Among the many unprecedented and fundamental. Proteomics Approaches. in Drug Discovery. Understanding the. human genome is. important, but most

Transcription

1 Proteomics Approaches in Drug Discovery Understanding the human genome is important, but most pharmaceuticals target proteins. Among the many unprecedented and fundamental changes that occurred in our society during the past century, perhaps the most notable was the increase in the average life expectancy from 45 to 75 years of age in the United States (1). New drugs and vaccines directly improved life expectancy but presented new challenges. As the population ages, debilitating diseases such as Alzheimer s and Parkinson s disease and cancer can reduce the quality of life for many people. At the same time, new diseases with fatal consequences are emerging, including AIDS and variant Creutzfeldt Jakob disease, a human transmissible spongiform encephalopathy. The foremost challenge for drug discovery in the 21st century is to find new efficacious drugs to cure diseases and improve the quality of life. Addressing these complex challenges requires an indepth understanding of human biology. In the early 1980s, researchers proposed that sequencing the human genome would be the first step toward gaining a deeper understanding of human biology and diseases and provide new avenues for drug discovery. After 13 years of labor, researchers reported a working draft of the human genome (2 4). But the effort to sequence the human genome was only the tip of the iceberg. The true complexity of cellular biology exists at the level of proteins, not genes. Furthermore, the raw genetic sequence cannot predict a protein s function, localization, posttranslational modification, or expression level in different cells. In reality, most drugs target proteins. Therefore, the study of proteins and their functions might bridge the gap between drug discovery and human genomic information. Fortunately, in the 1990s, technologies to rapidly analyze proteins and study their functions were developed. The term proteome the ensemble of proteins related to a genome was coined (5). Techniques for proteomics originated with the coupling of 2-dimensional electrophoresis (2-DE) in gels to MS. Within seven years, proteomics had provided significant insight into biology and MARLENA ZUBER Daniel Figeys MDS-Proteomics (Canada) A UGUST 1, 2002 / ANALYTICAL CHEMISTRY 413 A

2 aided in drug discovery. Furthermore, interest in proteomics was evident in the literature: Publications about proteomics increased from merely a handful of articles in 1995 to over 1000 in The discipline is currently divided into three distinct classes: profiling, functional, and structural proteomics. Here, we introduce the different classes of proteomics and how they are becoming integral to drug discovery. Profiling proteomics Profiling proteomics is the original type of proteomics and still its most popular application. Basically, it consists of identifying the proteins present in a biological sample or the proteins that are differentially expressed between samples, such as diseased versus normal tissues. The result is a refined list of proteins that are present in a cell type or tissue or a list of the proteins that are up- or down-regulated (expressed at higher or lower levels than usual) between different cell states or tissues. 2-DE/MS. At first, profiling proteomics depended on 2-DE, which is a powerful technique that separates proteins in the first dimension according to their isoelectric point and in the second dimension by denaturing gel electrophoresis according to molecular weight. This combination of orthogonal separation techniques can separate up to 10,000 proteins (6, 7). 2-DE has been around for more than 25 years, so one might wonder why it has recently attracted such attention (8)! Because it is now feasible to systematically identify the proteins on a 2-D gel, thanks to the development of MALDI time-of-flight (TF) mass spectrometers and electrospray ionization (ESI) State 1 State 2 Protein A Protein B Protein C Protein N Extract proteins Protein mixture Mass spectrometer Proteolytic digestion Nano HPLC/MS/MS FIGURE 1. Profiling proteomics: Gel-free approach to protein identification. tandem mass spectrometers in the 1990s. These instruments measure peptide masses and permit the generation of fragmentation patterns related to an individual peptide amino acid sequence. Although the proteins prepared by 2-DE are stuck in a gel and thus, are not directly compatible with these instruments researchers realized that proteins isolated by 2-DE can be digested in-gel by a proteolytic enzyme, and the resulting peptides can be rapidly analyzed by MALDI-TF MS or ESI- MS/MS (9 11). Furthermore, mass spectra can be used to search protein and DNA sequence databases to identify the proteins. This combination of 2-DE, MS, and database searching was originally used to list the proteins in a sample. However, if this was the only application for profiling proteomics, we would not be talking about it anymore because diseases are all about changes in cellular processes. To identify the critical proteins in diseases and to be relevant