Journal of Proteomics & EnzymologyISSN: 2470-1289

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Review Article, J Proteomics Enzymol Vol: 6 Issue: 1

An Overview of Proteomics Techniques and its Application as a Tool in Biomarker and Drug Discovery

Roopesh Krishnankutty1, Ajaz A Bhat1, Asfar S Azmi2, Serhiy Souchelnytskyi3, Shahab Uddin1, Abdul B Abou-Samra1 and Ramzi M Mohammad1*
1Academic Health System, Translational Research Institute, Hamad Medical Corporation, Doha, State of Qatar
2Wayne State University School of Medicine, Detroit, Michigan, USA
3College of Medicine, Qatar University, Doha, State of Qatar
Corresponding author : Ramzi M. Mohammad, PhD
Professor, Director, Translational Research Institute, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar
Tel: (974)-443-90497
Fax: (974)-443-98792
E-mail: [email protected]
Received: October 04, 2016 Accepted: December 16, 2016 Published: January 19, 2017
Citation: Krishnankutty R, Bhat AA, Azmi AS, Souchelnytskyi S, Uddin S, et al. (2017) An Overview of Proteomics Techniques and its Application as a Tool in Biomarker and Drug Discovery. J Proteomics Enzymol 6:1. doi: 10.4172/2470-1289.1000129


Introduction: Proteomics technology is extensively used to identify the underlying molecular mechanisms of various diseases. Emergent technologies in proteomics have been used in the biomarker and drug discovery process. Proper use of this technology can enable the understanding of mechanism of drug action; efficacy and toxicity, there by facilitating effective translation of the drug from bench to bedside.

Areas covered: The major techniques used in proteomics technology with an application in drug discovery process are discussed. An overview on different kinds of proteomic approaches and their application in various fields of biomarker discovery as well as drug development process has also been presented.

Conclusions: Proteomics technology serves as a promising approach by providing unbiased information about protein-protein interactions, post-translational modifications and regulatory mechanisms. Owing to the complexity of the proteomes the technology needs to be complemented with other omics techniques which could revolutionize drug development process. Advanced instrumentation with improved sensitivity, selectivity coupled with efficient proteomics work flows can facilitate comprehensive characterization of various proteomes for potential drug targets

Keywords: Biomarkers; Drug discovery; Mass spectrometry; Proteomics; Stable isotope labeling


Biomarkers; Drug discovery; Mass spectrometry; Proteomics; Stable isotope labeling


The process of discovering drug targets when explained in scientific context are quite complex. The process is quite tedious with the number of trial experiments to be performed to look at the possibilities of drug-to-target interactions that needs to be tested under in vitro conditions followed by in vivo and ultimately,the necessity of passing rigorous pharmacokinetic and toxicology studies successfully, before the drug canbe considered for clinical trials [1]. To make the drug development process faster and more cost-effective many new technologies has been adopted. Among them, proteomics technology gained much attention as this technology is being used effectively in the process of drug discovery and development including target discovery, mechanism of action and even predicting toxicity of the drugs.
Proteomics can be defined as the large-scale comprehensive study of a specific proteome wherein, proteome stands for the entire set of proteins being expressed by an organism, specific cell type or tissue at a given condition and given time [2,3]. During recent years, proteomics technology has gained lot of demand among the scientists as applying this technology helps in better understanding of disease prognosis as well as pathogenesis, discovery of novel and reliable biomarkers that could help in the early prediction or detection of diseases. Biomarkers can be defined as molecules that indicate changes in the physiological state of a particular cell under diseased condition and can be used as a diagnostic tool for monitoring prognosis or pathogenesis of diseases [4]. Biomarkers are increasingly emerging as a vital tool that could act as indicators even in drug trial experiments at an early stage so that the go or no-go decisions can be made early which can significantly enhance the drug development process.

Proteins as Drug Targets

Majority of the drugs act by binding to specific protein(s) thereby blocking its further functionality in the cellular process. Hence the proteins that are being expressed within specific tissues under diseased condition forms the major targets for drug discovery and development process [5]. An effective target discovery system should have the capability to enable the detection of these proteins in specific tissues which are likely to be targets for therapeutic and diagnostic development. Proteomics technology stands as an efficient and reliable tool to carry out the comprehensive analysis for the identification of these complex proteins. The ability of proteomics technology to measure quantitatively to a depth of 10,000 proteins their changes as well as various isoforms with dynamic range in abundance makes it an important tool in the drug discovery process [6,7].
Target-based drug discovery approaches start with the selection of a protein astarget based on its presumed role in the process of disease development. Biochemical assays using crude and purified protein (presumed as target) are used to monitor changes in the activity of the target and then to identify potential positive hits using high-throughput screening. After several positive hits, the target will be validated using many assay protocols using selected compounds and further the lead compounds will be optimized with regard to their potency, selectivity, pharmacodynamics and pharmacokinetic properties and finally will be tested in appropriate disease model systems for their in vivo efficacy [8].

