Large-scale Analysis Of Proteins Research Articles

High-resolution antibody array analysis of proteins from primary human keratinocytes and leukocytes.

Antibody array analysis of labeled proteomes has high throughput and is simple to perform, but validation remains challenging. Here, we used differential detergent fractionation and size exclusion chromatography in sequence for high-resolution separation of biotinylated proteins from human primary keratinocytes and leukocytes. Ninety-six sample fractions from each cell type were analyzed with microsphere-based antibody arrays and flow cytometry (microsphere affinity proteomics; MAP). Monomeric proteins and multi-molecular complexes in the cytosol, cytoplasmic organelles, membranes and nuclei were resolved as discrete peaks of antibody reactivity across the fractions. The fractionation also provided a two-dimensional matrix for assessment of specificity. Thus, antibody reactivity peaks were considered to represent specific binding if the position in the matrix was in agreement with published information about i) subcellular location, ii) size of the intended target, and iii) cell type-dependent variation in protein expression. Similarities in the reactivity patterns of either different antibodies to the same protein or antibodies to similar proteins were used as additional supporting evidence. This approach provided validation of several hundred proteins and identification of monomeric proteins and protein complexes. High-resolution MAP solves many of the problems associated with obtaining specificity with immobilized antibodies and a protein label. Thus, laboratories with access to chromatography and flow cytometry can perform large-scale protein analysis on a daily basis. This opens new possibilities for cell biology research in dermatology and validation of antibodies.

Integrating proteomic and phosphoproteomic data for pathway analysis in breast cancer

BackgroundAs protein is the basic unit of cell function and biological pathway, shotgun proteomics, the large-scale analysis of proteins, is contributing greatly to our understanding of disease mechanisms. Proteomics study could detect the changes of both protein expression and modification. With the releases of large-scale cancer proteome studies, how to integrate acquired proteomic and phosphoproteomic data in more comprehensive pathway analysis becomes implemented, but remains challenging. Integrative pathway analysis at proteome level provides a systematic insight into the signaling network adaptations in the development of cancer.ResultsHere we integrated proteomic and phosphoproteomic data to perform pathway prioritization in breast cancer. We manually collected and curated breast cancer well-known related pathways from the literature as target pathways (TPs) or positive control in method evaluation. Three different strategies including Hypergeometric test based over-representation analysis, Kolmogorov-Smirnov (K-S) test based gene set analysis and topology-based pathway analysis, were applied and evaluated in integrating protein expression and phosphorylation. In comparison, we also assessed the ranking performance of the strategy using information of protein expression or protein phosphorylation individually. Target pathways were ranked more top with the data integration than using the information from proteomic or phosphoproteomic data individually. In the comparisons of pathway analysis strategies, topology-based method outperformed than the others. The subtypes of breast cancer, which consist of Luminal A, Luminal B, Basal and HER2-enriched, vary greatly in prognosis and require distinct treatment. Therefore we applied topology-based pathway analysis with integrating protein expression and phosphorylation profiles on four subtypes of breast cancer. The results showed that TPs were enriched in all subtypes but their ranks were significantly different among the subtypes. For instance, p53 pathway ranked top in the Basal-like breast cancer subtype, but not in HER2-enriched type. The rank of Focal adhesion pathway was more top in HER2- subtypes than in HER2+ subtypes. The results were consistent with some previous researches.ConclusionsThe results demonstrate that the network topology-based method is more powerful by integrating proteomic and phosphoproteomic in pathway analysis of proteomics study. This integrative strategy can also be used to rank the specific pathways for the disease subtypes.