for drug discovery, profiling proteomics had to follow the changes in proteomes during the progression of diseases by quantitatively mapping the proteins that differ between samples. ver the years, better software was developed to analyze 2-DE protein patterns, and differential approaches were developed to focus only on proteins for which the expression levels changed from sample to sample. Compared with whole-proteome methods, these differential approaches provide smaller lists of proteins, and when combined with other approaches, those lists can guide the selection of diagnostic markers and potential targets for drug discovery. Le Naour et al. recently illustrated the power of profiling proteomics when they used it to discover breast carcinoma proteins that elicit a humoral response that is, an immune response in the blood, mediated by antibodies (12). They assumed that proteins specific to cancer cells are secreted into the bloodstream and act as antigens; therefore, antibodies against specific proteins in breast Peptide mixture Liquid chromatograph/ autosampler The proteins isolated from two different cell types (states 1 and 2) are extracted and digested. The resulting peptides are analyzed by LC/ESI-MS/MS, and the proteins contained in each cell type are identified. cancer might be present in the patients sera. The researchers cultured a breast cancer cell line to generate sufficient proteins for 2-DE separation. A series of 2-DE gels were electroblotted to membranes and probed with individual serum extracted from cancer patients. An antihuman immunoglobulin G was then used as a secondary antibody to highlight the protein spots that indicated that human antibodies were present in the sera. The proteins that were markedly different in normal versus cancerous patients were analyzed by MS. In particular, the researchers discovered a protein called R S/DJ-1, which was detected at high levels in the sera of 37% newly diagnosed breast cancer patients. Thus, this elegant experiment used profiling proteomics to rapidly analyze breast cancer markers. 414 A ANALYTICAL CHEMISTRY / AUGUST 1, 2002

3 Gel-free approaches. Although 2-DE is a powerful separation technique, its limitations must be understood. In particular, 2-DE/MS does not offer a sufficient dynamic range for analyzing lowabundance proteins. This was demonstrated by Garrels et al. and Gygi et al., who performed a systematic MS analysis of yeast proteins separated by 2-DE and observed that only mid- to high-abundance proteins could be analyzed (13, 14). (Fey and Larsen published arguments that counter Gygi and Garrels [15].) In addition, 2-DE is tedious to perform and has difficulty dealing with hydrophobic and basic proteins. Substitutes that address such limitations are becoming increasingly attractive for profiling proteomics, especially methods that totally bypass 2-DE and analyze complex protein mixtures without gels (Figure 1). This is possible because of improvements in on-line peptide separation, the dynamic range of mass spectrometers, and software for protein identification. In the gel-free approach, a complex mixture of proteins is extracted from the biological material of interest and digested in solution to produce a complex mixture of peptides. The mixture of peptides is then separated on-line either by 1-D or 2-D HPLC and ESI-MS. The mass spectrometer is continuously triggered by the (a) ICAT for cysteine-containing peptides HN S NH N H N H Cell state 1 Cell state 2 Cell state 1 Cell state 2 Label with D0 Combine and digest with trypsin Label with D8 Purify label peptide on avidin column Analysis by MS (b) Generic approach based on 18 / 16 water Digest with trypsin in the presence of 16 water Digest with trypsin in the presence of 18 water Combine and analyze by MS FIGURE 2. Approaches to determine the relative changes in protein expression. (a) ICAT methodology, which is based on the differential labeling of cysteine-containing peptides and analysis by MS. stands for either hydrogen (D0 label) or deuterium (D8 label). (b) 18 / 16 water methodology based on the differential labeling of all the peptides and analysis by MS. eluting peptides to generate MS/MS spectra for the individual peptides. These spectra can then be searched against genomic and proteomic databases to identify the various proteins extracted from the cell. Is this work worth the effort? Yes. This approach has already demonstrated that low-abundance proteins can be discovered (16). Furthermore, characteristic hydrophilic peptides can be found in proteins that have a preponderance of hydrophobic amino acids. Finally, gel-free profiling proteomics can be performed on smaller amounts of material a smaller mass of cancerous cells, for example which could open the door to proteomic discovery in earlier stages of disease. Even so, the gel-free approach has its own limitations. First, the protein extract can be extremely complex in terms of the number and concentration of proteins. Moreover, the enzymatic digestion of the gel-free sample before MS analysis increases the complexity of the protein extract. For example, upon digestion, a mixture of 1000 proteins can easily yield a mixture