Proteomics Techniques

Proteomics technology plays a pivotal role in drug development process as because majority of drugs act by targeting proteins or they by themselves are protein. Proteomics based approaches integrates techniques involving high-throughput separation of digested proteins: peptides using liquid chromatography (LC), peptide sequencing by mass spectrometry (MS), followed by genomic database search and bioinformatics. Considering the advances in proteomics technology, there is an increasing interest in applying this technology to improve the drug discovery process. Though proteomics technology can be classified into different types, in the context of drug discovery process, it can be classified into three major classes: expression/ profiling, functional and structural proteomics. Different types of proteomics techniques, their advantages, disadvantages and potential applications are described in Table 1.
Table 1: Types of Proteomics techniques, advantages, disadvantages and its potential application.

Expression/ Profiling Proteomics

Protein profiling, the traditional proteomics approach can be classified as expression/ profiling proteomics and forms the most popular application. It is a way of looking at the pattern of proteins expressed in a specific tissue, cell or even body fluid. Profiling is carried out as comparative analysis, for example, to identify the differentially expressed proteins between a healthy or control sample and diseased or drug-treated sample. The profiling results in a list of proteins those are present in a specific proteome or a list of the proteins that are up- (expressed at higher) or down-regulated (expressed at lower levels) between different proteomes with regard to comparative profiling. Further, validation and characterization can lead to identification of proteins that are disease related and act as drug targets. Traditionally the tools used in proteomics were twodimensional gel electrophoresis (2-DGE) as technique for separation and mass spectrometry (MS) for protein identification [9]. Figure 1 represents a schematic workflow of the various techniques involved in the proteomics technology.
Figure 1: Mass spectrometry based (bottom-up/shotgun) proteomics workflow. As depicted in the figure, the initial step is to extract proteins from cells/ tissues/ body fluids followed by its separation or fractionation using gel-based or gel free approaches. The fractionated proteome/proteins digested by proteolytic enzyme (e.g. trypsin) purified and cleaned up for LC-MS/MS analysis. Peptides separated by liquid chromatography analyzed by mass spectrometry. MS spectral data are processed by software for protein identifications. Bioinformatics and statistical tools are applied for data interpretation. Potential candidate protein(s) are further validated using different biochemical techniques (e.g. ELISA, western blotting).

Two-dimensional Gel Electrophoresis (2-DGE)

Two-dimensional gel electrophoresis (2-DGE) is a conventional and most commonly used technique in proteomics. It can be said as the traditional gold standard tool used in proteomics technology. This technique has been mostly employed in studying the changes in protein expression of specific proteomes [10]. The technique involves separating proteins according to their isoelectric point in the first dimension and in the second dimension according to their molecular weight by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The proteins separated in gels are visualized by staining them with either coomassie blue or silver stain. The gel images are analyzed using software aided computer. Protein spots of interest are identified, sliced off from gel and further subjected to in-gel digestion using trypsin. The peptide mixtures obtained are separated by technique of liquid chromatography and analyzed using mass spectrometry (MS), results in obtaining peptide sequences which are matched against available proteome databases to determine the protein identifications [11].

Mass Spectrometry (MS)

Mass spectrometry (MS) is an analytical tool that forms the core of proteomics technology. The recent advances in the field of MS with improved sensitivity, resolution as well as accuracy have made it the most favorite tool of choice in proteomics. These instruments uses an ion source to ionize the proteins/ peptides resolved by a mass analyzer based on mass to charge ratio m/z of the peptides which is finally displayed as a mass spectrum with an incrementing peptide mass from low to high.
The techniques used in MS are of two types: matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDITOF MS) [12,13] and electrospray ionization tandem MS (ESI-MS/ MS) [14]. In MALDI-TOF MS, peptides are co-crystallized with a chemical matrix to form spots on sample plates. A laser beam excites the peptides by energy transfer through the matrix and the ionized molecules are resolved by time of flight inside a vacuum tube until it reaches detector. In ESI MS/MS, peptides carried by the solvent is sprayed into the ion source as a fine mist and peptides get ionized as charged droplets when the solvent is evaporated in a high vacuum chambers (ion traps) and are resolved resulting in MS spectra. Further peptide ion (parent ion) can be selectively trapped inside the chambers (ion traps) using filters and undergo collision in the presence of an inert gas, so that the chosen peptide (parent ion) gets fragmented into daughter ions. The fragment ions get resolved based on their m/z ratio and results in MS2 spectra. By combining the MS2 spectra of the daughter ions (small peptides), the sequence of the parent peptide can be deduced.

