Cargando…

The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules

Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experime...

Descripción completa

Detalles Bibliográficos
Autores principales: Mei, Xueyin, Li, Xingyu, Zhao, Chen, Liu, Anna, Ding, Yan, Shen, Chuanlai, Li, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105472/
https://www.ncbi.nlm.nih.gov/pubmed/35563019
http://dx.doi.org/10.3390/ijms23094629
_version_ 1784708048846061568
author Mei, Xueyin
Li, Xingyu
Zhao, Chen
Liu, Anna
Ding, Yan
Shen, Chuanlai
Li, Jian
author_facet Mei, Xueyin
Li, Xingyu
Zhao, Chen
Liu, Anna
Ding, Yan
Shen, Chuanlai
Li, Jian
author_sort Mei, Xueyin
collection PubMed
description Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection.
format Online
Article
Text
id pubmed-9105472
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91054722022-05-14 The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules Mei, Xueyin Li, Xingyu Zhao, Chen Liu, Anna Ding, Yan Shen, Chuanlai Li, Jian Int J Mol Sci Article Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection. MDPI 2022-04-22 /pmc/articles/PMC9105472/ /pubmed/35563019 http://dx.doi.org/10.3390/ijms23094629 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mei, Xueyin
Li, Xingyu
Zhao, Chen
Liu, Anna
Ding, Yan
Shen, Chuanlai
Li, Jian
The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title_full The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title_fullStr The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title_full_unstemmed The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title_short The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules
title_sort use of molecular dynamics simulation method to quantitatively evaluate the affinity between hbv antigen t cell epitope peptides and hla-a molecules
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105472/
https://www.ncbi.nlm.nih.gov/pubmed/35563019
http://dx.doi.org/10.3390/ijms23094629
work_keys_str_mv AT meixueyin theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT lixingyu theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT zhaochen theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT liuanna theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT dingyan theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT shenchuanlai theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT lijian theuseofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT meixueyin useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT lixingyu useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT zhaochen useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT liuanna useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT dingyan useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT shenchuanlai useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules
AT lijian useofmoleculardynamicssimulationmethodtoquantitativelyevaluatetheaffinitybetweenhbvantigentcellepitopepeptidesandhlaamolecules