Quantitative chemical proteomics for identifying candidate drug targets

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Design, synthesis, and evaluation of a mitoxantrone probe (MXP) for biological studies

Mitoxantrone (MX) is a robust chemotherapeutic with well-characterized applications in treating certain leukemias and advanced breast and prostate cancers. The canonical mechanism of action associated with MX is its ability to intercalate DNA and inhibit topoisomerase II, giving it the designation of a topoisomerase II poison. Years after FDA approval, investigations have unveiled novel protein-binding partners, such as methyl-CpG-binding domain protein (MBD2), PIM1 serine/threonine kinase, RAD52, and others that may contribute to the therapeutic profile of MX. Moreover, recent proteomic studies have revealed MX's ability to modulate protein expression, illuminating the complex cellular interactions of MX. Although mechanistically relevant, the differential expression across the proteome does not address the direct interaction with potential binding partners. Identification and characterization of these MX-binding cellular partners will provide the molecular basis for the alternate mechanisms that influence MX's cytotoxicity. Here, we describe the design and synthesis of a MX-biotin probe (MXP) and negative control (MXP-NC) that can be used to define MX's cellular targets and expand our understanding of the proteome-wide profile for MX. In proof of concept studies, we used MXP to successfully isolate a recently identified protein-binding partner of MX, RAD52, in a cell lysate pulldown with streptavidin beads and western blotting.

Design, synthesis, and evaluation of a mitoxantrone probe (MXP) for biological studies

Mitoxantrone (MX) is a robust chemotherapeutic with well-characterized applications in treating certain leukemias and advanced breast and prostate cancers. The canonical mechanism of action associated with MX is its ability to intercalate DNA and inhibit topoisomerase II, giving it the designation of a topoisomerase II poison. Years after FDA approval, investigations have unveiled novel protein-binding partners, such as methyl-CpG-binding domain protein (MBD2), PIM1 serine/threonine kinase, RAD52, and others that may contribute to the therapeutic profile of MX. Moreover, recent proteomic studies have revealed MX's ability to modulate protein expression, illuminating the complex cellular interactions of MX. Although mechanistically relevant, the differential expression across the proteome does not address the direct interaction with potential binding partners. Identification and characterization of these MX-binding cellular partners will provide the molecular basis for the alternate mechanisms that influence MX's cytotoxicity. Here, we describe the design and synthesis of a MX-biotin probe (MXP) and negative control (MXP-NC) that can be used to define MX's cellular targets and expand our understanding of the proteome-wide profile for MX. In proof of concept studies, we used MXP to successfully isolate a recently identified protein-binding partner of MX, RAD52, in a cell lysate pulldown with streptavidin beads and western blotting.

Graphical abstract Draft

Highlights

An 8-step synthesis was used to generate a biotinylated-mitoxantrone probe (MXP).A pulldown of MXP demonstrated selectivity for RAD52, but not Replication Protein A.Western blot confirmed the identity of the isolated protein, RAD52.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

How to Design Peptides

Novel design of proteins to target receptors for treatment or tissue augmentation has come to the fore owing to advancements in computing power, modeling frameworks, and translational successes. Shorter proteins, or peptides, can offer combinatorial synergies with dendrimer, polymer, or other peptide carriers for enhanced local signaling, which larger proteins may sterically hinder. Here, we present a generalized method for designing a novel peptide. We first show how to create a script protocol that can be used to iteratively optimize and screen novel peptide sequences for binding a target protein. We present a step-by-step introduction to utilizing file repositories, data bases, and the Rosetta software suite. RosettaScripts, an .xml interface that allows for sequential functions to be performed, is used to order the functions for repeatable performance. These strategies may lead to more groups venturing into computational design, which may result in synergies from artificial intelligence/machine learning (AI/ML) to phage display and screening. Importantly, the beginner is expected to be able to design their first peptide ligand and begin their journey in peptide drug discovery. Generally, these peptides potentially could be used to interact with any enzyme or receptor, for example, in the study of chemokines and their interactions with glycosoaminoglycans and their receptors.