Gel-free Proteomics

Gel free proteomics is one of the attractive techniques used in clinical proteomics biomarker discovery [15]. In gel-free proteomics approach, proteins extracted from a cell or tissue or a specific proteome is digested in-solution resulting in a complex mixture of peptides. This peptide mixture is separated by High performance liquid chromatography (HPLC) or Ultra HPLC (UHPLC) and analyzed by a mass spectrometer. The HPLC system is coupled to the MS, wherein the eluting peptides are ionized by the electro spray ionization (ESI) technique generating MS/MS spectra of the individual peptides. The peptide spectra are then searched against proteomic databases to obtain the protein identifications. The gel-free proteomic profiling approach has been proved to have the potential in identifying low-abundance proteins [16]. The advantage of gel-free proteomics technique is that the workflows are not tedious and this approach can be used to analyze small masses of diseased tissues or extracts.

Capillary Electrophoresis-Mass Spectrometry (CEMS)

Capillary electrophoresis coupled to mass spectrometry (CE-MS) forms one of powerful analytical tool for characterization of proteins as the efficient separation by CE is complemented by the sensitivity and selectivity of MS [17,18]. CE-MS is applied widely in the field of discovery proteomics especially in clinical proteomics to identify biomarkers for various diseases using tissue samples or body fluids [19]. The slow flow rate as well as the high resolution of peaks from complex mixtures makes CE more attractive means of separation for high sensitivity and accuracy for mass spectrometry based analysis. In CE-MS approach, electro spray ionization (ESI) is the most frequently used MS interface that accounts for a soft ionization method which allows the formation of multi-charged ions enhancing the MS sensitivity [20]. CE-MS has been successfully applied in clinical proteomics for biomarker discovery specifically for body fluid proteomics or peptidomics by analysis of peptides in body fluids such as blood, urine and cerebrospinal fluid (CSF) [21].

Quantitative Proteomics

One of the gel-free approaches in proteomics technology that is becoming increasingly popular is termed quantitative proteomics. It can be defined as a technique used to quantitatively measure the differences in expression of proteins among different biological states or tissues or proteomes (e.g. healthy vs. diseased, control vs. treated). Two types of quantitative proteomics approaches exist: absolute and relative. Absolute quantification helps in estimating the exact amount or concentration of a protein while,with relative quantitation, a relative fold change of protein abundance in different samples can be obtained [22]. In quantitative proteomics, two kinds of approaches are used: label-free and stable isotopic labeling.

Label-free Proteomics

The label-free approach uses two different methods for quantitation: spectral counts and peptide peak intensity. Quantitation by spectral counting involves comparing the number of spectra identified from the same protein between different samples [23]. This method relies on the presence of abundant proteins which produces more MS/MS spectra compared to the low abundant proteins and hence, the high abundant peptides are sampled more times than the low abundant peptides. This quantitation method based on spectral counts can be said as protein-centered, as it requires enough amounts of peptides from the digested proteins to generate MS/MS spectra for quantification and identification [24]. Quantitation by peptide peak intensity is measured by comparing the peptide ion intensities wherein the peptides are obtained from a given protein [25]. In this method, the ion chromatograms of each peptide obtained from LCMS analysis are extracted and the peptide peak areas are integrated over their retention time.

Difference Gel Electrophoresis (DIGE)

Difference gel electrophoresis is a gel-based technique used in quantitative proteomics for the quantification of proteins from complex mixtures. In DIGE proteins are labeled by fluorescent tags that are separated by electrophoresis and detected by optical fluorescence [26]. Further, the proteins of interest can be excised from the gel, processed and identified by mass spectrometry. The technique is used mainly to detect the change of expression levels of proteins enabled by the differentially labeled proteins [27]. DIGE can also detect proteins with modification with respect to its size or its iso-electric point and can identify post-translational modifications as well. DIGE combined with the technique of 2D (two-dimensional gel electrophoresis) called as 2D-DIGE is widely used to identify protein biomarkers by comparative protein expression profiling. The technique of DIGE and 2D-DIGE have been applied widely in clinical proteomics research, for e.g. to identify biomarkers for Edwards syndrome [28], plasma biomarker for esophageal squamous cell carcinoma [29], adrenocortical carcinoma [30] etc.