with tens of thousands of peptides. Currently, the combined resolving power of 1-D or 2-D HPLC and MS does not surpass the separation power of 2-DE. Furthermore, unambiguous identification of proteins is not always feasible because fragmentation patterns in MS/MS spectra can only be obtained for a fraction of the peptides present in the gel-free sample. Another key challenge in proteomics is the quantitation of changes in protein expression between normal and diseased tissues. It is not unusual to see 10-fold changes in protein expression in such cases. More often, though, the changes can be subtle (i.e., less than 2-fold), yet they must be reproducibly measured across multiple samples. Another challenge in gel-free analysis is the relative quantitation of peptides. The traditional approach of staining a gel does not apply; instead, quantitation relies on the MS signal. In previous MS studies, researchers have quantified analytes by establishing response curves for particular analytes, but such curves are difficult to obtain for a constantly changing set of analytes, such as peptides obtained from a proteolytic digestion of complex proteins. Even two experiments run consecutively are difficult to compare in terms of peptide signal intensity. Fortunately, quantitative methods based on isotope tagging of peptides have recently been developed. These methods can be used on gel-free samples, and they allow direct comparison of the changes in expression levels between two proteomes in a single experiment. Various approaches have been recently proposed in particular, the isotope-coded affinity tag (ICAT) by Aebersold et al. (17), the N-terminal labeling of peptides by James et al. (18), and using 18 / 16 water by Stewart et al. and Mirgorodskaya et al. (19, 20). The ICAT method has been by far the most popular, mainly because kits that provide all the chemicals for protein labeling are commercially available. Briefly, the approach involves labeling cysteine-containing peptides from different samples with light versus heavy forms of a reactive chemical, which differ by 8 amu (17, 21, 22) (Figure 2a). The ICAT reagent consists of a biotin group followed by a linker and is terminated with a cysteinereactive group. Because the only difference between the light A UGUST 1, 2002 / ANALYTICAL CHEMISTRY 415 A

4 DNA-binding site Known protein A GAL4 DNA-binding domain Protein B Y GAL1-lacZ gene GAL4 activation domain GAL1-lacZ gene DNA FIGURE 3. Functional proteomics: Yeast two-hybrid approach. ff β-galactosidase activity n β-galactosidase activity Schematic of the classical two-hybrid approach using -galactosidase (GAL). Protein A is fused to the GAL4 DNA-binding domain. Protein B is attached to the GAL4 activation domain. Expression of -galactosidase is activated only when both hybrids are expressed in the same cell and proteins A and B interact. The presence of -galactosidase is assayed either by colony color using 5-bromo-4-chloro-3-indolyl -D-galactoside or by enzyme activity using chlorophenol red -D-galactopyranoside. and heavy tags is the presence of hydrogen or deuterium, the mass spectrometer responds similarly to both tags, yet there is a slight spacing of the m/z peaks on the spectrum. Because the peptides are identical in sequence yet do not completely quasico-elute, their relative abundances can be determined from the ratio of their peak intensities. In a typical ICAT experiment, one lysate sample is tagged with the light form of the reagent, and a second sample is tagged with the heavy form. Then, the two lysates are combined and enzymatically cleaved to generate peptide fragments. The cysteine-containing peptides are purified using a monomeric avidin column, which binds to the biotin in the tag. The purified peptides are separated on a nanoflow HPLC system, which is online with an ESI mass spectrometer. Finally, the automated generation of MS/MS fragmentation patterns of the peptides and database searching identify the peptide sequence and its protein provenance, and the relative quantitation is determined. More pairs of chemicals will soon become available for the relative quantitation of proteomes. This is important because the current methods may not accurately measure the expression levels of all proteins. First, the expression profile of a proteome is spread over a few orders of magnitude, which may not coincide with the dynamic range of a given chemical tagging approach. In addition, if only minute amounts of some proteins are present, a method might fail to label the peptides because of unfavorable kinetics. This is not an issue when large amounts of starting materials, such as yeast, E. coli, or blood, can be obtained; but performing ICAT, for example, on scarce samples such as cancerous cells from biopsies can be a problem. Fortunately, techniques such as 18 / 16 water labeling can be performed with a large excess of reagent, which allows minute amounts of proteins to be quantified in the gel-free approach (19, 20) (Figure 2b). Labeling with 18 / 16 water can be performed with a concentration of water up to 55 M, greatly favoring the reaction kinetics. Regardless of the technique, profiling proteomics only