TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR Molecules
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{"title"=>"Tepitopepan: Extending tepitope for peptide binding prediction covering over 700 hla-dr molecules", "type"=>"journal", "authors"=>[{"first_name"=>"Lianming", "last_name"=>"Zhang", "scopus_author_id"=>"55036393900"}, {"first_name"=>"Yiqing", "last_name"=>"Chen", "scopus_author_id"=>"55273492100"}, {"first_name"=>"Hau San", "last_name"=>"Wong", "scopus_author_id"=>"7402864844"}, {"first_name"=>"Shuigeng", "last_name"=>"Zhou", "scopus_author_id"=>"7404166246"}, {"first_name"=>"Hiroshi", "last_name"=>"Mamitsuka", "scopus_author_id"=>"6602748450"}, {"first_name"=>"Shanfeng", "last_name"=>"Zhu", "scopus_author_id"=>"8940145500"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84863182833", "pui"=>"364337932", "doi"=>"10.1371/journal.pone.0030483", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84863182833", "pmid"=>"22383964"}, "id"=>"14eae68d-50a1-3192-965a-f7b7177def06", "abstract"=>"MOTIVATION: Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II) molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules. METHOD: We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE. RESULT: The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in recognizing binding cores. We further analyzed the motifs detected by TEPITOPEpan, examining the corresponding literature of immunology. Its online server and PSSMs therein are available at http://www.biokdd.fudan.edu.cn/Service/TEPITOPEpan/.", "link"=>"http://www.mendeley.com/research/tepitopepan-extending-tepitope-peptide-binding-prediction-covering-700-hladr-molecules", "reader_count"=>86, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Researcher"=>17, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>8, "Other"=>9, "Student > Master"=>9, "Student > Bachelor"=>7, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Researcher"=>17, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>8, "Other"=>9, "Student > Master"=>9, "Student > Bachelor"=>7, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>36, "Chemistry"=>4, "Computer Science"=>13, "Economics, Econometrics and Finance"=>1, "Engineering"=>3, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Medicine and Dentistry"=>7, "Neuroscience"=>2, "Design"=>1, "Physics and Astronomy"=>1, "Immunology and Microbiology"=>8}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>3}, "Chemistry"=>{"Chemistry"=>4}, "Neuroscience"=>{"Neuroscience"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>8}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>36}, "Computer Science"=>{"Computer Science"=>13}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}}, "reader_count_by_country"=>{"Canada"=>1, "Argentina"=>2, "United States"=>2, "Ireland"=>1, "South Africa"=>1, "Australia"=>1, "Germany"=>1, "India"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/676449"], "description"=>"<p>The highest value in each row of columns for is highlighted in bold. 1-KNN means the result of using only specificity vector(s) in the library with highest similarity to derive PSSM.</p>", "links"=>[], "tags"=>["tepitopepan", "alphas"], "article_id"=>346936, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t003", "stats"=>{"downloads"=>1, "page_views"=>91, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_TEPITOPEpan_with_different_alphas_in_terms_of_AUC_/346936", "title"=>"Performance of TEPITOPEpan with different alphas in terms of AUC.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:55:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/676179"], "description"=>"<p>The binding cores of 2 complexes cannot be predicted by TEPITOPE, since it doesn't cover DRB3*01:01 and DRB3*02:01.</p>", "links"=>[], "tags"=>["errors", "predicting", "binding", "cores", "20", "complexes"], "article_id"=>346662, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t008", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_number_of_errors_on_predicting_binding_cores_of_20_complexes_in_EpanCore_Set8_/346662", "title"=>"The number of errors on predicting binding cores of 20 complexes in EpanCore-Set8.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:51:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/676419"], "description"=>"<p>The first column gives nine pockets (P1 to P9). The second column shows corresponding residue positions in contact with each pocket.</p>", "links"=>[], "tags"=>["hla-dr", "amino", "residue", "positions", "pockets", "tepitopepan"], "article_id"=>346897, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t002", "stats"=>{"downloads"=>0, "page_views"=>66, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_HLA_DR_amino_acid_residue_positions_of_each_pockets_in_TEPITOPEpan_profile_/346897", "title"=>"The HLA-DR amino acid residue positions of each pockets in TEPITOPEpan profile.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:54:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/676300"], "description"=>"<p>Highest values for each allele are highlighted in bold.</p>", "links"=>[], "tags"=>["immunology", "Computational biology", "biophysics", "computer science", "physics", "Biochemistry"], "article_id"=>346781, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t006", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_AUC_on_Epan_Set4_/346781", "title"=>"AUC on Epan-Set4.