Stable Isotope Labeling

Stable isotope labeling technique involves the addition of a specific mass tag to the protein or peptide which only alters their overall mass keeping their properties intact and not hinders with chromatographic separation or MS analysis [22]. Quantitation can be performed by comparing the abundance of tagged or labeled peptide for e.g. ‘heavy labeled’ (with known concentration, acts as internal standard) vs. the ‘light’ isoforms [31]. These stable isotope labels (tags) can be added either at the protein level or at the peptide level by using metabolic or chemical labeling methods [32].
In metabolic labeling method, the stable isotope(s) are introduced to the whole cells via growth medium as supplements so that after cell division the isotope labels get incorporated into the proteome [33]. The technique used for metabolic labeling is known as stable isotope labeling with amino acids in cell culture (SILAC) which was introduced by Ong group in 2002 [34]. In SILAC method, the whole proteome is labeled by in vivo incorporation of heavy and light forms of amino acids such as arginine or lysine. The tryptic digestion of labeled proteins results in peptides that carry at least one labeled amino acid with the specific tag of altered mass compared to the nonlabeled proteins. The isotopically labeled (heavy or light) samples are pooled together or combined for LC-MS analysis and this pooling of samples in the upstream of the proteomics workflow results in an efficient quantitation process with less variations otherwise can be introduced during the sample processing. The SILAC method has been successfully used to label whole organisms such as mice [35] and flies [36] which was achieved by feeding them the diet supplemented with heavy or light amino acids used for SILAC labeling. A recent report by Liberski et al. [37] demonstrated the use of a customized feeder-free SILAC media to obtain reproducible labeling and the technique was used to perform quantitative proteomics study to understand the mechanisms behind human embryonic stem cells (hESCs) differentiation.
SILAC is a preferred method of choice under stable isotope labeling technique because the labels are introduced at the early stage of sample preparation which can drastically reduce the errors or variables in quantitation process. But this method has the limitation such as that not all of the cell lines can grow on SILAC media thereby restricting the labeling efficiency. Also it is practically difficult to label whole higher organisms for e.g. labeling a human tissue or a whole human being is very difficult wherein the ethical issues also exists and above all it is regarded as a costly method of labeling because commercially available SILAC media are very expensive.
In chemical labeling method, the stable isotope labels are added to the proteins or peptides via chemical reaction. One of the popular techniques using chemical labeling protocol is named isotope-coded affinity tags (ICAT) [38]. In ICAT labeling method, the cysteine residues of peptides are specifically labeled by selective alkylation with either a zero (do) ‘light’ or eight (d8) deuterium atoms by a chemical reagent and this reagent also contain a biotin group which enables the affinity purification of labeled peptides. The peptides are purified by passing through avidin-agarose column and the ICAT-labeled peptides are subjected to LC-MS analysis. Although this technique has the advantage that the cysteine-labeled peptides can be selectively analyzed, which helps in the better identification of low-abundance proteins as well as reduces the complexity of the peptide mixture, it holds the disadvantage that some of the proteins has no cysteines or in other cases the quantitation has to be performed based on single peptide identification which will negatively impact the confidence of protein identification.
The other types of chemical labeling techniques involves the labeling of the N-terminus of the peptide as well as the epsilon-amino group of lysine residues via chemical reagents and they includes: isotope-coded protein label (ICPL) [39], isotope tags for relative and absolute quantification (iTRAQ) [40], tandem mass tags (TMT) [41] and dimethyl labeling. The ICPL method relies on the stable isotope labeling of the frequent free amino groups of the intact protein. The advantage of this technique is the compatibility of this method with the separation methods used in proteomics as well as it can be applied to many kinds of protein samples including tissue or body fluids and can also be applied for the identification of post-translational modifications [42].
The iTRAQ method depends on the covalent labeling of the N-terminus and the side chain amines of the peptides. This method of isobaric mass tagging produces labeled peptides with different mass tags but of the same total mass that co-elute in the LC and in the MS analysis, peptide fragmentation (MS2) leads to the identification of the differentially tagged peptides. This method helps in both the identification as well as the abundance of the peptide pairs in the mass spectra [40]. The reagents for iTRAQ/ TMT labeling are commercially available in the form of kits and this allows multiplexed analysis of upto eight samples in one experiment. This capability of multiplexing has made this method much handier for quantitative analysis of multiple samples at a time and has been used in biomarker discover processes [43].
Stable isotope dimethyl labeling is a type of chemical labeling method which uses the chemistry of reductive amination. In this method the primary amines (N-terminus and the side chain of lysine residues) of peptides are chemically modified to incorporate dimethyl amines using the reagents formaldehyde and cyanoborohydride. A combination of several isotopomers of these two reagents can result in a triplex labeling strategy wherein the labeled peptides can have a mass difference of 4 daltons (Da) between them [44]. This method of chemical labeling can be applied to a variety of samples and has been shown to be suitable for quantitative mass spectrometry analysis including the post-translational modifications such as phosphoproteomics as demonstrated by recent studies [45-47].
In addition to the metabolic and chemical labeling, an enzymatic labeling method also exists and 18O labeling falls under this category. This method relies on the catalytic action of protease enzyme such as trypsin that results in exchanging two 16O atoms from 18O atoms of the C-terminal of the peptides and produces differentially labeled peptides which will have a mass shift of 4 Da in the MS spectra [48,49]. Many of the studies have shown to use this labeling method to perform quantitative proteomics of cultured cells [49,50], serum [51,52], tissues [53,54] and also for quantitation of post-translational modifications [55,56].

