yet been reported. Analyses in vitro validated these effects, and their strength was consistent with predicted scores. Moreover, the number of outliers in decomposed effects per compound was higher in natural products than in drugs in the data set, which is consistent with the nature of the effects of natural products.

Discovery of small-molecule modulator of heterotrimeric Gi-protein by integrated phenotypic profiling and chemical proteomics

Discovery of small-molecule inducers of unique phenotypic changes combined with subsequent target identification often provides new insights into cellular functions. Here, we applied integrated profiling based on cellular morphological and proteomic changes to compound screening. We identified an indane derivative, NPD9055, which is mechanistically distinct from reference compounds with known modes of action. Employing a chemical proteomics approach, we then showed that NPD9055 binds subunits of heterotrimeric G-protein G_i. An in vitro [³⁵S]GTPγS-binding assay revealed that NPD9055 inhibited GDP/GTP exchange on a Gα_i subunit induced by a G-protein-coupled receptor agonist, but not on another G-protein from the Gα_s family. In intact HeLa cells, NPD9055 induced an increase in intracellular Ca²⁺ levels and ERK/MAPK phosphorylation, both of which are regulated by Gβγ, following its dissociation from Gα_i. Our observations suggest that NPD9055 targets Gα_i and thus regulates Gβγ-dependent cellular processes, most likely by causing the dissociation of Gβγ from Gα_i.

Target Protein Identification on Photocatalyst-Functionalized Magnetic Affinity Beads

Although various affinity chromatography and photoaffinity labeling methods have been developed for target protein identification of bioactive molecules, it is often difficult to detect proteins that bind the ligand with weak transient affinity using these techniques. We have developed single electron transfer-mediated tyrosine labeling using ruthenium photocatalysts. Proximity labeling using 1-methyl-4-aryl-urazole (MAUra) labels proteins in close proximity to the photocatalyst with high efficiency and selectivity. Performing this labeling reaction on affinity beads makes it possible to label proteins that bind the ligand with weak transient affinity. In this article, novel protocols are described for target protein identification using photocatalyst proximity labeling on ruthenium photocatalyst-functionalized magnetic affinity beads. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Synthesis of ruthenium photocatalyst Basic Protocol 2: Synthesis of azide- or desthiobiotin-conjugated labeling reagents Basic Protocol 3: Preparation of photocatalyst and ligand-functionalized affinity beads Basic Protocol 4: Target protein labeling in cell lysate Basic Protocol 5: Enrichment of labeled proteins with MAUra-DTB for LC-MS/MS analysis Basic Protocol 6: 2D-DIGE analysis of fluorescence-labeled proteins.

Identification of a Small Compound Targeting PKM2-Regulated Signaling Using 2D Gel Electrophoresis-Based Proteome-wide CETSA

The cellular thermal shift assay (CETSA) has recently been devised as a label-free method for target validation of small compounds and monitoring the thermal stabilization or destabilization of proteins due to binding with the compound. Herein, we developed a modified method by combining the CETSA and proteomics analysis based on 2D gel electrophoresis, namely 2DE-CETSA, to identify the thermal stability-shifted proteins by binding with a new compound. We applied the 2DE-CETSA for analysis of a target-unknown compound, NPD10084, which exerts anti-proliferative activity against colorectal cancer cells in vitro and in vivo, and identified pyruvate kinase muscle isoform 2 (PKM2) as a candidate target protein. Interestingly, NPD10084 interrupted protein-protein interactions between PKM2 and β-catenin or STAT3, with subsequent suppression of downstream signaling. We thus demonstrate that our 2DE-CETSA method is applicable for identification of target compounds discovered by phenotypic screening.

CRM646-A, a Fungal Metabolite, Induces Nucleus Condensation by Increasing Ca2+ Levels in Rat 3Y1 Fibroblast Cells

We previously identified a new heparinase inhibitor fungal metabolite, named CRM646-A, which showed inhibition of heparinase and telomerase activities in an in vitro enzyme assay and antimetastatic activity in a cell-based assay. In this study, we elucidated the mechanism by which CRM646-A rapidly induced nucleus condensation, plasma membrane disruption and morphological changes by increasing intracellular Ca2+ levels. Furthermore, PD98059, a mitogen-activated protein kinase (MEK) inhibitor, inhibited CRM646-A-induced nucleus condensation through ERK1/2 activation in rat 3Y1 fibroblast cells. We identified CRM646-A as a Ca2+ ionophore-like agent with a distinctly different chemical structure from that of previously reported Ca2+ ionophores. These results indicate that CRM646-A has the potential to be used as a new and effective antimetastatic drug.