Understanding emerging bioactive metabolites with putative roles in cancer biology

Dysregulated metabolism in cancers is, by now, well established. Although metabolic adaptations provide cancers with the ability to synthesize the precursors required for rapid biosynthesis, some metabolites have direct functional, or bioactive, effects in human cells. Here we summarize recently identified metabolites that have bioactive roles either as post-translational modifications (PTMs) on proteins or in, yet unknown ways. We propose that these metabolites could play a bioactive role in promoting or inhibiting cancer cell phenotypes in a manner that is mostly unexplored. To study these potentially important bioactive roles, we discuss several novel metabolomic and proteomic approaches aimed at defining novel PTMs and metabolite-protein interactions. Understanding metabolite PTMs and protein interactors of bioactive metabolites may provide entirely new therapeutic targets for cancer.

The emerging role of mass spectrometry-based proteomics in drug discovery

Proteins are the main targets of most drugs; however, system-wide methods to monitor protein activity and function are still underused in drug discovery. Novel biochemical approaches, in combination with recent developments in mass spectrometry-based proteomics instrumentation and data analysis pipelines, have now enabled the dissection of disease phenotypes and their modulation by bioactive molecules at unprecedented resolution and dimensionality. In this Review, we describe proteomics and chemoproteomics approaches for target identification and validation, as well as for identification of safety hazards. We discuss innovative strategies in early-stage drug discovery in which proteomics approaches generate unique insights, such as targeted protein degradation and the use of reactive fragments, and provide guidance for experimental strategies crucial for success.

A regioselective C7 bromination and C7 palladium-catalyzed Suzuki-Miyaura cross-coupling arylation of 4-substituted NH-free indazoles

A direct and efficient regioselective C7-bromination of 4-substituted 1H-indazole has been achieved. Subsequently, a successful palladium-mediated Suzuki–Miyaura reaction of C7-bromo-4-substituted-1H-indazoles with boronic acids has been performed under optimized reaction conditions. A series of new C7 arylated 4-substituted 1H-indazoles was obtained in moderate to good yields.

A regioselective C7-bromination of 4-substituted 1H-indazoles followed by a palladium-catalyzed Suzuki–Miyaura reaction with boronic acids is described.

A Point of Inflection and Reflection on Systems Chemical Biology

For the past several decades, chemical biologists have been leveraging chemical principles for understanding biology, tackling disease, and biomanufacturing, while systems biologists have holistically applied computation and genome-scale experimental tools to the same problems. About a decade ago, the benefit of combining the philosophies of chemical biology with systems biology into systems chemical biology was advocated, with the potential to systematically understand the way small molecules affect biological systems. Recently, there has been an explosion in new technologies that permit massive expansion in the scale of biological experimentation, increase access to more diverse chemical space, and enable powerful computational interpretation of large datasets. Fueled by these rapidly increasing capabilities, systems chemical biology is now at an inflection point, poised to enter a new era of more holistic and integrated scientific discovery. Systems chemical biology is primed to reveal an integrated understanding of fundamental biology and to discover new chemical probes to comprehensively dissect and systematically understand that biology, thereby providing a path to novel strategies for discovering therapeutics, designing drug combinations, avoiding toxicity, and harnessing beneficial polypharmacology. In this Review, we examine the emergence of new capabilities driving us to this inflection point in systems chemical biology, and highlight holistic approaches and opportunities that are arising from integrating chemical biology with a systems-level understanding of the intersection of biology and chemistry.

