Analysis of HLA‐A24‐restricted peptides of carcinoembryonic antigen using a novel structure‐based peptide‐HLA docking algorithm

Nakamura, Yoji; Tai, Sachiko; Oshita, Chie; Iizuka, Akira; Ashizawa, Tadashi; Saito, Shuji; Yamaguchi, Shigeki; Kondo, Haruhiko; Yamaguchi, Ken; Akiyama, Yasuto

doi:10.1111/j.1349-7006.2011.01866.x

Cited by 6 publications

(1 citation statement)

References 29 publications

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“…The stability and strength of the binding were not explored; modeling the interaction between the S9F residues and the MHC residues was not carried out. 32 Furthermore, the number of samples used to determine the functional profile was limited, making it difficult to explore possible associations with immunological and virological parameters.…”

Section: Discussionmentioning

confidence: 99%

The APPEESFRS Peptide, Restricted by the HLA-B*35:01 Molecule, and the APPEESFRF Variant Derived from an Autologous HIV-1 Strain Induces Polyfunctional Responses in CD8+ T Cells

Acevedo-Sáenz

Carmona-Pérez

Velilla

et al. 2015

BioResearch Open Access

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Numerous reports have focused on consensus peptides to determine CD8+ T-cell responses; however, few studies evaluated the functional profile using peptides derived from circulating strains of a specific region. We determined the effector profile and maturation phenotype of CD8+ T-cells targeting the consensus APPEESFRS (AS9) epitope and its variant APPEESFRF (AF9), previously identified. The free energy of binding, maturation phenotype, and polyfunctional profile of both peptides were similar. The magnitude of CD8+ T-cell responses to AF9 was greater than the one elicited by AS9, although the difference was not significant. The polyfunctional profile of AF9 was characterized by CD107a/interleukin-2 (IL-2)/macrophage inflammatory protein beta (MIP1β) and by interferon gamma (IFNγ)/MIP1β/tumor necrosis factor alpha (TNFα) in response to AS9. TNFα production was significantly higher in response to AF9 than to AS9, and there was a negative correlation between the absolute number of CD8+ T-cell-producing TNFα and the plasma human immunodeficiency virus (HIV) load, suggesting a role of this cytokine in the control of HIV replication.

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Section: Discussionmentioning

confidence: 99%

The APPEESFRS Peptide, Restricted by the HLA-B*35:01 Molecule, and the APPEESFRF Variant Derived from an Autologous HIV-1 Strain Induces Polyfunctional Responses in CD8+ T Cells

Acevedo-Sáenz

Carmona-Pérez

Velilla

et al. 2015

BioResearch Open Access

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Identification of novel MAGE-A6- and MAGE-A12-derived HLA-A24-restricted cytotoxic T lymphocyte epitopes using an in silico peptide-docking assay

Akiyama

Komiyama

Nakamura

et al. 2012

Cancer Immunol Immunother

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Many cancer-testis antigen genes have been identified; however, few human leukocyte antigen (HLA)-A24-restricted cytotoxic T cell (CTL) epitope peptides are available for clinical immunotherapy. To solve this problem, novel tools increasing the efficacy and accuracy of CTL epitope detection are needed. In the present study, we utilized a highly active dendritic cell (DC)-culture method and an in silico HLA-A24 peptide-docking simulation assay to identify novel CTL epitopes from MAGE-A6 and MAGE-A12 antigens. The highly active DCs, called α-type-1 DCs, were prepared using a combination of maturation reagents to produce a large amount of interleukin-12. Meanwhile, our HLA-A24 peptide-docking simulation assay was previously demonstrated to have an obvious advantage of accuracy over the conventional prediction tool, bioinformatics and molecular analysis section. For CTL induction assays, peripheral blood mononuclear cells derived from six cases of HLA-A24(+) melanoma were used. Through CTL induction against melanoma cell lines and peptide-docking simulation assays, two peptides (IFGDPKKLL from MAGE-A6 and IFSKASEYL from MAGE-A12) were identified as novel CTL epitope candidates. Finally, we verified that the combination of the highly active DC-culture method and HLA-A24 peptide-docking simulation assay might be tools for predicting CTL epitopes against cancer antigens.

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Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation

Ishikawa

2016

J Comput Aided Mol Des

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Binding between major histocompatibility complex (MHC) class I molecules and immunogenic epitopes is one of the most important processes for cell-mediated immunity. Consequently, computational prediction of amino acid sequences of MHC class I binding peptides from a given sequence may lead to important biomedical advances. In this study, an efficient structure-based method for predicting peptide binding to MHC class I molecules was developed, in which the binding free energy of the peptide was evaluated by two individual docking simulations. An original penalty function and restriction of degrees of freedom were determined by analysis of 361 published X-ray structures of the complex and were then introduced into the docking simulations. To validate the method, calculations using a 50-amino acid sequence as a prediction target were performed. In 27 calculations, the binding free energy of the known peptide was within the top 5 of 166 peptides generated from the 50-amino acid sequence. Finally, demonstrative calculations using a whole sequence of a protein as a prediction target were performed. These data clearly demonstrate high potential of this method for predicting peptide binding to MHC class I molecules.

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Analysis of HLA‐A24‐restricted peptides of carcinoembryonic antigen using a novel structure‐based peptide‐HLA docking algorithm

Cited by 6 publications

References 29 publications

The APPEESFRS Peptide, Restricted by the HLA-B*35:01 Molecule, and the APPEESFRF Variant Derived from an Autologous HIV-1 Strain Induces Polyfunctional Responses in CD8+ T Cells

The APPEESFRS Peptide, Restricted by the HLA-B*35:01 Molecule, and the APPEESFRF Variant Derived from an Autologous HIV-1 Strain Induces Polyfunctional Responses in CD8+ T Cells

Identification of novel MAGE-A6- and MAGE-A12-derived HLA-A24-restricted cytotoxic T lymphocyte epitopes using an in silico peptide-docking assay

Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation

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