High-Resolution Nano-Liquid Chromatography with Tandem Mass Spectrometric Detection for the Bottom-Up Analysis of Complex Proteomic Samples

Liquid chromatography coupled with mass spectrometric detection is one of the major technologies used for protein sequencing, identification, and quantification. This review provides an introduction of the current state-of-the-art technology in peptide profiling using nano-liquid chromatography–mass spectrometry applied to large-scale protein or proteome analysis. In particular, different aspects of the bottom-up proteomics workflow are covered, including aspects of sample preparation such as protein digestion, nanoflow gradient reversed-phase chromatographic separation, LC–MS interfacing via electrospray ionization, tandem mass spectrometry of digests, protein identification via database searches, and finally peptide quantitation.

Duplications and losses of genes encoding known elements of the stress defence system of the Aspergilli contribute to the evolution of these filamentous fungi but do not directly influence their environmental stress tolerance.

The contribution of stress protein duplication and deletion events to the evolution of the Aspergilli was studied. We performed a large-scale homology analysis of stress proteins and generated and analysed three stress defence system models based on Saccharomyces cerevisiae, Schizosaccharomyces pombe and Aspergillus nidulans. Although both yeast-based and A. nidulans-based models were suitable to trace evolutionary changes, the A. nidulans-based model performed better in mapping stress protein radiations. The strong Mantel correlation found between the positions of species in the phylogenetic tree on the one hand and either in the A. nidulans-based or S. cerevisiae-based models on the other hand demonstrated that stress protein expansions and reductions contributed significantly to the evolution of the Aspergilli. Interestingly, stress tolerance attributes correlated well with the number of orthologs only for a few stress proteins. Notable examples are Ftr1 iron permease and Fet3 ferro-O2-oxidoreductase, elements of the reductive iron assimilation pathway, in the S. cerevisiae-based model, as well as MpkC, a HogA-like mitogen activated protein kinase in the A. nidulans-based model. In the case of the iron assimilation proteins, the number of orthologs showed a positive correlation with H2O2-induced stress tolerance while the number of MpkC orthologs correlated positively with Congo Red induced cell wall stress, sorbitol induced osmotic stress and H2O2 induced oxidative stress tolerances. For most stress proteins, changes in the number of orthologs did not correlate well with any stress tolerance attributes. As a consequence, stress tolerance patterns of the studied Aspergilli did not correlate with either the sets of stress response proteins in general or with the phylogeny of the species studied. These observations suggest that stress protein duplication and deletion events significantly contributed to the evolution of stress tolerance attributes of Aspergilli. In contrast, there are other processes, which may counterbalance the effects of stress gene duplications or deletions including (i) alterations in the structures of stress proteins leading to changes in their biological activities, (ii) varying biosynthesis of stress proteins, (iii) rewiring stress response regulatory networks or even (iv) acquiring new stress response genes by horizontal gene transfer. All these multilevel changes are indispensable for the successful adaptation of filamentous fungi to altering environmental conditions, especially when these organisms are entering new ecological niches.

Identification of MS-Cleavable and Noncleavable Chemically Cross-Linked Peptides with MetaMorpheus.

Protein chemical cross-linking combined with mass spectrometry has become an important technique for the analysis of protein structure and protein-protein interactions. A variety of cross-linkers are well developed, but reliable, rapid, and user-friendly tools for large-scale analysis of cross-linked proteins are still in need. Here we report MetaMorpheusXL, a new search module within the MetaMorpheus software suite that identifies both MS-cleavable and noncleavable cross-linked peptides in MS data. MetaMorpheusXL identifies MS-cleavable cross-linked peptides with an ion-indexing algorithm, which enables an efficient large database search. The identification does not require the presence of signature fragment ions, an advantage compared with similar programs such as XlinkX. One complication associated with the need for signature ions from cleavable cross-linkers such as DSSO (disuccinimidyl sulfoxide) is the requirement for multiple fragmentation types and energy combinations, which is not necessary for MetaMorpheusXL. The ability to perform proteome-wide analysis is another advantage of MetaMorpheusXL compared with programs such as MeroX and DXMSMS. MetaMorpheusXL is also faster than other currently available MS-cleavable cross-link search software programs. It is imbedded in MetaMorpheus, an open-source and freely available software suite that provides a reliable, fast, user-friendly graphical user interface that is readily accessible to researchers.