STarFish: A Stacked Ensemble Target Fishing Approach and its Application to Natural Products

Target fishing is the process of identifying the protein target of a bioactive small molecule. To do so experimentally requires a significant investment of time and resources, which can be expedited with a reliable computational target fishing model. The development of computational target fishing models using machine learning has become very popular over the last several years because of the increased availability of large amounts of public bioactivity data. Unfortunately, the applicability and performance of such models for natural products has not yet been comprehensively assessed. This is, in part, due to the relative lack of bioactivity data available for natural products compared to synthetic compounds. Moreover, the databases commonly used to train such models do not annotate which compounds are natural products, which makes the collection of a benchmarking set difficult. To address this knowledge gap, a data set composed of natural product structures and their associated protein targets was generated by cross-referencing 20 publicly available natural product databases with the bioactivity database ChEMBL. This data set contains 5589 compound-target pairs for 1943 unique compounds and 1023 unique targets. A synthetic data set comprising 107 190 compound-target pairs for 88 728 unique compounds and 1907 unique targets was used to train k-nearest neighbors, random forest, and multilayer perceptron models. The predictive performance of each model was assessed by stratified 10-fold cross-validation and benchmarking on the newly collected natural product data set. Strong performance was observed for each model during cross-validation with area under the receiver operating characteristic (AUROC) scores ranging from 0.94 to 0.99 and Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) scores from 0.89 to 0.94. When tested on the natural product data set, performance dramatically decreased with AUROC scores ranging from 0.70 to 0.85 and BEDROC scores from 0.43 to 0.59. However, the implementation of a model stacking approach, which uses logistic regression as a meta-classifier to combine model predictions, dramatically improved the ability to correctly predict the protein targets of natural products and increased the AUROC score to 0.94 and BEDROC score to 0.73. This stacked model was deployed as a web application, called STarFish, and has been made available for use to aid in target identification for natural products.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

Systematic Protein Prioritization for Targeted Proteomics Studies through Literature Mining

There are more than 3.7 million published articles on the biological functions or disease implications of proteins, constituting an important resource of proteomics knowledge. However, it is difficult to summarize the millions of proteomics findings in the literature manually and quantify their relevance to the biology and diseases of interest. We developed a fully automated bioinformatics framework to identify and prioritize proteins associated with any biological entity. We used the 22 targeted areas of the Biology/Disease-driven (B/D)-Human Proteome Project (HPP) as examples, prioritized the relevant proteins through their Protein Universal Reference Publication-Originated Search Engine (PURPOSE) scores, validated the relevance of the score by comparing the protein prioritization results with a curated database, computed the scores of proteins across the topics of B/D-HPP, and characterized the top proteins in the common model organisms. We further extended the bioinformatics workflow to identify the relevant proteins in all organ systems and human diseases and deployed a cloud-based tool to prioritize proteins related to any custom search terms in real time. Our tool can facilitate the prioritization of proteins for any organ system or disease of interest and can contribute to the development of targeted proteomic studies for precision medicine.

Kinobead and Single-Shot LC-MS Profiling Identifies Selective PKD Inhibitors

ATP-competitive protein kinase inhibitors are important research tools and therapeutic agents. Because there are >500 human kinases that contain highly conserved active sites, the development of selective inhibitors is extremely challenging. Methods to rapidly and efficiently profile kinase inhibitor targets in cell lysates are urgently needed to discover selective compounds and to elucidate the mechanisms of action for polypharmacological inhibitors. Here, we describe a protocol for microgram-scale chemoproteomic profiling of ATP-competitive kinase inhibitors using kinobeads. We employed a gel-free in situ digestion protocol coupled to nanoflow liquid chromatography-mass spectrometry to profile ∼200 kinases in single analytical runs using as little as 5 μL of kinobeads and 300 μg of protein. With our kinobead reagents, we obtained broad coverage of the kinome, monitoring the relative expression levels of 312 kinases in a diverse panel of 11 cancer cell lines. Further, we profiled a set of pyrrolopyrimidine- and pyrazolopyrimidine-based kinase inhibitors in competition-binding experiments with label-free quantification, leading to the discovery of a novel selective and potent inhibitor of protein kinase D (PKD) 1, 2, and 3. Our protocol is useful for rapid and sensitive profiling of kinase expression levels and ATP-competitive kinase inhibitor selectivity in native proteomes.