Development of a Novel Platform of Proteome Profiling Based on an Easy-to-Handle and Informative 2D-DIGE System

Proteome profiling based on two-dimensional (2D)-DIGE might be a useful tool for investigating drug-like compounds and the mode of action of drugs. However, obtaining data for profiling requires high labor costs, and it is difficult to control the reproducibility of spot positions because 2D-DIGE usually requires large-size glass plates and spot alignments are greatly affected by the quality of DryStrips and polyacrylamide gels (PAGs). Therefore, we have developed a novel platform by employing small size DryStrips and PAGs, and an image analysis strategy based on dual correction of spot alignment and volume. Our system can automatically detect a large number of consistent spots through all images. Cytosol fractions of HeLa cells treated with dimethyl sulfoxide (DMSO) or bortezomib were analyzed, 1697 consistent spots were detected, and 775 of them were significantly changed with the treatment. Deviations between different days and lot sets of DryStrips and PAGs were investigated by calculating the correlation coefficients. The mean values of the correlation between days and lot sets were 0.96 and 0.94, respectively. Clustering analysis of all the treatment data clearly separated the DMSO or bortezomib treated groups beyond day deviations. Thus, we have succeeded in developing an easy-to-handle 2D-DIGE system that can be a novel proteome profiling platform.

Proteomic Profiling for Target Identification of Biologically Active Small Molecules Using 2D DIGE

Recent improvements in technologies such as omics analysis have enabled us to acquire a large amount of data regarding the biological changes in cells treated with bioactive small molecules. Using such data, a variety of profiling methods have been established for target identification of such bioactive compounds. In this chapter, we describe a proteomic profiling system, ChemProteoBase, based on proteome analysis using two-dimensional difference gel electrophoresis. This system compares the similarities in protein expression of 296 spots detected in the gel among the test compounds.

Repurposing of auranofin: Thioredoxin reductase remains a primary target of the drug

Auranofin is a gold (I)-containing compound used for the treatment of rheumatic arthritis. Auranofin has anticancer activity in animal models and is approved for clinical trials for lung and ovarian carcinomas. Both the cytosolic and mitochondrial forms of the selenoprotein thioredoxin reductase (TrxR) are well documented targets of auranofin. Auranofin was recently reported to also inhibit proteasome activity at the level of the proteasome-associated deubiquitinases (DUBs) UCHL5 and USP14. We here set out to re-examine the molecular mechanism underlying auranofin cytotoxicity towards cultured cancer cells. The effects of auranofin on the proteasome were examined in cells and in vitro, effects on DUB activity were assessed using different substrates. The cellular response to auranofin was compared to that of the 20S proteasome inhibitor bortezomib and the 19S DUB inhibitor b-AP15 using proteomics. Auranofin was found to inhibit mitochondrial activity and to an induce oxidative stress response at IC₅₀ doses. At 2-3-fold higher doses, auranofin inhibits proteasome processing in cells. At such supra-pharmacological concentrations USP14 activity was inhibited. Analysis of protein expression profiles in drug-exposed tumor cells showed that auranofin induces a response distinct from that of the 20S proteasome inhibitor bortezomib and the DUB inhibitor b-AP15, both of which induced similar responses. Our results support the notion that the primary mechanism of action of auranofin is TrxR inhibition and suggest that proteasome DUB inhibition is an off-target effect. Whether proteasome inhibition will contribute to the antineoplastic effect of auranofin in treated patients is unclear but remains a possibility.