Proteomic analysis of Tn-bearing glycoproteins from different stages of melanoma cells reveals new biomarkers

Cutaneous melanoma, the most aggressive form of skin cancer, responds poorly to conventional therapy. The appearance of Tn antigen-modified proteins in cancer is correlated with metastasis and poor prognoses. The Tn determinant has been recognized as a powerful diagnostic and therapeutic target, and as an object for the development of anti–tumor vaccine strategies. This study was designed to identify Tn-carrying proteins and reveal their influence on cutaneous melanoma progression. We used a lectin-based strategy to purify Tn antigen-enriched cellular glycoproteome, the LC-MS/MS method to identify isolated glycoproteins, and the DAVID bioinformatics tool to classify the identified proteins. We identified 146 different Tn-bearing glycoproteins, 88% of which are new. The Tn-glycoproteome was generally enriched in proteins involved in the control of ribosome biogenesis, CDR-mediated mRNA stabilization, cell-cell adhesion and extracellular vesicle formation. The differential expression patterns of Tn-modified proteins for cutaneous primary and metastatic melanoma cells supported nonmetastatic and metastatic cell phenotypes, respectively. To our knowledge, this study is the first large-scale proteomic analysis of Tn-bearing proteins in human melanoma cells. The identified Tn-modified proteins are related to the biological and molecular nature of cutaneous melanoma and may be valuable biomarkers and therapeutic targets.

Large-scale aggregation analysis of eukaryotic proteins reveals an involvement of intrinsically disordered regions in protein folding

A subset of the proteome is prone to aggregate formation, which is prevented by chaperones in the cell. To investigate whether the basic principle underlying the aggregation process is common in prokaryotes and eukaryotes, we conducted a large-scale aggregation analysis of ~500 cytosolic budding yeast proteins using a chaperone-free reconstituted translation system, and compared the obtained data with that of ~3,000 Escherichia coli proteins reported previously. Although the physicochemical properties affecting the aggregation propensity were generally similar in yeast and E. coli proteins, the susceptibility of aggregation in yeast proteins were positively correlated with the presence of intrinsically disordered regions (IDRs). Notably, the aggregation propensity was not significantly changed by a removal of IDRs in model IDR-containing proteins, suggesting that the properties of ordered regions in these proteins are the dominant factors for aggregate formation. We also found that the proteins with longer IDRs were disfavored by E. coli chaperonin GroEL/ES, whereas both bacterial and yeast Hsp70/40 chaperones have a strong aggregation-prevention effect even for proteins possessing IDRs. These results imply that a key determinant to discriminate the eukaryotic proteomes from the prokaryotic proteomes in terms of protein folding would be the attachment of IDRs.

Mass Spectrometry-Based Proteomics.

Proteomics is the large-scale analysis of proteins rendered possible by modern mass spectrometry analysis methods capable of identifying thousands of peptides/proteins in a fast high-throughput manner. Here I describe protocols for the preparation of fungal culture protein samples for mass spectrometry-based proteomics analysis including protein sample cleanup, proteolytic digestion, LC-MS/MS separation, and database search protein identification.

Understanding the Evolutionary Relationship of M2 Channel Protein of Influenza A Virus and its Structural Variation and Drug Resistance

Background: M2 channel protein of influenza A virus is one of the specific targets for the anti-influenza drugs amantadine and rimantadine. These drugs have lost their efficacy because of the mutations in their drug interaction sites. Large-scale analysis of these influenza surface proteins may give better elucidation for understanding the evolution of the proteins toward the drug resistant mechanism. Keywords: Amantadine, evolutionary lineage, influenza A virus, M2 channel protein, rimantadine.

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders.

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions.

Molecular insights into the functional role of nitric oxide (NO) as a signal for plant responses in chickpea.