Targeted Proteomics

Another approach that is being increasingly used in proteomics to identify biomarkers or potential drug targets is known as targeted proteomics [57,58]. The technique being used in this approach is known as selected reaction monitoring (SRM) or multiple reaction monitoring (MRM). To perform a proteomics analysis using a triple quadrupole MS in the SRM mode, the precursor ion as well as the target ions of the specifically targeted peptides should be preknown. In SRM technique, the targeted precursor ion is selected in the first quadrupole and in the second quadrupole which acts as a collision cell, the precursor ion is fragmented and finally in the third quadrupole the desired fragment ion is trapped. The SRM/ MRM technique uses a selective number of proteins/ peptides for analysis in MS and is very high-throughput technique with better sensitivity and reproducibility. The SRM technique has been used in drug metabolism studies to quantify the metabolites which has been carried out in a technically advanced mass spectrometer equipped with a triple quadrupole [59].

Functional Proteomics

The various cellular processes are dependent on the kinds of proteins present in there and also on the functions of proteins including specific protein-protein interactions as well as different signaling pathways that results in various cellular activities. Hence, it is necessary to understand these complex protein functions to define the various cellular activities. In this context the necessity of functional proteomics arises. Functional proteomics can be defined as the large-scale study of proteins at their functional level that is their expression, interaction and modifications [60]. This technique can help in identifying the role of a protein based on specific functional group or any kind of interactions such as protein-protein or proteinsubstrate or formation of any complexes or any functional pathways [61].
The technique of functional proteomics addresses two major questions. The first one is to find out the biological function(s) of an unknown protein that could be inferred as a potential target for drug discovery or a biomarker for disease identification. The second one is to define the mechanism of action of the protein at the molecular level by either direct interaction or being a part of a complex pathway. Identifying the protein-protein interaction can help in unraveling the underlying molecular mechanism of a specific cellular pathway leading to the definition of a biological function [62,63]. The two common types of MS based methods used in functional proteomics are the two-hybrid system and protein affinity/ immunoprecipitation [64].

Two-hybrid System

The two-hybrid system is used as a major tool in functional proteomics to study protein-protein interactions. The comprehensive analysis of the protein-protein interactions using the two-hybrid system was first performed in budding yeast. The method relies on the fact that, in yeast the transcription factors included a DNA-binding domain and a transcription activation domain that remains close together, were fully functional independently and it has been noticed that, a gene can be activated even if the domains are in two separate constructs and have been brought them in close proximity [65].
In this approach, a first protein of interest (Protein A) is expressed as a fusion/ chimeric protein by fusing it to a DNA binding domain (DBD) of a transcription factor and this fusion protein is called ‘bait’. This transcription factor will not have the transcription activation domain and hence the reporter gene will not be activated. The second protein of interest (Protein B) is expressed as another chimeric protein by fusion to activation domain (AD) and is called ‘Prey’. When the bait and prey are co-expressed and the proteins A and B interacts, a functional transcription factor complex is formed which will turn on the transcription of reporter gene [66]. The method has been used for the identification of protein partners of ZnF224, a zinc-finger protein belonging to the zinc-finger proteins family KRAB-ZFPs which forms one of the largest classes of transcription factors [67].

Tagging and Immunoprecipitation Approach

The best environment to study the protein-protein interactions is inside a cell as because in there, they are properly localized, regulated and even modified. When these interactions can be studied at their native environment that can throw lots of information on complex formations, signaling pathways and its regulations leading to various cellular functions and the proteins identified can form potential therapeutic targets for drug discovery process. High-throughput proteomic analysis using the techniques of protein tagging and immunopurification can enable the detection of protein-protein interactions [64].
In this method, the full length complementary DNA (cDNA) of a gene of interest is cloned into a vector and transfected into culture of human cells. The vector is designed to add an epitope tag to the N-terminus or C-terminus of the protein making the cells to express the protein of interest as a tagged one. Inside the cell the protein will carry out its functions involving interactions or complex formations or regulations. The cells are then ruptured and the protein extract is subjected to purification by immune-affinity purification which results in an enriched elute with the tagged protein as well as its other in-vivo interacting partners. The enriched elute is subjected to 1-DE or 2-DE for further fractionation followed by MS analysis leading to the identification of interacting proteins [66]. In a recent study by Schwertman et al. [68], the method of protein tagging and immuneaffinity purification was used to perform the proteomic analysis of endogenously ubiquitinated protein complexes. In this study, mass spectrometric analysis of two FK2 immunoprecipitations (IPs) resulted in identification of 296 FK2-specific proteins and also the protein–protein interactions revealed significantly more FK2-specific proteins presence in protein complexes than in random protein sets. Ho et al. [63] and Gavin et al. [62] have shown the power of using this technique for high-throughput analysis of protein interactions in yeast.