A novel inhibitor of tumorspheres reveals the activation of the serine biosynthetic pathway upon mitochondrial inhibition

Differences in the metabolism of cancer cells or cancer stem cells (CSCs) as compared to normal cells have provided avenues to safely target cancers. To discover metabolic inhibitors of CSCs, we performed alkaline phosphatase- and tumoursphere-based drug screening using induced cancer stem cell-like cells. From the screening of a RIKEN NPDepo chemical library, we discovered NPD2381 as a novel and selective cancer-stemness inhibitor that targets mitochondrial metabolism. Using our ChemProteoBase profiling, we found that NPD2381 increases the expression of enzymes within the serine biosynthesis pathway. We also found a role for serine in protecting cancer cells from mitochondrial inhibitors. Our results suggest the existence of a compensatory mechanism to increase the level of intracellular serine in response to mitochondrial inhibitors.

Development of Orthogonal Linear Separation Analysis (OLSA) to Decompose Drug Effects into Basic Components

Drugs have multiple, not single, effects. Decomposition of drug effects into basic components helps us to understand the pharmacological properties of a drug and contributes to drug discovery. We have extended factor analysis and developed a novel profile data analysis method: orthogonal linear separation analysis (OLSA). OLSA contracted 11,911 genes to 118 factors from transcriptome data of MCF7 cells treated with 318 compounds in a Connectivity Map. Ontology of the main genes constituting the factors detected significant enrichment of the ontology in 65 of 118 factors and similar results were obtained in two other data sets. In further analysis of the Connectivity Map data set, one factor discriminated two Hsp90 inhibitors, geldanamycin and radicicol, while clustering analysis could not. Doxorubicin and other topoisomerase inhibitors were estimated to inhibit Na+/K+ ATPase, one of the suggested mechanisms of doxorubicin-induced cardiotoxicity. Based on the factor including PI3K/AKT/mTORC1 inhibition activity, 5 compounds were predicted to be novel inducers of autophagy, and other analyses including western blotting revealed that 4 of the 5 actually induced autophagy. These findings indicate the potential of OLSA to decompose the effects of a drug and identify its basic components.

Recent advances in target identification of bioactive natural products

Natural products are a tremendous source of tool discovery for basic science and drug discovery for clinical uses. In contrast to the large number of compounds isolated from nature, however, the number of compounds whose target molecules have been identified so far is fairly limited. Elucidation of the mechanism of how bioactive small molecules act in cells to induce biological activity (mode of action) is an attractive but challenging field of basic biology. At the same time, this is the major bottleneck for drug development of compounds identified in cell-based and phenotype-based screening. Although researchers’ experience and inspiration have been crucial for successful target identification, recent advancements in genomics, proteomics, and chemical genomics have made this challenging task possible in a systematic fashion.

A framework for large-scale metabolome drug profiling links coenzyme A metabolism to the toxicity of anti-cancer drug dichloroacetate

Metabolic profiling of cell line collections has become an invaluable tool to study disease etiology, drug modes of action and to select personalized treatments. However, large-scale in vitro dynamic metabolic profiling is limited by time-consuming sampling and complex measurement procedures. By adapting a mass spectrometry-based metabolomics workflow for high-throughput profiling of diverse adherent mammalian cells, we establish a framework for the rapid measurement and analysis of drug-induced dynamic changes in intracellular metabolites. This methodology is scalable to large compound libraries and is here applied to study the mechanism underlying the toxic effect of dichloroacetate in ovarian cancer cell lines. System-level analysis of the metabolic responses revealed a key and unexpected role of CoA biosynthesis in dichloroacetate toxicity and the more general importance of CoA homeostasis across diverse human cell lines. The herein-proposed strategy for high-content drug metabolic profiling is complementary to other molecular profiling techniques, opening new scientific and drug-discovery opportunities.

Development of a Terpenoid-Production Platform in Streptomyces reveromyceticus SN-593

Terpenoids represent the largest class of natural products, some of which are resources for pharmaceuticals, fragrances, and fuels. Generally, mass production of valuable terpenoid compounds is hampered by their low production levels in organisms and difficulty of chemical synthesis. Therefore, the development of microbial biosynthetic platforms represents an alternative approach. Although microbial terpenoid-production platforms have been established in Escherichia coli and yeast, an optimal platform has not been developed for Streptomyces species, despite the large capacity to produce secondary metabolites, such as polyketide compounds. To explore this potential, we constructed a terpenoid-biosynthetic platform in Streptomyces reveromyceticus SN-593. This strain is unique in that it harbors the mevalonate gene cluster enabling the production of furaquinocin, which can be controlled by the pathway specific regulator Fur22. We simultaneously expressed the mevalonate gene cluster and subsequent terpenoid-biosynthetic genes under the control of Fur22. To achieve improved fur22 gene expression, we screened promoters from S. reveromyceticus SN-593. Our results showed that the promoter associated with rvr2030 gene enabled production of 212 ± 20 mg/L botryococcene to levels comparable to those previously reported for other microbial hosts. Given that the rvr2030 gene encodes for an enzyme involved in the primary metabolism, these results suggest that optimized expression of terpenoid-biosynthetic genes with primary and secondary metabolism might be as important for high yields of terpenoid compounds as is the absolute expression level of a target gene(s).