The molecular mechanisms and targets of nitric oxide (NO) are not fully known in plants. Our study reports the first large-scale quantitative proteomic analysis of NO donor responsive proteins in chickpea. Dose response studies carried out using NO donors, sodium nitroprusside (SNP), diethylamine NONOate (DETA) and S-nitrosoglutathione (GSNO) in chickpea genotype ICCV1882, revealed a dose dependent positive impact on seed germination and seedling growth. SNP at 0.1mM concentration proved to be most appropriate following confirmation using four different chickpea genotypes. while SNP treatment enhanced the percentage of germination, chlorophyll and nitrogen contents in chickpea, addition of NO scavenger, cPTIO reverted its impact under abiotic stresses. Proteome profiling revealed 172 downregulated and 76 upregulated proteins, of which majority were involved in metabolic processes (118) by virtue of their catalytic (145) and binding (106) activity. A few crucial proteins such as S-adenosylmethionine synthase, dehydroascorbate reductase, pyruvate kinase fragment, 1-aminocyclopropane-1-carboxylic acid oxidase, 1-pyrroline-5-carboxylate synthetase were less abundant whereas Bowman-Birk type protease inhibitor, non-specific lipid transfer protein, chalcone synthase, ribulose-1-5-bisphosphate carboxylase oxygenase large subunit, PSII D2 protein were highly abundant in SNP treated samples. This study highlights the protein networks for a better understanding of possible NO induced regulatory mechanisms in plants.

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells.

Proteomics is the large-scale analysis of proteins. Proteomic techniques, such as liquid chromatography tandem mass spectroscopy (LC-MS/MS), can characterize thousands of proteins at a time. These powerful techniques allow us to have a systemic understanding of cellular changes, especially when cells are subjected to various stimuli, such as infections, stresses, and specific test conditions. Even with recent developments, analyzing the exosomal proteome is time-consuming and often involves complex methodologies. In addition, the resultant large dataset often needs robust and streamlined analysis in order for researchers to perform further downstream studies. Here, we describe a SILAC-based protocol for characterizing the exosomal proteome when cells are infected with HIV-1. The method is based on simple isotope labeling, isolation of exosomes from differentially labeled cells, and mass spectrometry analysis. This is followed by detailed data mining and bioinformatics analysis of the proteomic hits. The resultant datasets and candidates are easy to understand and often offer a wealth of information that is useful for downstream analysis. This protocol is applicable to other subcellular compartments and a wide range of test conditions.

Mass Spectrometric Analysis of S-palmitoylation of Hemagglutinin from Influenza A Virus

Abstract S-palmitoylation in protein is one of the most important kinds of lipid modification and plays a vital role in cell signal transduction, metabolism and other processes. S-palmitoylation is formed by covalently binding of palmitic acid with sulfhydryl group of cysteine residue in protein through thioester bond. In this study, acyl-biotin exchange reaction was firstly used to convert S-palmitic acid on the hemagglutinin protein from influenza A virus into biotin-labeled tag. The biotin-labeled protein was then enriched by streptavidin-linked beads and further purified by electrophoresis, followed by in-gel digestion. The results showed that the ratio of biotin concentration of the sample with hydroxylamine treatment (+HA) to that of the sample without hydroxylamine treatment (−HA) was larger than 3. Mass spectrometric analysis of the digestion mixture of the enriched hemagglutinin protein from influenza A virus identified two S-palmitoylation modification sites that were located on carboxyl terminal region of hemagglutinin protein such as Cys562 and Cys565, respectively. This research offers a specific and effective method for large-scale analysis of S-palmitoylated proteins.

