Consensus classification of human leukocyte antigen class II proteins
Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA–pept...
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description | Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA–peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II–peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II–peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at
http://sysbio.icm.edu.pl/HLA
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doi_str_mv | 10.1007/s00251-012-0665-6 |
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http://sysbio.icm.edu.pl/HLA
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http://sysbio.icm.edu.pl/HLA
.</description><subject>Algorithms</subject><subject>Allergology</subject><subject>Amino acids</subject><subject>Antigen presentation</subject><subject>Binding Sites</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>CD4 antigen</subject><subject>Cell Biology</subject><subject>Classification</subject><subject>Cluster Analysis</subject><subject>Computational Biology - methods</subject><subject>Datasets</subject><subject>Gene Function</subject><subject>Gene loci</subject><subject>Gene polymorphism</subject><subject>Histocompatibility antigen HLA</subject><subject>Histocompatibility Antigens Class II - classification</subject><subject>Histocompatibility Antigens Class II - genetics</subject><subject>Histocompatibility Antigens Class II - metabolism</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Immunology</subject><subject>Leukocytes</subject><subject>Lymphocytes</subject><subject>Lymphocytes T</subject><subject>Original Paper</subject><subject>Peptides</subject><subject>Peptides - metabolism</subject><subject>Phylogeny</subject><subject>Polymorphism</subject><subject>Protein Binding - immunology</subject><subject>Proteins</subject><subject>Reproducibility of Results</subject><subject>Structure-function relationships</subject><subject>Support vector machines</subject><subject>T cell receptors</subject><subject>Vaccines</subject><issn>0093-7711</issn><issn>1432-1211</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkcFu1DAQhi0EokvhAbigSFy4BGbGsZ1ckNCqlJUqcYGz5TjO1iVrL3aC1LfHq7RVQUKcfJjv_-zxz9hrhPcIoD5kABJYA1INUopaPmEbbDjVSIhP2Qag47VSiGfsRc43ACg6ks_ZGXGirlG0YRfbGLILecmVnUzOfvTWzD6GKo7V9XIwoZrc8iPa29lVJsx-78JKVrtddUxxdj7kl-zZaKbsXt2d5-z754tv2y_11dfL3fbTVW0F8Lkmo5yRyg1KSKtoGEfbSVI9yF6iaVXbcOyNbFrTDtC0gwDE0ai-aaAtiYGfs4-r97j0BzdYF-ZkJn1M_mDSrY7G6z8nwV_rffyluWi4hLYI3t0JUvy5uDzrg8_WTZMJLi5ZIyfeggTC_6OkuADVAS_o27_Qm7ikUH6iCFEo6jqQhcKVsinmnNz48G4EfepTr33q0qc-9alPmTePF35I3BdYAFqBXEZh79Kjq_9p_Q0H9qp0</recordid><startdate>20130201</startdate><enddate>20130201</enddate><creator>Saha, Indrajit</creator><creator>Mazzocco, Giovanni</creator><creator>Plewczynski, Dariusz</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7T5</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20130201</creationdate><title>Consensus classification of human leukocyte antigen class II proteins</title><author>Saha, Indrajit ; Mazzocco, Giovanni ; Plewczynski, Dariusz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c503t-2a7ea67ed756c72dffc9627b06b61a878431ba648a8d048d5011fa7b440856cd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Algorithms</topic><topic>Allergology</topic><topic>Amino acids</topic><topic>Antigen presentation</topic><topic>Binding Sites</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>CD4 antigen</topic><topic>Cell Biology</topic><topic>Classification</topic><topic>Cluster Analysis</topic><topic>Computational Biology - methods</topic><topic>Datasets</topic><topic>Gene Function</topic><topic>Gene loci</topic><topic>Gene polymorphism</topic><topic>Histocompatibility antigen HLA</topic><topic>Histocompatibility Antigens Class II - classification</topic><topic>Histocompatibility Antigens Class II - genetics</topic><topic>Histocompatibility Antigens Class II - metabolism</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Immunology</topic><topic>Leukocytes</topic><topic>Lymphocytes</topic><topic>Lymphocytes T</topic><topic>Original Paper</topic><topic>Peptides</topic><topic>Peptides - metabolism</topic><topic>Phylogeny</topic><topic>Polymorphism</topic><topic>Protein Binding - immunology</topic><topic>Proteins</topic><topic>Reproducibility of Results</topic><topic>Structure-function relationships</topic><topic>Support vector machines</topic><topic>T cell receptors</topic><topic>Vaccines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saha, Indrajit</creatorcontrib><creatorcontrib>Mazzocco, Giovanni</creatorcontrib><creatorcontrib>Plewczynski, Dariusz</creatorcontrib><collection>Springer Nature OA/Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>Proquest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Immunogenetics (New York)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saha, Indrajit</au><au>Mazzocco, Giovanni</au><au>Plewczynski, Dariusz</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Consensus classification of human leukocyte antigen class II proteins</atitle><jtitle>Immunogenetics (New York)</jtitle><stitle>Immunogenetics</stitle><addtitle>Immunogenetics</addtitle><date>2013-02-01</date><risdate>2013</risdate><volume>65</volume><issue>2</issue><spage>97</spage><epage>105</epage><pages>97-105</pages><issn>0093-7711</issn><eissn>1432-1211</eissn><abstract>Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA–peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II–peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II–peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at
http://sysbio.icm.edu.pl/HLA
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subjects | Algorithms Allergology Amino acids Antigen presentation Binding Sites Biomedical and Life Sciences Biomedicine CD4 antigen Cell Biology Classification Cluster Analysis Computational Biology - methods Datasets Gene Function Gene loci Gene polymorphism Histocompatibility antigen HLA Histocompatibility Antigens Class II - classification Histocompatibility Antigens Class II - genetics Histocompatibility Antigens Class II - metabolism Human Genetics Humans Immunology Leukocytes Lymphocytes Lymphocytes T Original Paper Peptides Peptides - metabolism Phylogeny Polymorphism Protein Binding - immunology Proteins Reproducibility of Results Structure-function relationships Support vector machines T cell receptors Vaccines |
title | Consensus classification of human leukocyte antigen class II proteins |
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