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PubMed2004

Proteins associated with diseases show enhanced sequence correlation between charged residues.

MOTIVATION: Function of proteins or a network of interacting proteins often involves communication between residues that are well separated in sequence. The classic example is the participation of distant residues in allosteric regulation. Bioinformatic and structural analysis methods have been introduced to infer residues that are correlated. Recently, increasing attention has been paid to obtain the sequence properties that determine the tendency of disease-related proteins (Abeta peptides, prion proteins, transthyretin, etc.) to aggregate and form fibrils. Motivated in part by the need to identify sequence characteristics that indicate a tendency to aggregate, we introduce a general method that probes covariations in charged residues along the sequence in a given protein family. The method, which involves computing the sequence correlation entropy (SCE) using the quenched probability P(sk)(i,j) of finding a residue pair at a given sequence separation, sk, allows us to classify protein families in terms of their SCE. Our general approach may be a useful way in obtaining evolutionary covariations of amino acid residues on a genome wide level. RESULTS: We use a combination of SCE and clustering based on the principle component analysis to classify the protein families. From an analysis of 839 families, covering approximately 500,000 sequences, we find that proteins with relatively low values of SCE are predominantly associated with various diseases. In several families, residues that give rise to peaks in P(sk)(i,j) are clustered in the three-dimensional structure. For the class of proteins with low SCE values, there are significant numbers of mixed charged-hydrophobic (CH) and charged-polar (CP) runs. Our findings suggest that the low values of SCE and the presence of (CH) and/or (CP) may be indicative of disease association or tendency to aggregate. Our results led to the hypothesis that functions of proteins with similar SCE values may be linked. The hypothesis is validated with a few anecdotal examples. The present results also lead to the prediction that the overall charge correlations in proteins affect the kinetics of amyloid formation--a feature that is common to all proteins implicated in neurodegenerative diseases.

Algorithms↗
PubMed2006

Convergence of the proteomic pattern in cancer.

MOTIVATION: On the histological level the differentiation of normal epithelial tissues is well known. The phenomenon of dedifferentiation, which occurs as cells develop towards malignancy is also well described. To identify an epithelial tumor-specific proteomic profile as well as to measure the proximities between we used data from tumor tissue and adjacent normal tissue microdissected from head and neck and colon cancer samples which were analyzed using ProteinChip technology and performed a bioinformatic meta-analysis on the resulting four complex datasets. RESULTS: All four groups could be identified based on their proteomic signatures and the tumor tissues were found to be more similar to one another than to the normal epithelial tissue from which they progressed. This study shows at the proteomic level that changes in the histological features of tumors as compared to the tissues from which they arise are reflected in the convergence of proteomic pattern during the development to cancer.

Cell Differentiation↗
PubMed2006

Discovery of cyclotide-like protein sequences in graminaceous crop plants: ancestral precursors of circular proteins?

Cyclotides are peptides from plants of the Rubiaceae and Violaceae families that have the unusual characteristic of a macrocylic backbone. They are further characterized by their incorporation of a cystine knot in which two disulfides, along with the intervening backbone residues, form a ring through which a third disulfide is threaded. The cyclotides have been found in every Violaceae species screened to date but are apparently present in only a few Rubiaceae species. The selective distribution reported so far raises questions about the evolution of the cyclotides within the plant kingdom. In this study, we use a combined bioinformatics and expression analysis approach to elucidate the evolution and distribution of the cyclotides in the plant kingdom and report the discovery of related sequences widespread in the Poaceae family, including crop plants such as rice (Oryza sativa), maize (Zea mays), and wheat (Triticum aestivum), which carry considerable economic and social importance. The presence of cyclotide-like sequences within these plants suggests that the cyclotides may be derived from an ancestral gene of great antiquity. Quantitative RT-PCR was used to show that two of the discovered cyclotide-like genes from rice and barley (Hordeum vulgare) have tissue-specific expression patterns.

Amino Acid Sequence↗
PubMed2004

The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer.

Increasing interest in new pattern recognition methods has been motivated by bioinformatics research. The analysis of gene expression data originated from microarrays constitutes an important application area for classification algorithms and illustrates the need for identifying important predictors. We show that the Goodman-Kruskal coefficient can be used for constructing minimal classifiers for tabular data, and we give an algorithm that can construct such classifiers.