Chemoproteomics or chemical proteomics forms a new discipline of proteomics that deals with the study of interaction between proteins and small molecules such as drugs or lipids. In this approach, small molecules are used to fish out the interacting partners [69]. The technique holds a great potential in drug discovery process as the proteins that binds to a drug helps in the discovery of new drug targets. Three major approaches of chemoproteomics exist and they can be categorized as: affinity pull-down, Capture Compound Mass Spectrometry (CCMS) and affinity-based protein profiling [70-72].
In affinity pull-down technique the small molecule of choice such as a drug is modified to carry an affinity tag biotin and the small molecule is immobilized onto a surface [73]. The small molecule will act as the probe for interaction with proteins resulting in selective binding and the probe-protein complexes are further isolated by affinity purification mediated by biotin tag followed by MS analysis leading to the identification of interacting proteins.
In Capture Compound Mass Spectrometry [CCMS], the so called probe will have the components: small molecule of choice- a drug, the affinity tag- biotin, a reactive group for cross linking. The additional reactive group enables covalent bond formation of probe with the interacting protein thereby enhancing the yield of probe-protein complex during affinity purification. Studies have been reported using this technique to isolate proteins such as kinases and methyl transferases [74,75].
The affinity-based protein profiling (ABPP) is the third type of chemoproteomics technique and it has got two elements: the small molecule of choice- a drug is designed to interact with the protein through a covalent bond formation in the active site and the second element is a reporter tag that is functional and enables the enrichment and visualization of the interaction. This technique has the advantage that it not only measures the abundance of a specific protein but also tells the functional state of that protein which is very helpful in functional characterization of the identified protein in the context of protein-drug interaction.
A study conducted by Fadden et al. [76] has used the chemoproteomics approach in the identification of a clinical candidate targeting hsp90. In this study screening of 8000 member library resulted in identifying over 1500 unique protein-ligand interactions, which included novel hits for the oncology target Hsp90. The approach also led to the identification of a potent and orally active Hsp90 inhibitor, SNX-5422, which has been passed into the phase 1 clinical studies.

Reverse-phase Protein Microarrays

The Reverse Phase Protein Array (RPPA)is an antibodybased high-throughput technique used in proteomics [77]. In this technique, the proteins extracted from samples are separated by SDS-PAGE (1-DE) and are printed on to nitrocellulose-coated plates which are subsequently probed against specific antibodies. Compared to the other techniques such as western blot, ELISA or mass spectrometry, this technique has got significant advantages in terms of flexibility, sensitivity, data consistency and even speed of analysis. This technique allows simultaneous analysis of phosphorylated, glycosylated, cleaved and even total cellular proteins on multiple samples [78]. The multitude of data generated from this technique can provide valuable information with regard to the potential drug targets or biomarkers that could be useful as diagnostic or prognostic tools for disease identification [77,79,80]. A recent study conducted by O’Mahony et al. [81] used the RPPA technique to explore the protein expression variation in renal cell cancers. Tibes et al. [82] has shown the robustness of using RPPA technique in the analysis of primary acute myelogenous leukemia samples as well as leukemic and hematopoietic stem cells.


Post-translational modifications (PTMs) involve the addition of a modifying group to one or more of the amino acids of the protein or a proteolytic cleavage that alters the properties of protein [83]. The major modifications include phosphorylation, glycosylation, ubiquitination, nitrosylation, methylation, acetylation, lipidation and proteolysis and influence almost all aspects of normal cell biology and pathogenesis. PTMs have been reported to play key roles in many cellular functions/ processes such as differentiation [84], regulation as well as signaling [85], protein degradation [86] and protein-protein interactions.
Among PTMs, protein phosphorylation is one of the most commonly studied post-translational modifications. It can be said as a reversible modification adjusting the folding and making the protein to play its functional roles which includes enzymatic activities, substrate specificities, protein localization, complex formation and even protein degradation [87]. Hence, this form of PTM can have major influence on several cellular functions such as cell cycle progression, differentiation, transformation, development and adaptation. Mass spectrometry based techniques in proteomics have been developed to perform the analysis of protein phosphorylation which is termed as phosphoproteomics [88,89]. Since the analysis of phosphopeptides in MS is mostly suppressed by lower abundance of phosphopeptides over non-phosphorylated species, specific enrichment of phosphorylated proteins/ peptides is needed to carry out the phosphoproteomic studies [90].
Immobilized metal-ion affinity chromatography (IMAC) originally introduced by Porath et al. [91] for purification of his-tagged proteins, is the most commonly used technique for phosphoprotein/ peptide enrichment [92]. In IMAC, the phosphoprotein/ peptides bind to the positively charged metal ions in the stationary phase by electrostatic interactions. Non-phosphorylated species are washed off due to non-specific binding and the phosphoprotein/ peptides are eluted by either salt or pH gradients. A six-step derivatization method was used by Zhou et al. [93] to purify phosphopeptideswhile performingphosphoproteomic analysis. The group of Oda et al. [94] used the method of replacing the phosphorylated serine and threonine by a biotin moiety, which then helps in the selective purification of derivatized peptides. Goshe et al. [95] proposed a method of enriching the phosphopeptides by using a phosphoprotein isotope-coded affinity tag for purification process. Gruhler et al. [96] has used the technique of phosphoproteomics to identify and quantify the phosphoproteins that acts as regulators and effectors of a G-protein-coupled receptor involved in yeast pheromone signaling pathway.

