論文

査読有り
2017年9月6日

An interaction-based approach for affinity prediction between antigen peptide and human leukocyte antigen using COMBINE analysis

Chem-Bio Informatics Journal
  • Shinya Nakamura
  • ,
  • Rie Ohmura
  • ,
  • Isao Nakanishi

17
開始ページ
93
終了ページ
102
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1273/cbij.17.93
出版者・発行元
Chem-Bio Informatics Society

In peptide vaccine therapy, a peptide with high affinity for human leukocyte antigen (HLA), is important to stimulate the immune system to kill cancer cells. Several methods to predict HLA–peptide binding have been reported, but most of them rely on informatics to analyze the amino acid sequence of the peptide. Although intermolecular-interaction-based analysis is expected to improve prediction accuracy, such a method generally involves a high computational cost. Therefore, comparative binding energy (COMBINE) analysis, a 3D-quantitative structure–activity relationship method, combined with a rapidly implemented protein modeling method, was applied to solve this problem. The new method enabled quick evaluation of peptide affinity predictions with accuracy beyond a statistical method. In addition, several amino acid residues of HLA, which are known to be important for peptide binding, could be identified.

リンク情報
DOI
https://doi.org/10.1273/cbij.17.93
ID情報
  • DOI : 10.1273/cbij.17.93
  • ISSN : 1347-0442
  • ISSN : 1347-6297
  • SCOPUS ID : 85029178551

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