Algorithms↗
PubMedDate not supplied

An insight-based longitudinal study of visual analytics.

Visualization tools are typically evaluated in controlled studies that observe the short-term usage of these tools by participants on preselected data sets and benchmark tasks. Though such studies provide useful suggestions, they miss the long-term usage of the tools. A longitudinal study of a bioinformatics data set analysis is reported here. The main focus of this work is to capture the entire analysis process that an analyst goes through from a raw data set to the insights sought from the data. The study provides interesting observations about the use of visual representations and interaction mechanisms provided by the tools, and also about the process of insight generation in general. This deepens our understanding of visual analytics, guides visualization developers in creating more effective visualization tools in terms of user requirements, and guides evaluators in designing future studies that are more representative of insights sought by users from their data sets.

Algorithms↗
PubMed2006

Adenovirus infection triggers a rapid, MyD88-regulated transcriptome response critical to acute-phase and adaptive immune responses in vivo.

Nearly 50 years ago, the discovery of interferon prompted the notion that host cells innately respond to viral invasion. Since that time, technological advances have allowed this response to be extensively characterized and dissected in vitro. However, these advances have only recently been applied to highly complex, in vivo biological systems. To this end, we exploited high-titer adenovirus (Ad) vectors to globally investigate the innate immune response to nonenveloped viral infection in vivo. Our results indicated a potent cellular transcriptome response shortly after infection, with global assessments revealing significant dysregulation in approximately 15% of the measured transcripts derived from Ad vector-transduced tissue. Bioinformatics-based transcriptome analysis revealed a complex innate response to Ad infection, with induction of proinflammatory responses (and suppression of metabolism and mitochondrial genes) akin to those observed when mice are challenged with lipopolysaccharide. Despite this commonality, there were many unique aspects of the Ad-dependent transcriptome response, including the upregulation of several RNA regulatory mechanisms and apoptosis-related pathways, accompanied by the suppression of lysosomal and endocytic genes. Our results also implicated the Toll-like receptors (TLRs) in these responses, prompting specific investigations into this pathway. By using MyD88KO mice, our results confirmed that Ad-induced dysregulation of five functionally related gene clusters are significantly dependent on this TLR adaptor gene. MyD88 deficiency also resulted in significantly diminished, although not abolished, adaptive and acute-phase immune responses to Ad, confirming the transcriptome data, as well as specifically identifying MyD88 as a significant Ad immunity amplifier and regulator in vivo.

Adenoviridae↗
PubMed2006

Global suppression of the host antiviral response by Ebola- and Marburgviruses: increased antagonism of the type I interferon response is associated with enhanced virulence.

We studied the effect of filovirus infection on host cell gene expression by characterizing the regulation of gene expression responses in human liver cells infected with Zaire Ebolavirus (ZEBOV), Reston Ebolavirus (REBOV), and Marburgvirus (MARV), using transcriptional profiling and bioinformatics. Expression microarray analysis demonstrated that filovirus infection resulted in the up-regulation of immune-related genes and the down-regulation of many coagulation and acute-phase proteins. These studies further revealed that a common feature of filovirus virulence is suppression of key cellular antiviral responses, including TLR-, interferon (IFN) regulatory factor 3-, and PKR-related pathways. We further showed that ZEBOV and MARV were more potent antagonists of the IFN response and inhibited the expression of most of the IFN-stimulated genes (ISGs) observed in mock-infected IFN-alpha-2b treated cells, compared to REBOV infection, which activated more than 20% of these ISGs. Finally, we examined IFN-related gene expression in filovirus-infected cells treated with IFN-alpha-2b. These experiments revealed that a majority of genes induced in mock-infected cells treated with type I IFN were antagonized in treated ZEBOV- and MARV-infected cells, while in contrast, REBOV infection resulted in a significant increase in ISG expression. Analysis of STAT1 and -2 phosphorylation following IFN treatment showed a significant reduction of STAT phosphorylation for MARV but not for ZEBOV and REBOV, indicating that different mechanisms might be involved in antagonizing IFN signaling pathways by the different filovirus species. Taken together, these studies showed a correlation between antagonism of type I IFN responses and filovirus virulence.

Animals↗
PubMed2002

A molecular compendium of genes expressed in multiple myeloma.