The Life of Pi Star: Exploring the Exciting and Forbidden Worlds of the Benzophenone Photophore

The widespread applications of benzophenone (BP) photochemistry in biological chemistry, bioorganic chemistry, and material science have been prominent in both academic and industrial research. BP photophores have unique photochemical properties: upon n-π* excitation at 365 nm, a biradicaloid triplet state is formed reversibly, which can abstract a hydrogen atom from accessible C-H bonds; the radicals subsequently recombine, creating a stable covalent C-C bond. This light-directed covalent attachment process is exploited in many different ways: (i) binding/contact site mapping of ligand (or protein)-protein interactions; (ii) identification of molecular targets and interactome mapping; (iii) proteome profiling; (iv) bioconjugation and site-directed modification of biopolymers; (v) surface grafting and immobilization. BP photochemistry also has many practical advantages, including low reactivity toward water, stability in ambient light, and the convenient excitation at 365 nm. In addition, several BP-containing building blocks and reagents are commercially available. In this review, we explore the "forbidden" (transitions) and excitation-activated world of photoinduced covalent attachment of BP photophores by touring a colorful palette of recent examples. In this exploration, we will see the pros and cons of using BP photophores, and we hope that both novice and expert photolabelers will enjoy and be inspired by the breadth and depth of possibilities.

Invited Review: Toxicoproteomics: Proteomics Applied to Toxicology and Pathology

Global measurement of proteins and their many attributes in tissues and biofluids defines the field of proteomics. Toxicoproteomics, as part of the larger field of toxicogenomics, seeks to identify critical proteins and pathways in biological systems that are affected by and respond to adverse chemical and environmental exposures using global protein expression technologies. Toxicoproteomics integrates 3 disciplinary areas: traditional toxicology and pathology, differential protein and gene expression analysis, and systems biology. Key topics to be reviewed are the evolution of proteomics, proteomic technology platforms and their capabilities with exemplary studies from biology and medicine, a review of over 50 recent studies applying proteomic analysis to toxicological research, and the recent development of databases designed to integrate -Omics technologies with toxicology and pathology. Proteomics is examined for its potential in discovery of new biomarkers and toxicity signatures, in mapping serum, plasma, and other biofluid proteomes, and in parallel proteomic and transcriptomic studies. The new field of toxicoproteomics is uniquely positioned toward an expanded understanding of protein expression during toxicity and environmental disease for the advancement of public health.

Approaches for targeted proteomics and its potential applications in neuroscience

An extensive guide on practicable and significant quantitative proteomic approaches in neuroscience research is important not only because of the existing overwhelming limitations but also for gaining valuable understanding into brain function and deciphering proteomics from the workbench to the bedside. Early methodologies to understand the functioning of biological systems are now improving with high-throughput technologies, which allow analysis of various samples concurrently, or of thousand of analytes in a particular sample. Quantitative proteomic approaches include both gel-based and non-gel-based methods that can be further divided into different labelling approaches. This review will emphasize the role of existing technologies, their advantages and disadvantages, as well as their applications in neuroscience. This review will also discuss advanced approaches for targeted proteomics using isotope-coded affinity tag (ICAT) coupled with laser capture microdissection (LCM) followed by liquid chromatography tandem mass spectrometric (LC-MS/MS) analysis. This technology can further be extended to single cell proteomics in other areas of biological sciences and can be combined with other 'omics' approaches to reveal the mechanism of a cellular alterations. This approach may lead to further investigation in basic biology, disease analysis and surveillance, as well as drug discovery. Although numerous challenges still exist, we are confident that this approach will increase the understanding of pathological mechanisms involved in neuroendocrinology, neuropsychiatric and neurodegenerative disorders by delivering protein biomarker signatures for brain dysfunction.