Sendai virus recruits cellular villin to remodel actin cytoskeleton during fusion with hepatocytes

Reconstituted Sendai viral envelopes (virosomes) are well recognized for their promising potential in membrane fusion-mediated delivery of bioactive molecules to liver cells. Despite the known function of viral envelope glycoproteins in catalyzing fusion with cellular membrane, the role of host cell proteins remains elusive. Here, we used two-dimensional differential in-gel electrophoresis to analyze hepatic cells in early response to virosome-induced membrane fusion. Quantitative mass spectrometry together with biochemical analysis revealed that villin, an actin-modifying protein, is differentially up-regulated and phosphorylated at threonine 206-an early molecular event during membrane fusion. We found that villin influences actin dynamics and that this influence, in turn, promotes membrane mixing through active participation of Sendai viral envelope glycoproteins. Modulation of villin in host cells also resulted in a discernible effect on the entry and egress of progeny Sendai virus. Taken together, these results suggest a novel mechanism of regulated viral entry in animal cells mediated by host factor villin.

Potential molecular mechanisms for fruiting body formation of Cordyceps illustrated in the case of Cordyceps sinensis

The fruiting body formation mechanisms of Cordyceps sinensis are still unclear. To explore the mechanisms, proteins potentially related to the fruiting body formation, proteins from fruiting bodies, and mycelia of Cordyceps species were assessed by using two-dimensional fluorescence difference gel electrophoresis, and the differential expression proteins were identified by matrix-assisted laser desorption/ionisation tandem time of flight mass spectrometry. The results showed that 198 differential expression proteins (252 protein spots) were identified during the fruiting body formation of Cordyceps species, and 24 of them involved in fruiting body development in both C. sinensis and other microorganisms. Especially, enolase and malate dehydrogenase were first found to play an important role in fruiting body development in macro-fungus. The results implied that cAMP signal pathway involved in fruiting body development of C. sinensis, meanwhile glycometabolism, protein metabolism, energy metabolism, and cell reconstruction were more active during fruiting body development. It has become evident that fruiting body formation of C. sinensis is a highly complex differentiation process and requires precise integration of a number of fundamental biological processes. Although the fruiting body formation mechanisms for all these activities remain to be further elucidated, the possible mechanism provides insights into the culture of C. sinensis.

Choose and Use Your Chemical Probe Wisely to Explore Cancer Biology

Small-molecule chemical probes or tools have become progressively more important in recent years as valuable reagents to investigate fundamental biological mechanisms and processes causing disease, including cancer. Chemical probes have also achieved greater prominence alongside complementary biological reagents for target validation in drug discovery. However, there is evidence of widespread continuing misuse and promulgation of poor-quality and insufficiently selective chemical probes, perpetuating a worrisome and misleading pollution of the scientific literature. We discuss current challenges with the selection and use of chemical probes, and suggest how biologists can and should be more discriminating in the probes they employ.

Phenotypic screening meets natural products in drug discovery†

The Nobel Prize in Physiology or Medicine 2015 was awarded for discoveries related to the control of parasitic diseases using natural products of microbial and plant origin. In current drug discovery programs, synthesized compounds are widely used as a screening source; however, this award reminds us of the importance of natural products. Here, we introduce our phenotypic screening methods based on changes in cell morphology and discuss their effectiveness and impact for natural products in drug discovery.