We have created a molecular resource of genes expressed in primary malignant plasma cells using a combination of cDNA library construction, 5' end single-pass sequencing, bioinformatics, and microarray analysis. In total, we identified 9732 nonredundant expressed genes. This dataset is available as the Myeloma Gene Index (www.uhnres.utoronto.ca/akstewart_lab).Predictably, the sequenced profile of myeloma cDNAs mirrored the known function of immunoglobulin-producing, high-respiratory rate, low-cycling, terminally differentiated plasma cells. Nevertheless, approximately 10% of myeloma-expressed sequences matched only entries in the database of Expressed Sequence Tags (dbEST) or the high-throughput genomic sequence (htgs) database. Numerous novel genes of potential biologic significance were identified. We therefore spotted 4300 sequenced cDNAs on glass slides creating a myeloma-enriched microarray. Several of the most highly expressed genes identified by sequencing, such as a novel putative disulfide isomerase (MGC3178), tumor rejection antigen TRA1, heat shock 70-kDa protein 5, and annexin A2, were also differentially expressed between myeloma and B lymphoma cell lines using this myeloma-enriched microarray. Furthermore, a defined subset of 34 up-regulated and 18 down-regulated genes on the array were able to differentiate myeloma from nonmyeloma cell lines. These not only include genes involved in B-cell biology such as syndecan, BCMA, PIM2, MUM1/IRF4, and XBP1, but also novel uncharacterized genes matching sequences only in the public databases. In summary, our expressed gene catalog and myeloma-enriched microarray contains numerous genes of unknown function and may complement other commercially available arrays in defining the molecular portrait of this hematopoietic malignancy. GenBank Accession numbers include BF169967-BF176369, BF185966-BF185969, and BF177280-BF177455.

Amino Acid Sequence↗
PubMed2003

T-cell epitopes within the complementarity-determining and framework regions of the tumor-derived immunoglobulin heavy chain in multiple myeloma.

The idiotypic structure of the monoclonal immunoglobulin (Ig) in multiple myeloma (MM) might be regarded as a tumor-specific antigen. The present study was designed to identify T-cell epitopes of the variable region of the Ig heavy chain (VH) in MM (n = 5) using bioinformatics and analyze the presence of naturally occurring T cells against idiotype-derived peptides. A large number of human-leukocyte-antigen (HLA)-binding (class I and II) peptides were identified. The frequency of predicted epitopes depended on the database used: 245 in bioinformatics and molecular analysis section (BIMAS) and 601 in SYFPEITHI. Most of the peptides displayed a binding half-life or score in the low or intermediate affinity range. The majority of the predicted peptides were complementarity-determining region (CDR)-rather than framework region (FR)-derived (52%-60% vs 40%-48%, respectively). Most of the predicted peptides were confined to the CDR2-FR3-CDR3 "geographic" region of the Ig-VH region (70%), and significantly fewer peptides were found within the flanking (FR1-CDR1-FR2 and FR4) regions (P <.01). There were 8- to 10-amino acid (aa) long peptides corresponding to the CDRs and fitting to the actual HLA-A/B haplotypes that spontaneously recognized, albeit with a low magnitude, type I T cells (interferon gamma), indicating an ongoing major histocompatibility complex (MHC) class I-restricted T-cell response. Most of those peptides had a low binding half-life (BIMAS) and a low/intermediate score (SYFPEITHI). Furthermore, 15- to 20-aa long CDR1-3-derived peptides also spontaneously recognized type I T cells, indicating the presence of MHC class II-restricted T cells as well. This study demonstrates that a large number of HLA-binding idiotypic peptides can be identified in patients with MM. Such peptides may spontaneously induce a type I MHC class I- as well as class II-restricted memory T-cell response.

Aged↗
PubMed2005

Evaluation of BioCreAtIvE assessment of task 2.