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:53:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/676224"], "description"=>"<p>The highest values for each allele are highlighted in bold. <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030483#s3\" target=\"_blank\">Results</a> of NetMHCIIpan-2.0 are obtained by leave-one-(allele)-out (LOO) experiment over original 24 alleles in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030483#pone.0030483-Nielsen6\" target=\"_blank\">[27]</a>.</p>", "links"=>[], "tags"=>["immunology", "Computational biology", "biophysics", "computer science", "physics", "Biochemistry"], "article_id"=>346702, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_AUC_on_Nielsen_Set2_/346702", "title"=>"AUC on Nielsen-Set2.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:51:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/676373"], "description"=>"<p>The table shows complex structures retrieved from PDB. The columns in the table give PDB ID, HLA-DR restriction and bound peptide (binding core highlighted in bold).</p>", "links"=>[], "tags"=>["x-ray", "structures", "mhc", "ii", "hla-peptide"], "article_id"=>346859, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Available_X_ray_structures_of_MHC_class_II_HLA_peptide_complexe_/346859", "title"=>"Available X-ray structures of MHC class II HLA-peptide complexe.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:54:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/676022"], "description"=>"<p>Comparing of different pan-specific methods by the sequence logos of peptides restricted to HLA-DRB1*04:02, DRB1*11:01, DRB1*12:01, DRB1*13:01.</p>", "links"=>[], "tags"=>["pan-specific", "methods", "logos", "peptides", "restricted"], "article_id"=>346506, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.g001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparing_of_different_pan_specific_methods_by_the_sequence_logos_of_peptides_restricted_to_HLA_DRB1_04_02_DRB1_11_01_DRB1_12_01_DRB1_13_01_/346506", "title"=>"Comparing of different pan-specific methods by the sequence logos of peptides restricted to HLA-DRB1*04:02, DRB1*11:01, DRB1*12:01, DRB1*13:01.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-23 01:48:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/676259"], "description"=>"<p>The highest value for each allele is highlighted in bold. According to Nielsen et al. <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030483#pone.0030483-Nielsen6\" target=\"_blank\">[27]</a>, for DRB1*01:01, 04:01, 07:01 and 15:01, binding threshold is set to 100 nM, and threshold is set to 1000 nM for the rest when calculating the AUC.</p>", "links"=>[], "tags"=>["immunology", "Computational biology", "biophysics", "computer science", "physics", "Biochemistry"], "article_id"=>346744, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_AUC_on_Lin_Set3_/346744", "title"=>"AUC on Lin-Set3.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:52:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/345840", "https://ndownloader.figshare.com/files/345914", "https://ndownloader.figshare.com/files/345983", "https://ndownloader.figshare.com/files/346042", "https://ndownloader.figshare.com/files/346094", "https://ndownloader.figshare.com/files/346147"], "description"=>"<div><h3>Motivation</h3><p>Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II) molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules.</p> <h3>Method</h3><p>We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE.</p> <h3>Result</h3><p>The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in recognizing binding cores. We further analyzed the motifs detected by TEPITOPEpan, examining the corresponding literature of immunology. Its online server and PSSMs therein are available at <a href=\"http://www.biokdd.fudan.edu.cn/Service/TEPITOPEpan/\">http://www.biokdd.fudan.edu.cn/Service/TEPITOPEpan/</a>.</p> </div>", "links"=>[], "tags"=>["extending", "tepitope", "peptide", "binding", "covering", "700", "hla-dr", "molecules"], "article_id"=>128357, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0030483.s001", "https://dx.doi.org/10.1371/journal.pone.0030483.s002", "https://dx.doi.org/10.1371/journal.pone.0030483.s003", "https://dx.doi.org/10.1371/journal.pone.0030483.s004", "https://dx.doi.org/10.1371/journal.pone.0030483.s005", "https://dx.doi.org/10.1371/journal.pone.0030483.s006"], "stats"=>{"downloads"=>30, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/TEPITOPEpan_Extending_TEPITOPE_for_Peptide_Binding_Prediction_Covering_over_700_HLA_DR_Molecules/128357", "title"=>"TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR Molecules", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-23 02:19:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/676333"], "description"=>"<p>Identifying HLA-DR ligands and T-cell epitopes, respectively. Ligand and Epitopes show the number of HLA-DR ligands and HLA-DR epitopes, respectively. Avg per ligand shows the average AUC over all ligands, and Avg per allele gives the average of Avg per ligand over all alleles.</p>", "links"=>[], "tags"=>["syf-set6"], "article_id"=>346820, "categories"=>["Physics", "Biochemistry", "Biophysics", "Information And Computing Sciences", "Immunology", "Biological Sciences"], "users"=>["Lianming Zhang", "Yiqing Chen", "Hau-San Wong", "Shuigeng Zhou", "Hiroshi Mamitsuka", "Shanfeng Zhu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030483.t007", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_on_SYF_Set6_and_EIEDB_SET7_/346820", "title"=>"Evaluation on SYF-Set6 and EIEDB-SET7.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-23 01:53:40"}

PMC Usage Stats | Further Information

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Relative Metric

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