Identifying compound efficacy targets in phenotypic drug discovery

The identification of the efficacy target(s) for hits from phenotypic compound screens remains a key step to progress compounds into drug development. In addition to efficacy targets, the characterization of epistatic proteins influencing compound activity often facilitates the elucidation of the underlying mechanism of action; and, further, early determination of off-targets that cause potentially unwanted secondary phenotypes helps in assessing potential liabilities. This short review discusses the most important technologies currently available for characterizing the direct and indirect target space of bioactive compounds following phenotypic screening. We present a comprehensive strategy employing complementary approaches to balance individual technology strengths and weaknesses.

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene

CONTEXT

Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD) superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential.

AIMS

In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets.

MATERIALS AND METHODS

In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO) database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE) study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3.

STATISTICAL ANALYSIS USED

Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold.

RESULTS

The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology.

CONCLUSIONS

The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis.

Quantitative proteomics of kinase inhibitor targets and mechanisms

Small molecule inhibitors of protein kinases are key tools for signal transduction research and represent a major class of targeted drugs. Recent developments in quantitative proteomics enable an unbiased view on kinase inhibitor selectivity and modes of action in the biological context. While chemical proteomics techniques utilizing quantitative mass spectrometry interrogate both target specificity and affinity in cellular extracts, proteome-wide phosphorylation analyses upon kinase inhibitor treatment identify signal transduction pathway and network regulation in an unbiased manner. Thus, critical information is provided to promote new insights into mechanisms of kinase signaling and their relevance for kinase inhibitor drug discovery.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

The use of affinity sorbents in targeted proteomics

The complexity of most proteomes is too high to obtain a truly comprehensive view of all expressed proteins by any of the current technologies. Prefractionation techniques are thus necessary to dig deeper into the low-abundance region of the proteome. Progress in the application of affinity sorbents to focus on particular protein classes of low abundance, while at the same time adding understanding about their function through the way they interact with the affinity ligands, will be described.:

The emerging field of chemo- and pharmacoproteomics

The emerging field of chemo- and pharmacoproteomics studies the mechanisms of action of bioactive molecules in a systems pharmacology context. In contrast to traditional drug discovery, pharmacoproteomics integrates the mechanism of a drug's action, its side effects including toxicity, and the discovery of new drug targets in a single approach. Thus, it determines early favorable (e.g. multiple kinase target in cancer drugs) and unfavorable (e.g. side effects) polypharmacology. Target profiling is accomplished using either active site-labeling probes or immobilized drugs. This strategy identifies direct targets and has in fact enabled even the determination of binding curves and half maximum inhibitory concentrations of these targets. In addition, the enrichment greatly reduces the complexity of the proteome to be analyzed by quantitative MS. Complementary to these approaches, global proteomics profiling studying drug treatement-induced changes in protein expression levels and/or post-translational modification status have started to become possible mostly due to significant improvements in instrumentation. Particularly, when using multidimensional separations, a considerable proteome depth of up to 10 000 proteins can be achieved with current state-of-the-art mass spectrometers and bioinformatics tools. In summary, chemo- and pharmacoproteomics has already contributed significantly to the identification of novel drug targets and their mechanisms of action(s). Aided by further technological advancements, this interdisciplinary approach will likely be used more broadly in the future.

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.

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 and mechanism of action in chemical biology and drug discovery

Target-identification and mechanism-of-action studies have important roles in small-molecule probe and drug discovery. Biological and technological advances have resulted in the increasing use of cell-based assays to discover new biologically active small molecules. Such studies allow small-molecule action to be tested in a more disease-relevant setting at the outset, but they require follow-up studies to determine the precise protein target or targets responsible for the observed phenotype. Target identification can be approached by direct biochemical methods, genetic interactions or computational inference. In many cases, however, combinations of approaches may be required to fully characterize on-target and off-target effects and to understand mechanisms of small-molecule action.