BACKGROUND: Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products. Those annotation databases are crucial for the interpretation of large scale analysis approaches using bioinformatics or experimental techniques. Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent. In order to make text mining tools useable in real world scenarios, for instance to assist database curators during annotation of protein function, comparisons and evaluations of different approaches on full text articles are needed. RESULTS: The Critical Assessment for Information Extraction in Biology (BioCreAtIvE) contest consists of a community wide competition aiming to evaluate different strategies for text mining tools, as applied to biomedical literature. We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles. The predictions of task 2 are based on triplets of protein--GO term--article passage. The annotation-relevant text passages were returned by the participants and evaluated by expert curators of the GO annotation (GOA) team at the European Institute of Bioinformatics (EBI). Each participant could submit up to three results for each sub-task comprising task 2. In total more than 15,000 individual results were provided by the participants. The curators evaluated in addition to the annotation itself, whether the protein and the GO term were correctly predicted and traceable through the submitted text fragment. CONCLUSION: Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Although the obtained results are promising, they are still far from reaching the required performance demanded by real world applications. Among the principal difficulties encountered to address the proposed task, were the complex nature of the GO terms and protein names (the large range of variants which are used to express proteins and especially GO terms in free text), and the lack of a standard training set. A range of very different strategies were used to tackle this task. The dataset generated in line with the BioCreative challenge is publicly available and will allow new possibilities for training information extraction methods in the domain of molecular biology.

Computational Biology↗
PubMed2006

A dehydration-inducible gene in the truffle Tuber borchii identifies a novel group of dehydrins.

BACKGROUND: The expressed sequence tag M6G10 was originally isolated from a screening for differentially expressed transcripts during the reproductive stage of the white truffle Tuber borchii. mRNA levels for M6G10 increased dramatically during fruiting body maturation compared to the vegetative mycelial stage. RESULTS: Bioinformatics tools, phylogenetic analysis and expression studies were used to support the hypothesis that this sequence, named TbDHN1, is the first dehydrin (DHN)-like coding gene isolated in fungi. Homologs of this gene, all defined as "coding for hypothetical proteins" in public databases, were exclusively found in ascomycetous fungi and in plants. Although complete (or almost complete) fungal genomes and EST collections of some Basidiomycota and Glomeromycota are already available, DHN-like proteins appear to be represented only in Ascomycota. A new and previously uncharacterized conserved signature pattern was identified and proposed to Uniprot database as the main distinguishing feature of this new group of DHNs. Expression studies provide experimental evidence of a transcript induction of TbDHN1 during cellular dehydration. CONCLUSION: Expression pattern and sequence similarities to known plant DHNs indicate that TbDHN1 is the first characterized DHN-like protein in fungi. The high similarity of TbDHN1 with homolog coding sequences implies the existence of a novel fungal/plant group of LEA Class II proteins characterized by a previously undescribed signature pattern.

Amino Acid Sequence↗
PubMed2024

Clinical characterizations and molecular genetic study of two co-segregating variants in PDZD7 and PDE6C genes leading simultaneously to non-syndromic hearing loss and achromatopsia.

BACKGROUND: Autosomal recessive non-syndromic hearing loss (NSHL) and cone dystrophies (CODs) are highly genetically and phenotypically heterogeneous disorders. In this study, we applied the whole exome sequencing (WES) to find the cause of HL and COD in an Iranian consanguineous family with three affected individuals. METHODS: Three members from an Iranian consanguineous family who were suffering from NSHL and visual impairment were ascertained in this study. Comprehensive clinical evaluations and genetic analysis followed by bioinformatic and co-segregation studies were performed to diagnose the cause of these phenotypes. Data were collected from 2020 to 2022. RESULTS: All cases showed congenital bilateral NSHL, decreased visual acuity, poor color discrimination, photophobia and macular atrophy. Moreover, cornea, iris and anterior vitreous were within normal limit in both eyes, decreased foveal sensitivity, central scotoma and generalized depression of visual field were seen in three cases. WES results showed two variants, a novel null variant (p.Trp548Ter) in the PDE6C gene causing COD type 4 (Achromatopsia) and a previously reported variant (p.Ile84Thr) in the PDZD7 gene causing NSHL. Both variants were found in the cis configuration on chromosome 10 with a genetic distance of about 8.3&#xa0;cM, leading to their co-inheritance. However, two diseases could appear independently in subsequent generations due to crossover during meiosis. CONCLUSIONS: Here, we could successfully determine the etiology of a seemingly complex phenotype in two adjacent genes. We identified a novel variant in the PDE6C gene, related to achromatopsia. Interestingly, this variant could cooperatively cause visual disorders: cone dystrophy and cone-rod dystrophy.

