Literature DB >> 26416257

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

Massimo Andreatta1, Edita Karosiene2, Michael Rasmussen3, Anette Stryhn3, Søren Buus3, Morten Nielsen4,5.   

Abstract

A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

Entities:  

Keywords:  Artificial neural networks; Binding core; MHC class II; Peptide binding; Peptide-MHC; T cell cross-reactivity

Mesh:

Substances:

Year:  2015        PMID: 26416257      PMCID: PMC4637192          DOI: 10.1007/s00251-015-0873-y

Source DB:  PubMed          Journal:  Immunogenetics        ISSN: 0093-7711            Impact factor:   2.846


  39 in total

1.  Molecular basis for recognition of an arthritic peptide and a foreign epitope on distinct MHC molecules by a single TCR.

Authors:  D Basu; S Horvath; I Matsumoto; D H Fremont; P M Allen
Journal:  J Immunol       Date:  2000-06-01       Impact factor: 5.422

2.  Naturally processed HLA class II peptides reveal highly conserved immunogenic flanking region sequence preferences that reflect antigen processing rather than peptide-MHC interactions.

Authors:  A J Godkin; K J Smith; A Willis; M V Tejada-Simon; J Zhang; T Elliott; A V Hill
Journal:  J Immunol       Date:  2001-06-01       Impact factor: 5.422

Review 3.  Heterologous immunity between viruses.

Authors:  Raymond M Welsh; Jenny W Che; Michael A Brehm; Liisa K Selin
Journal:  Immunol Rev       Date:  2010-05       Impact factor: 12.988

4.  Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction.

Authors:  I A Doytchinova; D R Flower
Journal:  Bioinformatics       Date:  2003-11-22       Impact factor: 6.937

Review 5.  Antigen presentation by MHC class II molecules: invariant chain function, protein trafficking, and the molecular basis of diverse determinant capture.

Authors:  F Castellino; G Zhong; R N Germain
Journal:  Hum Immunol       Date:  1997-05       Impact factor: 2.850

6.  A functional and structural basis for TCR cross-reactivity in multiple sclerosis.

Authors:  Heather L E Lang; Helle Jacobsen; Shinji Ikemizu; Christina Andersson; Karl Harlos; Lars Madsen; Peter Hjorth; Leif Sondergaard; Arne Svejgaard; Kai Wucherpfennig; David I Stuart; John I Bell; E Yvonne Jones; Lars Fugger
Journal:  Nat Immunol       Date:  2002-09-03       Impact factor: 25.606

7.  Specificity and promiscuity among naturally processed peptides bound to HLA-DR alleles.

Authors:  R M Chicz; R G Urban; J C Gorga; D A Vignali; W S Lane; J L Strominger
Journal:  J Exp Med       Date:  1993-07-01       Impact factor: 14.307

8.  Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.

Authors:  Morten Nielsen; Claus Lundegaard; Ole Lund
Journal:  BMC Bioinformatics       Date:  2007-07-04       Impact factor: 3.169

9.  NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.

Authors:  Morten Nielsen; Claus Lundegaard; Thomas Blicher; Kasper Lamberth; Mikkel Harndahl; Sune Justesen; Gustav Røder; Bjoern Peters; Alessandro Sette; Ole Lund; Søren Buus
Journal:  PLoS One       Date:  2007-08-29       Impact factor: 3.240

10.  The immune epitope database (IEDB) 3.0.

Authors:  Randi Vita; James A Overton; Jason A Greenbaum; Julia Ponomarenko; Jason D Clark; Jason R Cantrell; Daniel K Wheeler; Joseph L Gabbard; Deborah Hix; Alessandro Sette; Bjoern Peters
Journal:  Nucleic Acids Res       Date:  2014-10-09       Impact factor: 16.971

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  125 in total

1.  Improved methods for predicting peptide binding affinity to MHC class II molecules.

Authors:  Kamilla Kjaergaard Jensen; Massimo Andreatta; Paolo Marcatili; Søren Buus; Jason A Greenbaum; Zhen Yan; Alessandro Sette; Bjoern Peters; Morten Nielsen
Journal:  Immunology       Date:  2018-02-06       Impact factor: 7.397