provides a list of proteins that are differentially expressed. This approach cannot indicate whether these proteins are involved in cellular changes or are merely side effects of those changes. For example, protein expression is often upregulated in cancerous cells, yet some of these increases simply indicate that the cells are rapidly growing and dividing and are not part of the cause. Functional proteomics To understand different cellular processes, one must understand how proteins function individually and in pathways. The function of a protein can be defined on the basis of its interactions, whereas pathways are cascades of specific protein interactions that are necessary to activate distinct cellular functions. Functional proteomics attempts to define a protein s role on the basis of the presence of specific functional groups or involvement in protein ligand interactions, protein complexes, and novel pathways. Mapping the complete set of protein interactions in humans could be a challenge. The human genome is estimated to contain 30,000 60,000 genes, producing perhaps millions of proteins if posttranslational modifications and mutations are included. Experience in mapping protein interactions suggests that each protein participates in an average of 5 10 interactions. In humans, that implies millions of possible interactions. Fortunately, advances in molecular biology have created genetically engineered systems capable of signaling the occurrence of interactions either directly or through an affinity-based protein purification approach. In particular, the two-hybrid system and protein affinity/immunoprecipitation with MS form the basic approaches to large-scale functional proteomics (23, 24). Two-hybrid approach. The two-hybrid approach to functional proteomics is an invaluable technology for studying binary protein protein interactions (23, 25). It answers the question, Is protein A binding to protein B?, by using a reporter gene to indicate when an interaction occurs between two chimeric, or hybrid, proteins (Figure 3). The method, which is performed in yeast, originated when researchers noticed that transcription factors include a DNA-binding domain and a transcription activation domain, both of which are fully functional on their own. These domains are normally close together, but even if they are encoded in separate genetic constructs, a gene can still be activated if the domains are brought into close proximity. In these experiments, one chimeric protein is created by expressing the first protein of interest called the bait, or protein A and fusing it to the DNA-binding domain of a transcription factor. This transcription factor lacks the transcription 416 A ANALYTICAL CHEMISTRY / AUGUST 1, 2002

5 activation domain, which is expressed separately as a fusion with the second protein of interest often called the prey, or protein B. nly when both fusion proteins are expressed and have interacted are all the elements in place to turn on the reporter gene. Thus, the reporter identifies cells in which proteins A and B interact. The DNA coding of the two fusion proteins can be done in different ways. In the classical high-throughput approach, plasmids encode the two fusion proteins (26). The first hybrid is constructed using the DNA-binding domain of the yeast s transcriptional activator protein (GAL4) coupled to a known protein. The second hybrid consists of the GAL4 activation domain coupled to a library of yeast genomic fragments. The yeast is then simultaneously transformed with the known protein hybrid and an element from the hybrid library. The yeast that incorporates both hybrids will grow on a histine- and leucine-depleted medium. Because the medium includes 5-bromo- 4-chloro-3-indolyl -D-galactoside, the yeast colonies in which the proteins interact will turn blue, indicating the activation of -galactosidase. In this way, a yeast genomic library can be rapidly screened for interactions with a known protein. ne variation is to express the protein A fusion and the protein B fusion in two different yeast strains, which must be mated to each other to determine if the proteins interact. This approach can reduce the number of transformations needed when multiple bait proteins are screened against multiple prey proteins. For example, if 10 bait and 5 prey proteins are used, 50 transformations are needed to cover all possible combinations in the traditional two-hybrid assay, but only 15 transformations 10 for the bait plasmids and 5 for the prey plasmids are needed for the mating assay. Large-scale two-hybrid studies are possible because the approach can be automated. In particular, a library of proteins attached to the activation domain can be screened in high throughput against a library of proteins attached to the DNA-binding domain. The two-hybrid method is not just for yeast proteins; it can be applied to discover the interactions between human proteins, albeit in the yeast environment. n the negative side, the two-hybrid method can only detect binary interactions. Protein interactions in cells are more intricate because proteins are involved in multiprotein complexes. Furthermore, human proteins are regulated