Adult↗
PubMed2006

Application of bioinformatics for DNA microarray data to bioscience, bioengineering and medical fields.

In the 1990s, DNA microarray or DNA chip as a novel biological experimental technology was developed, which enables the comprehensive measurement of the expression levels of hundreds of genes, simultaneously. Using this technique, a comprehensive understanding of the cell can be achieved. However, because even simple life forms, such as microorganisms, have more than a thousand kinds of genes, the data from a DNA chip cannot be analyzed without statistical and informational technology. Bioinformatics is the interdisciplinary research field integrating molecular biology with informatics, and it is expected to have a huge impact on the bioscientific, bioengineering and medical fields. There are many techniques in bioinformatics for the analysis of DNA microarray data; however, these are mainly divided into fold-change analysis, clustering, classification, genetic network analysis, and simulation. In this review, these techniques are briefly explained by using some examples.

Animals↗
PubMed2024

SPOP expression is associated with tumor-infiltrating lymphocytes in pancreatic cancer.

BACKGROUND: Speckle Type POZ Protein (SPOP), despite its tumor type-dependent role in tumorigenesis, primarily as a tumor suppressor gene is associated with a variety of different cancers. However, its function in pancreatic cancer remains uncertain. METHODS: SPOP expression and the association between its expression and patient prognosis and immune function were evaluated using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), The Tumor Immune Estimation Resource 2.0 (TIMER2.0) database, cBioportal, and various bioinformatic databases. Enrichment analysis of SPOP and the association between SPOP expression with clinical stage and grade were analyzed using the R software package. Then immunohistochemistry (IHC) was used to estimate the correlation between SPOP and tumor-infiltrating lymphocytes (TILs) in patients with pancreatic cancer. RESULTS: As part of our study, we assessed that SPOP was anomalously expressed in kinds of cancers, associated with clinical stage and outcomes. Meanwhile, SPOP also played a crucial role in the tumor microenvironment (TME). The expression level of SPOP was significantly correlated to tumor-infiltrating immune cells (TICs) in pancreatic cancer. CONCLUSIONS: Our study uncovered the potential corrections in SPOP with TICs, suggesting that SPOP may act as a biomarker for immunotherapy in pancreatic cancer.

Humans↗
PubMed2004

Synthetic peptide studies on the severe acute respiratory syndrome (SARS) coronavirus spike glycoprotein: perspective for SARS vaccine development.

BACKGROUND: The S (spike) protein of the etiologic coronavirus (CoV) agent of severe acute respiratory syndrome (SARS) plays a central role in mediating viral infection via receptor binding and membrane fusion between the virion and the host cell. We focused on using synthetic peptides for developing antibodies against SARS-CoV, which aimed to block viral invasion by eliciting an immune response specific to the native SARS-CoV S protein. METHODS: Six peptide sequences corresponding to the surface regions of SARS-CoV S protein were designed and investigated by use of combined bioinformatics and structural analysis. These synthetic peptides were used to immunize both rabbits and monkeys. Antisera collected 1 week after the second immunization were analyzed by ELISA and tested for antibody specificity against SARS-CoV by immunofluorescent confocal microscopy. RESULTS: Four of our six synthetic peptides (S2, S3, S5, and S6) elicited SARS-CoV-specific antibodies, of which S5 (residues 788-820) and S6 (residues 1002-1030) exhibited immunogenic responses similar to those found in a parallel investigation using truncated recombinant protein analogs of the SARS-CoV S protein. This suggested that our S5 and S6 peptides may represent two minimum biologically active sequences of the immunogenic regions of the SARS-CoV S protein. CONCLUSIONS: Synthetic peptides can elicit specific antibodies to SARS-CoV. The study provides insights for the future development of SARS vaccine via the synthetic-peptide-based approach.

Amino Acid Sequence↗
PubMed2006

Proteomics in pulmonary medicine.