A proteomic approach to compare saliva from individuals with and without oral leukoplakia

BackgroundOral leukoplakia is the most common potentially malignant disorder in the oral cavity and can precede carcinoma. This study aimed to identify possible oral leukoplakia salivary biomarkers. MethodsUnstimulated saliva was collected from participants and protein concentration was determined. Proteins were then precipitated with cold acetone and separated using 2DE over a pH range of 3–10. Spot demarcation and matching were performed and protein identification was done through MS analysis. Oral leukoplakia tissues were submitted to immunohistochemistry analysis for keratin 10 (CK10). A complementary analysis of oral leukoplakias that were not included previously was performed in addition. Results226±10 spots were identified in oral leukoplakia 2DE gels, and 262±12 spots were identified in volunteers. Twenty-two spots were highly abundant in oral leukoplakias or not detected in the control group, such as apolipoprotein A1, alpha amylase, cystatins, keratin 10, and lysozyme precursor. All were identified. All oral leukoplakia cases were immunopositive for CK10, mainly in the superficial epithelial layers. ConclusionsThe 2DE salivary protein profiles of individuals with and without oral leukoplakia were observably different. CK10 appears to be an interesting protein and should be further studied in oral carcinogenesis. SignificanceMS-based proteomics enables large-scale analysis of proteins. Proteomics can provide detailed descriptions of proteomes of cells and tissues, including body fluids, and appears as a powerful tool to study human disorders. Saliva is readily accessible through non invasive collection and can mirror diverse disease states. Saliva from both diseased and healthy subjects can be analyzed through 2DE and differences between groups could be found. Routine immunohistochemistry analysis confirmed one of these findings, with CK10 being positive tissues from individuals with oral leukoplakia. Therefore, the present study allows insights into development of an important potential oral cancer precursor, named oral leukoplakia. However, the results can be extrapolated and tested in other precancer states, such as proliferative verrucous leukoplakia, patients at risk of oral cancer due to lifestyle behavior and/or cancer history in the family or even those who are under surveillance after a treated primary oral cancer.

Review on proteomics for food authentication

Consumers have the right to know what is in the food they are eating. Accordingly, European and global food regulations require that the provenance of the food can be guaranteed from farm to fork. Many different instrumental techniques have been proposed for food authentication. Although traditional methods are still being used, new approaches such as genomics, proteomics, and metabolomics are helping to complement existing methodologies for verifying the claims made about certain food products. During the last decade, proteomics (the large-scale analysis of proteins in a particular biological system at a particular time) has been applied to different research areas within food technology. Since proteins can be used as markers for many properties of a food, even indicating processes to which the food has been subjected, they can provide further evidence of the foods labeling claim. This review is a comprehensive and updated overview of the applications, drawbacks, advantages, and challenges of proteomics for food authentication in the assessment of the foods compliance with labeling regulations and policies. SignificanceThis review paper provides a comprehensive and critical overview of the application of proteomics approaches to determine the authenticity of several food products updating the performances and current limitations of the applied techniques in both laboratory and industrial environments.

Dynamic changes of histone H3 marks during Caenorhabditis elegans lifecycle revealed by middle-down proteomics.

We applied a middle-down proteomics strategy for large-scale protein analysis during in vivo development of Caenorhabditis elegans. We characterized PTMs on histone H3 N-terminal tails at eight time points during the C. elegans lifecycle, including embryo, larval stages (L1-L4), dauer, and L1/L4 postdauer. Histones were analyzed by our optimized middle-down protein sequencing platform using high mass accuracy MS/MS. This allows quantification of intact histone tails and detailed characterization of distinct histone tails carrying cooccurring PTMs. We measured temporally distinct combinatorial PTM profiles during C. elegans development. We show that the doubly modified form H3K23me3K27me3, which is rare or nonexistent in mammals, is the most abundant PTM in all stages of C. elegans lifecycle. The abundance of H3K23me3 increased during development and it was mutually exclusive of the active marks H3K18ac, R26me1, and R40me1, suggesting a role for H3K23me3 in silent chromatin. We observed distinct PTM profiles for normal L1 larvae and for L1-postdauer larvae, or L4 and L4 postdauer, suggesting that histone PTMs mediate an epigenetic memory that is transmitted during dauer formation. Collectively, our data describe the dynamics of histone H3 combinatorial code during C. elegans lifecycle and demonstrate the feasibility of using middle-down proteomics to study in vivo development of multicellular organisms. All MS data have been deposited in the ProteomeXchange with identifier PXD002525 (http://proteomecentral.proteomexchange.org/dataset/PXD002525).