The evolving role of infectomics in drug discovery

Signatures of infectomes, which are encoded by both host and microbial genomes, and mirror the interplay between pathogens and their hosts, provide invaluable knowledge in the search for novel antimicrobial drugs. Infectomics is the study of infectomes by using systems biology and high-throughput omic approaches. There are three types of infectomic approaches that can be used for drug discovery: ecological infectomics, immunoinfectomics and chemical infectomics. Ecological infectomics, which is the ecological study of infectomes, explores symbiotic solutions to microbial infections. Research on drug discovery using infectomic signatures and immunomic approaches falls within the field of immunoinfectomics. Advances in chemical infectomics will lead to the development of a new generation of chemical drugs for therapeutics for microbial infections.

Target identification for small bioactive molecules: finding the needle in the haystack

Identification and confirmation of bioactive small-molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state-of-the-art. Among the techniques currently available, protein affinity isolation using suitable small-molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins.

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.

Gold nanoparticle-based immuno dual probes for targeting proteomics

Immunoprecipitation combined with mass spectrometry (MS) is a promising technique for targeting proteomics in characterizing submicrograms of target protein and interacting proteins in living cells. This method, however, is limited by interference arising from nonspecific binding. We report a novel gold nanoparticle (AuNP)-based immuno probe approach for immunoprecipitation. By cross-linking the antibody Fc domain to protein G covalently modified on AuNPs, the probe was fabricated and characterized to have 60 protein G and 30 immunoglobins per AuNP. We used human immunoglobin against the target and mouse immunoglobin with the same isotype (IgG) to fabricate the target and preclear probe, respectively, and termed it as the dual probe approach. Our results showed that the preclear probe (AuNP-IgG) and the target probe (AuNP-anti-ERα) share a similar panel of nonspecific binders but dramatic different specificity toward the target. Thus, using the dual probe method, we showed major nonspecific binders in the cell lysate could be largely removed without sacrificing the target protein. Compared to the conventional agarose gel-chromatography, the AuNP-based probe exhibited less nonspecific interference and higher recovery yield for ERα. Moreover, the AuNP-based probe is more inert than the agarose gel under harsh conditions and does not induce dissociation of the cross-linked IgG that could interfere with target identification. Using AuNP-based dual probes, ERα was shown to be purified from MCF-7 cells with minimum nonspecific binding. Moreover, the identity and phosphorylation sites on the C-terminus of the purified ERα could be positively confirmed by MS using only 1 mg of cellular protein.

Mass spectrometry approaches to monitor protein-drug interactions

Recent advances in mass spectrometry-based approaches have enabled the investigation of drug-protein interactions in various ways including the direct detection of drug-target complexes, the examination of drug-induced changes in the target protein structure, and the monitoring of enzymatic target activity. Mass spectrometry-based proteomics methods also permit the unbiased analysis of changes in protein abundance and post-translational modifications induced by drug action. Finally, chemoproteomic affinity enrichment studies enable the deconvolution of drug targets under close to physiological conditions. This review provides an overview of current methods for the characterization of drug-target interactions by mass spectrometry and describes a protocol for chemoproteomic target binding studies using immobilized bioactive molecules.

Mass spectrometry-based chemoproteomic approaches

The term "chemical proteomics" refers to a research area at the interface of chemistry, biochemistry, and cell biology that focuses on studying the mechanism of action of bioactive small molecule compounds, which comprises the mapping of their target proteins and their impact on protein expression and posttranslational modifications in target cells or tissues of interest on a proteome-wide level. For this purpose, a large arsenal of approaches has emerged in recent years, many of which employing quantitative mass spectrometry. This review briefly summarizes major experiment types employed in current chemical proteomics research.

Therapeutic potential and molecular mechanism of a novel sulfonamide anticancer drug, indisulam (E7070) in combination with CPT-11 for cancer treatment

PURPOSE

Indisulam (N-(-3-chloro-7-indolyl)-1,4-benzenedisulfonamide; E7070) is an experimental anticancer agent. Microarray analysis indicates that indisulam downregulates several genes involved in drug resistance, and this finding led us to test the effect of combining indisulam with other anticancer drugs. We investigated the antitumor effect and mechanism of synergism when indisulam was administered in combination with CPT-11.