Proteomic profiling reveals that collismycin A is an iron chelator

Collismycin A (CMA), a microbial product, has anti-proliferative activity against cancer cells, but the mechanism of its action remains unknown. Here, we report the identification of the molecular target of CMA by ChemProteoBase, a proteome-based approach for drug target identification. ChemProteoBase profiling showed that CMA is closely clustered with di-2-pyridylketone 4,4-dimethyl-3-thiosemicarbazone, an iron chelator. CMA bound to both Fe(II) and Fe(III) ions and formed a 2:1 chelator-iron complex with a redox-inactive center. CMA-induced cell growth inhibition was completely canceled by Fe(II) and Fe(III) ions, but not by other metal ions such as Zn(II) or Cu(II). Proteomic and transcriptomic analyses showed that CMA affects the glycolytic pathway due to the accumulation of HIF-1α. These results suggest that CMA acts as a specific iron chelator, leading to the inhibition of cancer cell growth.

Chemical and biological studies of reveromycin A

The research on antibiotics requires the integration of broad areas, such as microbiology, organic chemistry, biochemistry and pharmacology. It is similar to the field of chemical biology that is recently popular as an approach for drug discovery. When we isolate a new compound from a microorganism, we can pursue the interesting research on chemistry and biology. In this review, I would like to introduce our achievements in relation to reveromycin A.

Proteomic profiling of small-molecule inhibitors reveals dispensability of MTH1 for cancer cell survival

Since recent publications suggested that the survival of cancer cells depends on MTH1 to avoid incorporation of oxidized nucleotides into the cellular DNA, MTH1 has attracted attention as a potential cancer therapeutic target. In this study, we identified new purine-based MTH1 inhibitors by chemical array screening. However, although the MTH1 inhibitors identified in this study targeted cellular MTH1, they exhibited only weak cytotoxicity against cancer cells compared to recently reported first-in-class inhibitors. We performed proteomic profiling to investigate the modes of action by which chemically distinct MTH1 inhibitors induce cancer cell death, and found mechanistic differences among the first-in-class MTH1 inhibitors. In particular, we identified tubulin as the primary target of TH287 and TH588 responsible for the antitumor effects despite the nanomolar MTH1-inhibitory activity in vitro. Furthermore, overexpression of MTH1 did not rescue cells from MTH1 inhibitor–induced cell death, and siRNA-mediated knockdown of MTH1 did not suppress cancer cell growth. Taken together, we conclude that the cytotoxicity of MTH1 inhibitors is attributable to off-target effects and that MTH1 is not essential for cancer cell survival.

Photo-cross-linked small-molecule affinity matrix as a tool for target identification of bioactive small molecules

This review describes the status of the photo-cross-linked small-molecule affinity matrix while providing a useful tutorial for academic and industrial chemical biologists who are involved or interested in drug target identification.

Integrated profiling methods for identifying the targets of bioactive compounds: MorphoBase and ChemProteoBase

Target identification of new bioactive compounds has been achieved by both our direct and indirect approaches. Here, we highlight the utility of the latter approaches, MorphoBase and ChemProteoBase.

Improving drug discovery with high-content phenotypic screens by systematic selection of reporter cell lines

High-content, image-based screens enable the identification of compounds that induce cellular responses similar to those of known drugs but through different chemical structures or targets. A central challenge in designing phenotypic screens is choosing suitable imaging biomarkers. Here we present a method for systematically identifying optimal reporter cell lines for annotating compound libraries (ORACLs), whose phenotypic profiles most accurately classify a training set of known drugs. We generate a library of fluorescently tagged reporter cell lines, and let analytical criteria determine which among them--the ORACL--best classifies compounds into multiple, diverse drug classes. We demonstrate that an ORACL can functionally annotate large compound libraries across diverse drug classes in a single-pass screen and confirm high prediction accuracy by means of orthogonal, secondary validation assays. Our approach will increase the efficiency, scale and accuracy of phenotypic screens by maximizing their discriminatory power.