Advances in proteomics analytical techniques

Proteins are fundamental components of cells which mediate many essential biological processes. Proteomics is a rapidly growing field for the study of proteome, the protein complement expressed by the genome of an organism or cell type. The large-scale analysis of proteins leads to a more comprehensive view of molecular and cellular pathways that improves the overall understanding of the complex processes supporting the living systems. The analysis of proteome is significantly challenging due to high dynamic range and difficulties in assessment of low abundance proteins and the absence of efficient purification and identification techniques. A variety of methods have been utilized for protein studies including gel-based techniques, protein microarrays, mass spectrometry-based approaches such as MALDI and SELDI, high and ultra-performance liquid chromatography and fourier transform ion cyclotron resonance mass spectrometry. NMR spectroscopy and X-Ray crystallography methods are also used for structural study of proteins. This review aims to give a brief overview of some of the above techniques and their most recent advances. We also introduce Proteominer, a recent protein enrichment technology for the exploration of the entire proteome content

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.

The application of cell cultures, body fluids and tissues in oncoproteomics

Mass spectrometry (MS)-based proteomics is a rapidly developing technology for the large scale analysis of proteins, their interactions and subcellular localization. In recent years proteomics has attracted much attention in medicine. Since a single biomarker might not have sufficient sensitivity and specificity in clinical practice, the identification of biomarker panels that comprise several proteins would improve the detection and clinical management of cancer patients. Additionally, the characteristics of protein profiles of most severe human malignancies certainly contribute to the understanding of the biology of cancer and fill the gap in our knowledge of carcinogenesis. This knowledge also is likely to result in the discovery of novel potential cancer markers and targets for molecular therapeutics. It is believed that the novel biomarkers will help in the development of personalized therapy tailored to the individual patient and will thereby reduce the mortality rate from cancer. In this review, the use of different types of human clinical samples (cell cultures, tissues and body fluids) in oncoproteomics is explained and the latest advances in mass spectrometry-based proteomics biomarker discovery are discussed.

IDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition.

Playing crucial roles in various cellular processes, such as recognition of specific nucleotide sequences, regulation of transcription, and regulation of gene expression, DNA-binding proteins are essential ingredients for both eukaryotic and prokaryotic proteomes. With the avalanche of protein sequences generated in the postgenomic age, it is a critical challenge to develop automated methods for accurate and rapidly identifying DNA-binding proteins based on their sequence information alone. Here, a novel predictor, called “iDNA-Prot|dis”, was established by incorporating the amino acid distance-pair coupling information and the amino acid reduced alphabet profile into the general pseudo amino acid composition (PseAAC) vector. The former can capture the characteristics of DNA-binding proteins so as to enhance its prediction quality, while the latter can reduce the dimension of PseAAC vector so as to speed up its prediction process. It was observed by the rigorous jackknife and independent dataset tests that the new predictor outperformed the existing predictors for the same purpose. As a user-friendly web-server, iDNA-Prot|dis is accessible to the public at http://bioinformatics.hitsz.edu.cn/iDNA-Prot_dis/. Moreover, for the convenience of the vast majority of experimental scientists, a step-by-step protocol guide is provided on how to use the web-server to get their desired results without the need to follow the complicated mathematic equations that are presented in this paper just for the integrity of its developing process. It is anticipated that the iDNA-Prot|dis predictor may become a useful high throughput tool for large-scale analysis of DNA-binding proteins, or at the very least, play a complementary role to the existing predictors in this regard.