by a series of posttranslational modifications and have specific localizations that The two-hybrid approach to functional proteomics is invaluable for studying binary protein protein interactions. cannot be mimicked by the two-hybrid approach. Ultimately, the best place to study the interactions between human proteins is in human cells. Protein tagging and immunopurification. Studying protein protein interactions directly in human cells has tremendous advantages: The proteins are properly folded and regulated, their localizations are appropriate, and the correct posttranslational modifications have been made. More importantly, deciphering protein complexes, pathways, and posttranslational modifications provides invaluable information for understanding cellular functions and for target drug validation. Fortunately, the combination of molecular biology, protein tagging, immunopurification, and MS has made possible the high-throughput analyses of human protein complexes formed in vivo (24) (Figure 4). Briefly, in this approach, the corresponding full-length complementary DNA (cdna) of a gene is cloned into a transfection vector. The vector is pre-encoded to add an epitope tag to either the N- or C-terminus of the protein. This vector is then added to a culture of human cells in the presence of an agent to facilitate the transfection. The DNA is rapidly transferred into the cells, and the cells express the tagged protein of interest, which performs its normal interactions and is properly localized. The cells are then collected and lysed, and the recovered supernatant is clarified and subjected to immunopurification using an immobilized antibody to capture the epitope tag. This step purifies and concentrates the tagged protein and all the proteins that interact with it in vivo. The purified protein fraction is then separated by 1-DE or 2-DE and analyzed by MS to identify the interacting proteins. A key issue with applying this approach to humans is obtaining the target genes coding material. Encoded genetic material can be carefully accessed at the messenger RNA (mrna) level and reverse-transcribed into cdna. Fortunately, collections of human cdna, which represent a large portion of the expressed genetic material, have been amassed. De novo cloning either directly from mrna or by using cdna pools is also standard practice. The systematic application of this approach to high-throughput studies provides a collection of interactions, complexes, and pathways that are useful for discovering novel protein targets. Recently, Ho et al. demonstrated the power of this approach in yeast (27). Their technique is readily applicable to humans. Gavin et al. also presented the high-throughput mapping of in- A UGUST 1, 2002 / ANALYTICAL CHEMISTRY 417 A

6 teractions in yeast, although their method is not directly applicable to humans (28). Chemiproteomics. Proteins also interact with a range of other molecules, such as drugs, lipids, and other small molecules. Chemiproteomics studies the interaction between small molecules and proteins, particularly drugs and proteins. Instead of using proteins as bait, chemiproteomics uses small molecules to fish for interacting proteins (29, 30). Drug companies are particularly eager to discover drug protein interactions because the majority of drugs act directly on proteins. So, finding the proteins that bind to a drug might aid in the discovery of new protein targets that can prolong the intellectual protection of current drugs or might help elucidate the side effects of a drug before it is released on the market. Chemiproteomics can be performed in vitro and in vivo. In the in vitro approach, the compound of interest is immobilized on beads or flat surfaces and used to probe a cell lysate for interacting proteins. After appropriate rinsing, the extracted proteins are digested and identified by MS. The advantage of this approach is that it can be used with cell cultures, tissues, and bodily fluids. ne disadvantage is that the proteins from the cell are combined in vitro, increasing the risk of degradation and false interactions. Another drawback is that the concentration of proteins decreases when cells are lysed. Thus, the drug protein interactions that were observed in vivo may not occur in vitro, depending on the on-rate (rate of ligand binding to the protein) and the incubation time. In the in vivo approach, cells are incubated with a drug that Vector tag Cell transfection Protein identified Bait Protein I Protein II Cell culture Gel electrophoresis and protein identification by MS tag FIGURE 4. Functional proteomics: Immunopurification of protein complexes. has been engineered to include a tag, which is not supposed to interfere with the drug s normal interactions or localization. The cells are then lysed, and the drug and the molecules with which it interacts are affinity-purified using the tag. After proper rinsing, the interacting proteins can be digested and identified by MS. The drug protein interactions truly occur inside the cell; therefore, the proper localization, normal protein concentrations, and appropriate cellular processes are in place. The disadvantage of this approach is that