A Novel Peptide Binding Prediction Approach for HLA-DR Molecule Based on Sequence and Structural Information
Autor: | Gaofeng Pan, Yilei Zhao, Zhao Li, Fei Guo, Jijun Tang |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
Article Subject Structural similarity Molecular Sequence Data lcsh:Medicine Peptide Peptide binding Computational biology Bioinformatics Major histocompatibility complex General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Epitopes Similarity (network science) Protein Interaction Mapping HLA-DR Molecule Amino Acid Sequence chemistry.chemical_classification Binding Sites General Immunology and Microbiology biology lcsh:R General Medicine HLA-DR Antigens Molecular Docking Simulation 030104 developmental biology chemistry Drug Design biology.protein Peptides Function (biology) Epitope Mapping Research Article Protein Binding |
Zdroj: | BioMed Research International BioMed Research International, Vol 2016 (2016) |
ISSN: | 2314-6141 2314-6133 |
Popis: | MHC molecule plays a key role in immunology, and the molecule binding reaction with peptide is an important prerequisite for T cell immunity induced. MHC II molecules do not have conserved residues, so they appear as open grooves. As a consequence, this will increase the difficulty in predicting MHC II molecules binding peptides. In this paper, we aim to propose a novel prediction method for MHC II molecules binding peptides. First, we calculate sequence similarity and structural similarity between different MHC II molecules. Then, we reorder pseudosequences according to descending similarity values and use a weight calculation formula to calculate new pocket profiles. Finally, we use three scoring functions to predict binding cores and evaluate the accuracy of prediction to judge performance of each scoring function. In the experiment, we set a parameterαin the weight formula. By changingαvalue, we can observe different performances of each scoring function. We compare our method with the best function to some popular prediction methods and ultimately find that our method outperforms them in identifying binding cores of HLA-DR molecules. |
Databáze: | OpenAIRE |
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