METHODS

In vitro cytotoxic activity was examined using a cell counter kit, and the combination effect was determined by isobologram analysis. The level of topoisomerase IIα was measured by Western blotting. The in vivo antitumor effect was assessed in mice inoculated with human colorectal cancer SW620 cells.

RESULTS

Isobologram analysis indicated that a 24-h exposure to indisulam and SN-38, an active metabolite of CPT-11, had a synergistic effect in HCT116 and SW620 cells and an additive effect in HCT15 and WiDr cells. Prolongation of exposure to 48 h resulted in a synergistic effect in HCT15 and WiDr cells. Treatment with SN-38 alone increased the amount of intracellular topoisomerase IIα in all cell lines tested. Co-treatment with indisulam suppressed the SN-38-induced upregulation of topoisomerase IIα after 24 h of exposure in HCT116 and SW620 cells and after 48 h of exposure in HCT15 and WiDr cells. This apparent association between a synergistic effect and suppression of SN-38-mediated upregulation of topoisomerase IIα suggests that indisulam enhances SN-38 cytotoxicity by suppressing topoisomerase IIα upregulation to compensate for topoisomerase I inhibition by SN-38. Synergy was also observed in xenografted tumors and was accompanied by complete suppression of topoisomerase IIα upregulation induced by CPT-11 treatment.

CONCLUSION

These observations prompted the clinical evaluation of indisulam and CPT-11 combination therapy.

Compound immobilization and drug-affinity chromatography

Bioactive small molecules act through modulating a yet unpredictable number of targets. It is therefore of critical importance to define the cellular target proteins of a compound as an entry point to understanding its mechanism of action. Often, this can be achieved in a direct fashion by chemical proteomics. As with any affinity chromatography, immobilization of the bait to a solid support is one of the earliest and most crucial steps in the process. Interfering with structural features that are important for identification of a target protein will be detrimental to binding affinity. Also, many molecules are sensitive to heat or to certain chemicals, such as acid or base, and might be destroyed during the process of immobilization, which therefore needs to be not only efficient, but also mild. The subsequent affinity chromatography step needs to preserve molecular and conformational integrity of both bait compound and proteins in order to result in the desired specific enrichment while ensuring a high level of compatibility with downstream analysis by mass spectrometry. Thus, the right choice of detergent, buffer, and protease inhibitors is also essential. This chapter describes a widely applicable procedure for the immobilization of small molecule drugs and for drug-affinity chromatography with subsequent protein identification by mass spectrometry.

Nano-enabled biomarker discovery and detection

The completion of the human genome project has led to intensified efforts toward comprehensive analysis of proteomes. New possibilities exist for efficient proteomic technologies. However, primary attention is given to the discovery of new predictive biomarker patterns. Understanding proteomes and, in particular, protein-mediated interactions underlying their complexity and diversity, is critical for the development of more reliable and robust diagnostic platforms, which are anticipated to enable personalized medicine. Of immediate relevance in this respect are those approaches that capitalize on the application of nanotechnology, which is seen as a powerful tool for the diagnosis of early-stage diseases. Here we highlight the current state of the field exemplified by recent nano-enabled technologies for biomarker discovery.

The end game of chemical genetics: target identification

The use of classical genetic and molecular biology methods along with the sequencing of many genomes has proven crucial for elucidating complex biological processes. Despite being invaluable tools, their limitations have led to a search for more versatile alternatives and, thus, to the use of small molecules. Chemical genetics is a rapidly emerging field that uses small-molecule techniques to probe biological systems and is composed of three parts: natural product or small-molecule libraries, phenotypic screening and target identification. Currently, the biggest hurdle in the overall process of chemical genetics is target identification. Efforts to overcome this obstacle have led to advances in the areas of affinity chromatography, yeast haploinsufficiency, complementary DNA (cDNA) overexpression, DNA microarray, small-molecule microarray and RNA interference (RNAi) technologies. While these technologies continue to undergo further optimization, they have been integral in the identification and/or confirmation of many cellular targets and have seen an increase in applications to the drug-development process.