Structural Proteomics

Structural proteomics forms one of the less-developed fields in proteomics. High-resolution structural information of proteins that acts as targets can help the process of drug discovery efficient and faster. This technology involves high-resolution structure determination of proteins by X-ray crystallography or nuclear magnetic resonance (NMR) techniques followed by their structure prediction/ elucidation using computational approaches [97,98]. Once the three-dimensional (3D) model of a protein is obtained, then this model can used to find promising binding sites for a potential drug. The best model can be determined when a stable interaction is observed between the drug and the 3D protein model. For an effective drug discovery process it is rather important to obtain the high resolution structure of the ‘protein/ target of choice’ than getting the known structures of similar proteins. This technology has many challenges, such as the time required to determine the structure of a protein may vary from months to years. The computational approach gives the best fit model assumed to be the stable form under ‘in silico’ state, while in an ‘in vivo’ state, the active protein may take a different form due to the interaction with other molecules that are involved in that particular biological process.

Proteomics as a Tool in Biomarker and Drug Discovery

The use of proteomics technology for the discovery of biomarkers that could serve as potential drug targets has attracted a lot of attention of the research community during recent years. The mass spectrometry based high-throughput techniques have resulted in the selective analysis of proteins, their modification as well as interactions making the process of identification of potential drug targets easy. Most of the biomarkers form the proteins that are specifically diseaseassociated and have an altered/ variant expression levels in different kinds of tissues or cell types. Considering this complexity, proteomics technology offers a powerful platform for the identification of biomarkers and their characterization so that they can be targeted for drug discovery processes.
The process of drug discovery involves a sequence of steps starting with target identification, screening of small molecules, specificity and optimization, toxicity followed by pre-clinical and clinical testing. Several approaches in proteomics enable the identification of proteins that are involved in the pathophysiological condition of a disease and comparative expression profiles of these proteins in diseased to the healthy states can determine their capability to serve as a biomarker or a potential drug target (Figure 2). In certain cases, specifically identified biomarkers can act as protein signatures which can be used for drug screening processes and throws light on the drug efficacy, resistance and toxicity. It is not only the discovery and verification, but also validation is necessary for the biomarkers in order to qualify them as potential drug targets.
Figure 2: Schematic representation of a proteomics approach towards drug discovery process. Proteins extracted from normal vs. diseased tissues separated and differentially expressed protein(s) identified. The identified protein isolated, crystallized and structure elucidated by X-ray crystallography. The 3-dimensional structure of protein facilitates the process of drug discovery by designing appropriate blockers that could serve as a potential drug.
Clinical trials using the proteomics technology for biomarker/ drug targets discovery in many types of diseases including cancers are ongoing. In many types of cancers, multiple cell signaling pathways have been found to be dysregulated which leads to the progression and metastasis. Identifying and targeting the main components of dysregulated signaling pathways can result in a better management of disease improving the overall survival rate. Several studies in this direction exist. For example, in ovarian cancer, the pI3K pathway is dysregulated due to a somatic gain-of-function mutation in PI3KCA which results in the hyper activation of this pathway and hence inhibition of apoptosis [99]. Similar hyper activation of PI3K pathway has been reported in other types of cancers [100-102]. Molecules that target PI3K pathway and its downstream effectors like Akt and mTOR are currently under clinical investigation [103]. In addition proteomic assays have been developed to assess the abnormal changes in PI3K/AKT/mTOR pathway [104,105].
Although molecular profiling at the gene level can help in categorizing patient population based on their disease stage or survival outcome this is not sufficient enough to provide a clear picture of the disease states as the transcript level does not really match with the functional protein being expressed by the gene. Also the profiling at the gene level cannot provide sufficient information with regard to the protein-protein interactions or protein posttranslational modifications. Thus applying the proteomics technology in molecular profiling of diseased samples can help in screening the entire pathological signaling pathway leading to the identification of potential drug targets [106]. The key molecules involved in most of the signaling pathways are the protein kinases which act as cellular ‘gate keepers’ and their abnormal functional activation has been found to be a key in many disease states including cancer [107]. In the context of drug discovery process, the focus of current and future research is directed towards the designing of novel small molecules as inhibitors of specific kinases. A major breakthrough in this field was the discovery of STI-571 (Gleevec, imatinibmesylate) which specifically target the enhanced activity of abl kinase protein in T-cell leukemia [108,109]. Moreover, many other small molecules that have been found to block kinase activity are currently under clinical investigations [110-131].
Furthermore, in the field of cancer proteomics, identification of functional biomarkers to understand disease development and classification, tumor metastasis, heterogeneity and response to the treatment are of major concerns. The identified biomarkers should be highly sensitive and specific as they serve as signatures to cancer detection, prognosis and even for selective therapies. To search for novel biomarkers, the proteomics technology can be helpful in the comprehensive analysis of cancer proteomes identifying potential protein markers that are involved in disease pathogenesis. Several studies have been reported on the identification of biomarkers that serves as prognostic, diagnostic as well as early detection markers (Table 2). Intense research in this area is currently ongoing and proteomics technology can serve as an efficient platform to make this biomarker discovery process smooth and effective.
Table 2: Summary of few protein markers established through proteomics approach.

