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Abstract
INTRODUCTION Proteomics, i.e. the study of the set of proteins produced in a cell, tissue, organism, or biological entity, has made possible analyses and contextual comparisons of proteomes/proteins and biological functions among the most disparate entities, from viruses to the human being. In this way, proteomic scrutiny of tumor-associated proteins, autoantigens, and pathogen antigens offers the tools for fighting cancer, autoimmunity, and infections. AREAS COVERED Comparative proteomics and immunoproteomics, the new scientific disciplines generated by proteomics, are the main themes of the present review that describes how comparative analyses of pathogen and human proteomes led to re-modulate the molecular mimicry concept of the pre-proteomic era. I.e. before proteomics, molecular mimicry - the sharing of peptide sequences between two biological entities - was considered as intrinsically endowed with immunologic properties and was related to cross-reactivity. Proteomics allowed to redefine such an assumption using physicochemical parameters according to which frequency and hydrophobicity preferentially confer an immunologic potential to shared peptide sequences. EXPERT OPINION Proteomics is outlining peptide platforms to be used for the diagnostics and management of human diseases. A Molecular Medicine targeted to obtain healing without paying the price for adverse events is on the horizon. The next step is to take up the challenge and operate the paradigm shift that the current proteomic era requires.
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Affiliation(s)
- Darja Kanduc
- Department of Biosciences, Biotechnologies, and Biopharmaceutics, University of Bari, Bari, Italy
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Poznański J, Topiński J, Muszewska A, Dębski KJ, Hoffman-Sommer M, Pawłowski K, Grynberg M. Global pentapeptide statistics are far away from expected distributions. Sci Rep 2018; 8:15178. [PMID: 30310110 DOI: 10.1038/s41598-018-33433-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 09/26/2018] [Indexed: 11/08/2022] Open
Abstract
The relationships between polypeptide composition, sequence, structure and function have been puzzling biologists ever since first protein sequences were determined. Here, we study the statistics of occurrence of all possible pentapeptide sequences in known proteins. To compensate for the non-uniform distribution of individual amino acid residues in protein sequences, we investigate separately all possible permutations of every given amino acid composition. For the majority of permutation groups we find that pentapeptide occurrences deviate strongly from the expected binomial distributions, and that the observed distributions are also characterized by high numbers of outlier sequences. An analysis of identified outliers shows they often contain known motifs and rare amino acids, suggesting that they represent important functional elements. We further compare the pentapeptide composition of regions known to correspond to protein domains with that of non-domain regions. We find that a substantial number of pentapeptides is clearly strongly favored in protein domains. Finally, we show that over-represented pentapeptides are significantly related to known functional motifs and to predicted ancient structural peptides.
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Suzek BE, Wang Y, Huang H, McGarvey PB, Wu CH. UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics 2014; 31:926-32. [PMID: 25398609 PMCID: PMC4375400 DOI: 10.1093/bioinformatics/btu739] [Citation(s) in RCA: 874] [Impact Index Per Article: 87.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
MOTIVATION UniRef databases provide full-scale clustering of UniProtKB sequences and are utilized for a broad range of applications, particularly similarity-based functional annotation. Non-redundancy and intra-cluster homogeneity in UniRef were recently improved by adding a sequence length overlap threshold. Our hypothesis is that these improvements would enhance the speed and sensitivity of similarity searches and improve the consistency of annotation within clusters. RESULTS Intra-cluster molecular function consistency was examined by analysis of Gene Ontology terms. Results show that UniRef clusters bring together proteins of identical molecular function in more than 97% of the clusters, implying that clusters are useful for annotation and can also be used to detect annotation inconsistencies. To examine coverage in similarity results, BLASTP searches against UniRef50 followed by expansion of the hit lists with cluster members demonstrated advantages compared with searches against UniProtKB sequences; the searches are concise (∼7 times shorter hit list before expansion), faster (∼6 times) and more sensitive in detection of remote similarities (>96% recall at e-value <0.0001). Our results support the use of UniRef clusters as a comprehensive and scalable alternative to native sequence databases for similarity searches and reinforces its reliability for use in functional annotation.
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Affiliation(s)
- Baris E Suzek
- Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland
| | - Yuqi Wang
- Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland
| | - Hongzhan Huang
- Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland
| | - Peter B McGarvey
- Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland
| | - Cathy H Wu
- Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland Protein Information Resource, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla 48000, Turkey, Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, DE 19711, USA, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK and Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland
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Patel A, Dong JC, Trost B, Richardson JS, Tohme S, Babiuk S, Kusalik A, Kung SK, Kobinger GP. Pentamers not found in the universal proteome can enhance antigen specific immune responses and adjuvant vaccines. PLoS One 2012; 7:e43802. [PMID: 22937099 DOI: 10.1371/journal.pone.0043802] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2012] [Accepted: 07/26/2012] [Indexed: 12/22/2022] Open
Abstract
Certain short peptides do not occur in humans and are rare or non-existent in the universal proteome. Antigens that contain rare amino acid sequences are in general highly immunogenic and may activate different arms of the immune system. We first generated a list of rare, semi-common, and common 5-mer peptides using bioinformatics tools to analyze the UniProtKB database. Experimental observations indicated that rare and semi-common 5-mers generated stronger cellular responses in comparison with common-occurring sequences. We hypothesized that the biological process responsible for this enhanced immunogenicity could be used to positively modulate immune responses with potential application for vaccine development. Initially, twelve rare 5-mers, 9-mers, and 13-mers were incorporated in frame at the end of an H5N1 hemagglutinin (HA) antigen and expressed from a DNA vaccine. The presence of some 5-mer peptides induced improved immune responses. Adding one 5-mer peptide exogenously also offered improved clinical outcome and/or survival against a lethal H5N1 or H1N1 influenza virus challenge in BALB/c mice and ferrets, respectively. Interestingly, enhanced anti-HBsAg antibody production by up to 25-fold in combination with a commercial Hepatitis B vaccine (Engerix-B, GSK) was also observed in BALB/c mice. Mechanistically, NK cell activation and dependency was observed with enhancing peptides ex vivo and in NK-depleted mice. Overall, the data suggest that rare or non-existent oligopeptides can be developed as immunomodulators and supports the further evaluation of some 5-mer peptides as potential vaccine adjuvants.
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