Methyl 3-((6-methoxy-1,4-dihydroindeno[1,2-c]pyrazol-3-yl)amino)benzoate (GN39482) as a tubulin polymerization inhibitor identified by MorphoBase and ChemProteoBase profiling methods

A series of indenopyrazoles was synthesized from the corresponding indanones and phenyl isothiocyanates in two steps. Among the compounds synthesized, methyl 3-((6-methoxy-1,4-dihydroindeno[1,2-c]pyrazol-3-yl)amino)benzoate 6m (GN39482) was found to possess a promising antiproliferative activity toward human cancer cells without affecting any antimicrobial and antimalarial activities at 100 nM. Both a methoxy group at R(1) position and a methoxycarbonyl group at R(2) position of the anilinoquinazoline framework are essential for the high cell growth inhibition. Both MorphoBase and ChemProteoBase profiling analyses suggested that compound 6m was classified as a tubulin inhibitor. Indeed, compound 6m inhibited the acetylated tubulin accumulation and the microtubule formation and induced G2/M cell cycle arrest in HeLa cells, revealing that a promising antiproliferative activity of compound 6m toward human cancer cells is probably caused by the tubulin polymerization inhibition.

Connecting phenotype and chemotype: high-content discovery strategies for natural products research

In recent years, the field of natural products has seen an explosion in the breadth, resolution, and accuracy of profiling platforms for compound discovery, including many new chemical and biological annotation methods. With these new tools come opportunities to examine extract libraries using systematized profiling approaches that were not previously available to the field and which offer new approaches for the detailed characterization of the chemical and biological attributes of complex natural products mixtures. This review will present a summary of some of these untargeted profiling methods and provide perspective on the future opportunities offered by integrating these tools for novel natural products discovery.

A small molecule that induces reactive oxygen species via cellular glutathione depletion

A new cytotoxic compound was found in our chemical library. We revealed that the compound induced reactive oxygen species through glutathione depletion. Moreover, the compound was effective against several cancer cell lines including those harbouring KRAS.

Report from the Third Annual Symposium of the RIKEN-Max Planck Joint Research Center for Systems Chemical Biology

The third Annual Symposium of the RIKEN-Max Planck Joint Research Center for Systems Chemical Biology was held at Ringberg castle, May 21-24, 2014. At this meeting 45 scientists from Japan and Germany presented the latest results from their research spanning a broad range of topics in chemical biology and glycobiology.

Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats

A proteome-level time-series study of drug effects (i.e., pharmacodynamics) is critical for understanding mechanisms of action and systems pharmacology, but is challenging, because of the requirement of a proteomics method for reliable quantification of many biological samples. Here, we describe a highly reproducible strategy, enabling a global, large-scale investigation of the expression dynamics of corticosteroid-regulated proteins in livers from adrenalectomized rats over 11 time points after drug dosing (0.5–66 h, N = 5/point). The analytical advances include (i) exhaustive tissue extraction with a Polytron/sonication procedure in a detergent cocktail buffer, and a cleanup/digestion procedure providing very consistent protein yields (relative standard deviation (RSD%) of 2.7%–6.4%) and peptide recoveries (4.1–9.0%) across the 60 animals; (ii) an ultrahigh-pressure nano-LC setup with substantially improved temperature stabilization, pump-noise suppression, and programmed interface cleaning, enabling excellent reproducibility for continuous analyses of numerous samples; (iii) separation on a 100-cm-long column (2-μm particles) with high reproducibility for days to enable both in-depth profiling and accurate peptide ion-current match; and (iv) well-controlled ion-current-based quantification. To obtain high-quality quantitative data necessary to describe the 11 time-points protein expression temporal profiles, strict criteria were used to define “quantifiable proteins”. A total of 323 drug-responsive proteins were revealed with confidence, and the time profiles of these proteins provided new insights into the diverse temporal changes of biological cascades associated with hepatic metabolism, response to hormone stimuli, gluconeogenesis, inflammatory responses, and protein translation processes. Most profile changes persisted well after the drug was eliminated. The developed strategy can also be broadly applied in preclinical and clinical research, where the analysis of numerous biological replicates is crucial.

Proteomics of osteosarcoma

Osteosarcoma (OS) is the most common primary malignant tumor of bone and the third most common cancer in childhood and adolescence. Nowadays, early diagnosis, drug resistance and recurrence of the disease represent the major challenges in OS treatment. Post-genomics, and in particular proteomic technologies, offer an invaluable opportunity to address the level of biological complexity expressed by OS. Although the main goal of OS oncoproteomics is focused on diagnostic and prognostic biomarker discovery, in this review we describe and discuss global protein profiling approaches to other aspects of OS biology and pathophysiology, or to investigate the mechanism of action of chemotherapeutics. In addition, we present proteomic analyses carried out on OS cell lines as in vitro models for studying osteoblastic cell biology and the attractive opportunity offered by proteomics of OS cancer stem cells.