Conclusions and Perspectives

Proteomics technology has been evolving much rapidly and widely used in biomarker and drug discovery process. Increased sensitivity with high-throughput approaches has made this technology much reliable for identification of biomarkers that could form potential drug targets or as diagnostic tools for early detection of various diseases. Well characterized biomarkers can enhance the understanding of mechanism of drug action, its efficacy and toxicity which can facilitate effective translation of a proposed drug from pre-clinical to clinical phase and thereby improving the efficiency of drug discovery process. Comprehensive proteomic analysis using various techniques as applied using different proteomics workflows can help in dissecting the proteins involved in key signaling pathways which can define the potential drug targets. Identification of specific molecular markers such as receptor/secretory proteins can lead to improvement in choosing right adjuvants for drug development that can result in less expensive and better treatment strategies.
As proteins form the most important class of molecules being targeted by pharmacological agents, high-throughput technology such as proteomics can help in unravelling the complexity of proteins involved in diseased states which can improve the characterization of these molecules as drug targets. The use of this technology for discovery of novel and validated biomarkers can broaden our current understanding of various diseases and can lead to the development of vital drugs as well as for effective targeted therapies.
Over the years the proteomics technology has progressed well enough and its application in biomarker discovery and drug development processes have been overwhelming. In the context of biomarker and drug discovery, proteomics technology serves in the identification of altered protein expression patterns in a pathological condition and holds the advantage that the identified proteins form the potential therapeutic drug targets. Proteomics offers unprecedented ability to monitor in the same experiment both a drug and its target. Mass spectrometry imaging is a promising example of integration of detection of a drug in the examined section of a tissue, protein/peptide markers, and at the same time integration with patho-histological analysis of the same tissue sample. The further developments in proteomics technology must incorporate a multitude of techniques which would enhance more data generation as well as interpretation for better understanding of the cellular functions and regulatory mechanisms. On this regard, an integration of interdisciplinary approaches that combines the aspects of biology, chemistry, engineering and informatics that work in harmony would be a better promising complementation to the existing proteomics technology. With that perspective, the technology becomes more applicable particularly to all areas of drug discovery from target identification to the clinical trial settings. It is obvious that the current proteomics technologies reviewed here will be even more efficient, more sensitive, robust and easier to use. We foresee that these technologies will be complemented by other tools in future.
Proteomics as a technique has already taken a lead role in discovery of biomarkers, drug targets and in the drug development process which is exemplified by the fact that most of the new drugs coming to the clinic have a companion diagnostic that is frequently proteomics-based. Today, proteomics technology is fully integrated with other omics technologies, e.g. genomics, transcriptomics, metabolomics along with novel informatics tools and systems biology which can tremendously promote the speed of drug discovery and development process.
The challenges in proteomics technology owes mainly to the complexity of the proteomes, protein concentrations, their posttranslational modifications as well as protein-protein interactions. These can be overcome by advanced instrumentation methods with improved sensitivity, selectivity and speed. In addition, improved proteomics workflows with less tedious, efficient sample preparation with enhanced protein/peptide yields and deep proteome coverage can facilitate success in comprehensive profiling studies. Better integration of the technologies with a nurtured symphony in sample preparation, separation, analysis and interpretation can enhance the potential of proteomics in identifying specific biomarkers that can be used in clinical diagnosis, as therapeutic drug targets or as markers of drug efficacy and toxicity. Above all, advanced and sophisticated bioinformatics tools could provide added support in handling large datasets for this technology to flourish with glory. To conclude, future advancements and improvements in proteomics technology will fuel the hunt for safer, responsive and cost-effective drugs.


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