the tag might, in reality, disturb the drug s localization or interactions. Although chemiproteomics is a promising new technology for discovering drug targets, technological improvements in drug immobilization and tagging are still needed. Nevertheless, chemiproteomics could become a high-throughput approach for rapidly screening drug libraries against different cells to discover protein drug interactions. For example, high throughput could be achieved for the in vitro approach by immobilizing drug libraries or for the in vivo approach by tagging a drug library. Phosphoproteomics. Protein protein interactions in cells do not occur randomly. Regulatory mechanisms activate proteins and allow interactions to occur at appropriate times. Such regulation might include the posttranslational modification of a protein, the increased expression of a protein involved in a pathway, or the degradation of a protein. Posttranslational modifications are important regulatory elements of protein protein interactions. In particular, the phosphorylation of serine, threonine, and tyrosine are known to be involved in protein regulations. Simplistically, phosphorylation of proteins is comparable with switching the function of a Harvesting/lysis Immunopurification, denaturation Schematic of the over-expression of a tag protein for the in vivo capture of protein complexes. The transfected cells are harvested and lysed, and the protein complex of interest is extracted using the tag on the bait protein and an immobilized antitag antibody. protein on and off or modulating protein activity through increasing phosphorylation. The study of protein phosphorylation is important in pharmaceutical research because diseases are often due to modifications that affect the phosphorylation pattern of proteins and, therefore, their interactions. MS-based techniques have been developed and reviewed for the low-throughput analysis of protein phosphorylation (31 33). Until recently, the large-scale application of these approaches was limited by the sensitivity and throughput that could be achieved with these methods. However, phosphoproteomics a new subfield for the large-scale mapping of protein phosphorylation sprouted from recent developments in the field of phosphorylation mapping by MS. Although the selective purification of phosphoproteins and 418 A ANALYTICAL CHEMISTRY / AUGUST 1, 2002

7 phosphopeptides has been the limiting factor of high-throughput phosphoproteomic mapping, new approaches have been developed for the selective purification of phosphorylated peptides on the basis of their chemical derivatization (34 36). Zhou et al. used a six-step chemical derivatization approach to purify and analyze phosphorylated peptides by MS (34). da et al. proposed a method that involves the chemical replacement of phosphorylated serine and threonine by a biotin moiety, which can then be used for the selective enrichment of the derivatized peptides (35). Goshe et al. reported a phosphoprotein isotopecoded affinity tag based on the -elimination applied to serine and threonine followed by biotinylation to introduce an affinity purification tag (36). These approaches still achieve limited sensitivity but clearly demonstrate that phosphoproteomic studies might be feasible. Ficarro et al. recently reported a breakthrough: They developed a novel MS approach that rapidly and globally analyzes the phosphorylation switchboard on a proteomic scale (37). They combined chemical derivatization with affinity purification of phosphorylated peptides, followed by automated MS identification and mapping of the peptides. Using yeast, they demonstrated that 383 phosphorylation sites could be rapidly mapped. Furthermore, they achieved a sufficient level of detection to identify rare protein phosphorylations, such as tyrosine phosphorylation in yeast and the phosphorylation of low-abundance proteins. The new frontier Structural proteomics is one of the less-developed areas of proteomics. Typically, it attempts to rapidly determine the tertiary structures of proteins, mainly using -ray crystallography and the prediction of protein structures by computational biology. Various projects are currently under way for large-scale -ray crystallography of proteins and domains, either by a large-scale crystallization effort (38, 39) or by systematic elucidation of domains. Researchers have come a long way since the early days of proteomics by 2-DE. Looking ahead, we can expect profiling proteomics to play an important role in the discovery of disease markers and provide lists of potential drug targets. Similarly, functional proteomics has a broad applicability across the drugdiscovery pipeline, from target prioritization to extending or recycling drugs. Finally, structural proteomics is uncovering the 3-D structures of proteins, which will have an impact on drug designs and the modeling of drug docking (ligand binding) and provide a framework for the structural modeling of novel proteins. I would like to acknowledge Rachel Figeys for reviewing this manuscript. Daniel Figeys is the vice president of analytical sciences at MDS- Proteomics. 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