2.  Cepharanthine blocks TSH receptor peptide presentation by HLA-DR3: Therapeutic implications to Graves' disease.

Authors:  Cheuk Wun Li; Roman Osman; Francesca Menconi; Erlinda Concepcion; Yaron Tomer
Journal:  J Autoimmun       Date:  2020-01-21       Impact factor: 7.094

3.  Improved peptide-MHC class II interaction prediction through integration of eluted ligand and peptide affinity data.

Authors:  Christian Garde; Sri H Ramarathinam; Emma C Jappe; Morten Nielsen; Jens V Kringelum; Thomas Trolle; Anthony W Purcell
Journal:  Immunogenetics       Date:  2019-06-10       Impact factor: 2.846

4.  TCR Repertoire Intratumor Heterogeneity in Localized Lung Adenocarcinomas: An Association with Predicted Neoantigen Heterogeneity and Postsurgical Recurrence.

Authors:  Alexandre Reuben; Rachel Gittelman; Jianjun Gao; Jiexin Zhang; Erik C Yusko; Chang-Jiun Wu; Ryan Emerson; Jianhua Zhang; Christopher Tipton; Jun Li; Kelly Quek; Vancheswaran Gopalakrishnan; Runzhe Chen; Luis M Vence; Tina Cascone; Marissa Vignali; Junya Fujimoto; Jaime Rodriguez-Canales; Edwin R Parra; Latasha D Little; Curtis Gumbs; Marie-Andrée Forget; Lorenzo Federico; Cara Haymaker; Carmen Behrens; Sharon Benzeno; Chantale Bernatchez; Boris Sepesi; Don L Gibbons; Jennifer A Wargo; William N William; Stephen Swisher; John V Heymach; Harlan Robins; J Jack Lee; Padmanee Sharma; James P Allison; P Andrew Futreal; Ignacio I Wistuba; Jianjun Zhang
Journal:  Cancer Discov       Date:  2017-07-21       Impact factor: 39.397

5.  Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Authors:  Massimo Andreatta; Vanessa I Jurtz; Thomas Kaever; Alessandro Sette; Bjoern Peters; Morten Nielsen
Journal:  Immunology       Date:  2017-06-19       Impact factor: 7.397

6.  Distinct editing functions of natural HLA-DM allotypes impact antigen presentation and CD4+ T cell activation.

Authors:  Miguel Álvaro-Benito; Eliot Morrison; Friederike Ebner; Esam T Abualrous; Marie Urbicht; Marek Wieczorek; Christian Freund
Journal:  Cell Mol Immunol       Date:  2018-11-22       Impact factor: 11.530

7.  HLA-DO Modulates the Diversity of the MHC-II Self-peptidome.

Authors:  Padma P Nanaware; Mollie M Jurewicz; John D Leszyk; Scott A Shaffer; Lawrence J Stern
Journal:  Mol Cell Proteomics       Date:  2018-12-20       Impact factor: 5.911

8.  Current progress of immunoinformatics approach harnessed for cellular- and antibody-dependent vaccine design.

Authors:  Ada Kazi; Candy Chuah; Abu Bakar Abdul Majeed; Chiuan Herng Leow; Boon Huat Lim; Chiuan Yee Leow
Journal:  Pathog Glob Health       Date:  2018-03-12       Impact factor: 2.894

9.  An automated benchmarking platform for MHC class II binding prediction methods.

Authors:  Massimo Andreatta; Thomas Trolle; Zhen Yan; Jason A Greenbaum; Bjoern Peters; Morten Nielsen
Journal:  Bioinformatics       Date:  2018-05-01       Impact factor: 6.937

Review 10.  Current tools for predicting cancer-specific T cell immunity.

Authors:  David Gfeller; Michal Bassani-Sternberg; Julien Schmidt; Immanuel F Luescher
Journal:  Oncoimmunology       Date:  2016-04-25       Impact factor: 8.110

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