Proteomics is the study of the entire protein complement of the genome (the proteome) in a biological system. Proteomic studies require a multidisciplinary approach and have only been practical with the convergence of technical and methodologic improvements including the following: advances in mass spectrometry and genomic sequencing that now permit the identification and relative quantization of small amounts (femtomole) of nearly any single protein; new methods in gel electrophoresis that allow the detection of subtle changes in protein expression, including posttranslational modifications; automation and miniaturization that permit high-throughput analysis of clinical samples; and new bioinformatics and computational methods that facilitate analysis and interpretation of the abundant data that are generated by proteomics experiments. This convergence makes proteomics studies practical for pulmonary researchers using BAL fluid, lung tissue, blood, and exhaled breath condensates, and will facilitate the research of complex, multifactorial lung diseases such as acute lung injury and COPD. This review describes how proteomics experiments are conducted and interpreted, their limitations, and how proteomics has been used in clinical pulmonary medicine.

Humans↗
PubMed2026

Casein Kinase 1 Alpha 1 Is Over-expressed in Pancreatic Adenocarcinoma Tissues and Correlates With Shorter Patient Survival.

BACKGROUND/AIM: A quarter of a century has passed since the start of the 21st century, and cancer, once considered an incurable disease, has become manageable thanks to the development of various treatments. However, pancreatic adenocarcinoma (PAAD) remains one of the deadliest cancers in the world, with over 95% of patients dying within five years. This is because the anatomical location of the pancreas makes it very difficult to detect with imaging, and symptoms often do not appear until the cancer invades the nerve plexus in its terminal stages, meaning that by the time it is diagnosed, it is often too late. Therefore, the development of prognostic markers is an urgent task. Casein kinase 1 alpha 1 (CSNK1A1) is a serine/threonine protein kinase deeply involved in Wnt signaling and the tumor suppressor mechanisms of p53. While the association between increased or decreased CSNK1A1 expression and prognosis has been reported in many types of cancer tissue, its association in PAAD is not yet fully understood. This study investigated the potential of CSNK1A1 as a prognostic marker for PAAD. MATERIALS AND METHODS: We used Gene Expression Profiling Interactive Analysis (GEPIA) and the University of Alabama Birmingham Cancer Data Analysis Portal (UALCAN) bioinformatics platforms to analyze CSNK1A1 mRNA expression, protein levels, and survival rates of patients with PAAD obtained from The Cancer Genome Atlas (TCGA) database. RESULTS: CSNK1A1 mRNA and protein levels were significantly higher in PAAD tissue compared to normal pancreatic tissue, and this increase was associated with a poor prognosis in patients with PAAD. CONCLUSION: In PAAD tissue, increased expression of CSNK1A1 mRNA and protein was observed compared to normal pancreatic tissue, and this increased expression correlated with poor patient prognosis. Therefore, CSNK1A1 is considered a promising prognostic biomarker in PAAD.

CSNK1A1↗
PubMed2004

Random screening of proteins for HLA-A*0201-binding nine-amino acid peptides is not sufficient for identifying CD8 T cell epitopes recognized in the context of HLA-A*0201.

HLA-A2 is the most frequent HLA molecule in Caucasians with HLA-A*0201 representing the most frequent allele; it was also the first human HLA allele for which peptide binding prediction was developed. The Bioinformatics and Molecular Analysis Section of the National Institutes of Health (BIMAS) and the University of Tübingen (Syfpeithi) provide the most popular prediction algorithms of peptide/MHC interaction on the World Wide Web. To test these predictions, HLA-A*0201-binding nine-amino acid peptides were searched by both algorithms in 19 structural CMV proteins. According to Syfpeithi, the top 2% of predicted peptides should contain the naturally presented epitopes in 80% of predictions (www.syfpeithi.de). Because of the high number of predicted peptides, the analysis was limited to 10 randomly chosen proteins. The top 2% of peptides predicted by both algorithms were synthesized corresponding to 261 peptides in total. PBMC from 10 HLA-A*0201-positive and CMV-seropositive healthy blood donors were tested by ex vivo stimulation with all 261 peptides using crossover peptide pools. IFN-gamma production in T cells measured by CFC was used as readout. However, only one peptide was found to be stimulating in one single donor. As a result of this work, we report a potential new T cell target protein, one previously unknown CD8-T cell-stimulating peptide, and an extensive list of CMV-derived potentially strong HLA-A*0201-binding peptides that are not recognized by T cells of HLA-A*0201-positive CMV-seropositive donors. We conclude that MHC/peptide binding predictions are helpful for locating epitopes in known target proteins but not necessarily for screening epitopes in proteins not known to be T cell targets.

Algorithms↗