Literature DB >> 19519456

Predicting affinity and specificity of antigenic peptide binding to major histocompatibility class I molecules.

Florian Sieker1, Andreas May, Martin Zacharias.   

Abstract

Major Histo-Compatibility (MHC) class I molecules are major agents of the mammalian adaptive immune system. Class I molecules bind short antigenic peptides with a length of 8-10 residues in the Endoplasmatic Reticulum (ER) and after transport to the cell surface the peptides are presented to T-lymphocytes. The binding site of class I molecules is formed by a deep cleft between two alpha-helices at top of an extended beta-sheet. Only tightly bound high-affinity peptides have a chance to reach the cell surface and trigger an immune response. It is therefore of great interest to identify possible high-affinity antigenic peptides that could be used as vaccines to help the immune system to detect viral infections or kill malignant cells. A large number of crystal structures of antigenic peptides in complex with class I alleles have been determined that allow to understand the structural details important for peptide binding. Biophysical and biochemical analysis of peptide-class I complexes has resulted in a number of rules concerning the selection of high-affinity peptides. However, an accurate prediction of allele specific peptide-binding is still not possible. This issue is currently addressed by various computational tools developed by the bioinformatics community. The computational efforts range from statistical analysis of peptide motifs stored in databases to application of neural network methods and support vector machine approaches. In addition, structure based approaches to predict class I binding specificity including molecular modeling and molecular dynamics (MD) simulations will also be presented.

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Year:  2009        PMID: 19519456     DOI: 10.2174/138920309788452191

Source DB:  PubMed          Journal:  Curr Protein Pept Sci        ISSN: 1389-2037            Impact factor:   3.272


  10 in total

1.  Prediction of protease substrates using sequence and structure features.

Authors:  David T Barkan; Daniel R Hostetter; Sami Mahrus; Ursula Pieper; James A Wells; Charles S Craik; Andrej Sali
Journal:  Bioinformatics       Date:  2010-05-26       Impact factor: 6.937

Review 2.  High throughput T epitope mapping and vaccine development.

Authors:  Giuseppina Li Pira; Federico Ivaldi; Paolo Moretti; Fabrizio Manca
Journal:  J Biomed Biotechnol       Date:  2010-06-15

3.  Structural allele-specific patterns adopted by epitopes in the MHC-I cleft and reconstruction of MHC:peptide complexes to cross-reactivity assessment.

Authors:  Dinler A Antunes; Gustavo F Vieira; Maurício M Rigo; Samuel P Cibulski; Marialva Sinigaglia; José A B Chies
Journal:  PLoS One       Date:  2010-04-26       Impact factor: 3.240

4.  PeptX: using genetic algorithms to optimize peptides for MHC binding.

Authors:  Bernhard Knapp; Verena Giczi; Reiner Ribarics; Wolfgang Schreiner
Journal:  BMC Bioinformatics       Date:  2011-06-17       Impact factor: 3.169

5.  The Carboxy Terminus of the Ligand Peptide Determines the Stability of the MHC Class I Molecule H-2Kb: A Combined Molecular Dynamics and Experimental Study.

Authors:  Esam Tolba Abualrous; Sunil Kumar Saini; Venkat Raman Ramnarayan; Florin Tudor Ilca; Martin Zacharias; Sebastian Springer
Journal:  PLoS One       Date:  2015-08-13       Impact factor: 3.240

6.  Identification of human leukemia antigen A*0201-restricted epitopes derived from epidermal growth factor pathway substrate number 8.

Authors:  Baishan Tang; Weijun Zhou; Jingwen Du; Yanjie He; Yuhua Li
Journal:  Mol Med Rep       Date:  2015-04-23       Impact factor: 2.952

7.  Towards peptide vaccines against Zika virus: Immunoinformatics combined with molecular dynamics simulations to predict antigenic epitopes of Zika viral proteins.

Authors:  Muhammad Usman Mirza; Shazia Rafique; Amjad Ali; Mobeen Munir; Nazia Ikram; Abdul Manan; Outi M H Salo-Ahen; Muhammad Idrees
Journal:  Sci Rep       Date:  2016-12-09       Impact factor: 4.379

8.  Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening.

Authors:  Muhammad Waqas; Ali Haider; Abdur Rehman; Muhammad Qasim; Ahitsham Umar; Muhammad Sufyan; Hafiza Nisha Akram; Asif Mir; Roha Razzaq; Danish Rasool; Rana Adnan Tahir; Sheikh Arslan Sehgal
Journal:  Biomed Res Int       Date:  2021-02-26       Impact factor: 3.411

Review 9.  Thermodynamics of Peptide-MHC Class II Interactions: Not all Complexes are Created Equal.

Authors:  Andrea Ferrante
Journal:  Front Immunol       Date:  2013-10-01       Impact factor: 7.561

10.  Determine the Potential Epitope Based Peptide Vaccine Against Novel SARS-CoV-2 Targeting Structural Proteins Using Immunoinformatics Approaches.

Authors:  Muhammad Waqas; Ali Haider; Muhammad Sufyan; Sami Siraj; Sheikh Arslan Sehgal
Journal:  Front Mol Biosci       Date:  2020-10-15
  10 in total

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