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2018 Fiscal Year Final Research Report

Development of comprehensive calculation method of HLA-peptide affinity and application to elucidation of the pathogenesis of Behcet's disease

Research Project

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Project/Area Number 16K00397
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Life / Health / Medical informatics
Research InstitutionKagoshima University (2018)
Nagasaki University (2016-2017)

Principal Investigator

Ishikawa Takeshi  鹿児島大学, 理工学域工学系, 教授 (80505909)

Co-Investigator(Kenkyū-buntansha) 野口 博司  日本薬科大学, 薬学部, 教授 (60126141)
竹内 二士夫  東京聖栄大学, 公私立大学の部局等, 教授 (70154979)
Project Period (FY) 2016-04-01 – 2019-03-31
Keywordsヒト主要組織適合抗原 / ベーチェット病 / エピトープ予測 / 結合親和性予測 / ドッキング計算 / フラグメント分子軌道法
Outline of Final Research Achievements

In this study, we developed a method to predict the binding affinity of human leukocyte antigen (HLA) and peptide fragments. While the previous methods use experimental affinity databases of the peptides, our methods can predict the binding affinity only using the structural information of HLA. Therefore, it is an important feature of our method that prediction is possible even for HLA alleles with few experimental data. In addition, the relative binding affinity of “AAAAAIFVI”, which is considered as a candidate for an antigenic peptide of Behcet's disease (BD), was high for HLA-B*51 (this HLA is correlated with BD), and was low for HLA-B*52 (this HLA is not correlated with BD). These results indicate the possibility that AAAAAIFVI is an antigenic peptide of BD.

Free Research Field

計算化学

Academic Significance and Societal Importance of the Research Achievements

本研究で開発したHLAとペプチド断片の結合親和性の予測法は、特定のHLAに結合するペプチドの網羅的探索に利用可能であり、他のHLA関連疾患への応用も期待される。例えば、リウマチや糖尿病といった生活習慣病、様々な自己免疫疾患、癌などもHLAと有意な相関を示すことが知られている。さらに、ウイルス感染における免疫応答の個人差や、抗原提示を利用したペプチドワクチンの開発などにおいても、HLAとペプチドの親和性が重要な意味を担っている。今後、結合親和性の予測精度を向上させることができれば、これらを含む様々な医学・薬学研究に貢献することが期待される。

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Published: 2020-03-30  

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