Biological characterization of the antiproliferative potential of Co(II) and Sn(IV) coordination compounds in human cancer cell lines: a comparative proteomic approach

BACKGROUND

The discovery of cisplatin's antitumor activity led to a great interest in the potential application of coordination compounds as chemotherapeutic agents. It is essential to identify new compounds that selectively inhibit tumor proliferation, evading secondary effects and resistance associated with chemotherapeutics.

METHODS

The in vitro antiproliferative potential of an organotin(IV) compound was evaluated using colorectal and hepatocellular carcinoma, mammary gland adenocarcinoma cell lines, and human fibroblasts. Tumor cell death was evaluated by fluorescence microscopy and flow cytometry for the Sn(IV) compound and also for a Co(II) compound bearing 1,10-phenanthroline-5,6-dione as ligand. Comparative proteomic analysis for both compounds was assessed in the colorectal cancer cell line.

RESULTS

The Sn(IV) compound presented a high cytotoxic effect in colorectal and hepatocellular carcinoma cell lines (IC50 of 0.238 ± 0.011 μM, 0.199 ± 0.003 μM, respectively), and a lower cytotoxicity in human fibroblasts. Both compounds induced cell apoptosis and promoted the overexpression of oxidative stress-related enzyme superoxide dismutase [Cu-Zn] (SODC). The Co(II) compound induced a decreased expression of anti-apoptotic proteins (translationally-controlled tumor protein and endoplasmin), and the Sn(IV) compound decreased expression of proteins involved in microtubule stabilization, TCTP, and cofilin-1.

CONCLUSIONS

Our data reveals a high in vitro antiproliferative potential against cancer cell lines and a moderate selectivity promoted by the Sn(IV) compound. Proteomic analysis of Sn(IV) and Co(II) compounds in the colorectal cancer cell line allowed an insight to their mechanisms of action, particularly by affecting the expression of proteins typically deregulated in cancer, and also suggesting a promising therapeutic potential for both compounds.

Mass spectrometry for proteomics-based investigation

Within the past years, we have witnessed a great improvement in mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify proteins but also to identify the protein's posttranslational modifications (PTMs), protein isoforms, protein truncation, protein-protein interaction (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in scientific and clinical settings in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Multidimensional profiling in the investigation of small-molecule-induced cell death

Numerous morphological variations of cell death have been described. These processes depend on a complex and overlapping cellular signaling network, making molecular definition of the pathways challenging. This review describes one solution to this problem for small-molecule-induced death, the creation of high-dimensionality profiles for compounds that can be used to define and compare pathways. Such profiles have been assembled from gene expression measurements, protein quantification, chemical-genetic interactions, chemical combination interactions, cancer cell line sensitivity profiling, quantitative imaging, and modulatory profiling. We discuss the advantages and limitations of these techniques in the study of cell death.

Affinity-based target identification for bioactive small molecules

A variety of new approaches of affinity-based target identification for bioactive small molecules are being developed, facilitating drug development and understanding complicated biological processes.

Target identification of small molecules based on chemical biology approaches

Recently, a phenotypic approach-screens that assess the effects of compounds on cells, tissues, or whole organisms-has been reconsidered and reintroduced as a complementary strategy of a target-based approach for drug discovery. Although the finding of novel bioactive compounds from large chemical libraries has become routine, the identification of their molecular targets is still a time-consuming and difficult process, making this step rate-limiting in drug development. In the last decade, we and other researchers have amassed a large amount of phenotypic data through progress in omics research and advances in instrumentation. Accordingly, the profiling methodologies using these datasets expertly have emerged to identify and validate specific molecular targets of drug candidates, attaining some progress in current drug discovery (e.g., eribulin). In the case of a compound that shows an unprecedented phenotype likely by inhibiting a first-in-class target, however, such phenotypic profiling is invalid. Under the circumstances, a photo-crosslinking affinity approach should be beneficial. In this review, we describe and summarize recent progress in both affinity-based (direct) and phenotypic profiling (indirect) approaches for chemical biology target identification.