このエントリーをはてなブックマークに追加
ID 63756
フルテキストURL
fulltext.pdf 4.26 MB
著者
Wang, Jin Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University
Sakai, Kenji Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University ORCID Kaken ID publons researchmap
Kiwa, Toshihiko Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University ORCID Kaken ID publons researchmap
抄録
Peptides are promising molecular-binding elements and have attracted great interest in novel biosensor development. In this study, a series of peptides derived from odorant-binding proteins (OBPs) were rationally designed for recognition of SARS-CoV-2-related volatile organic compounds (VOCs). Ethanol, nonanal, benzaldehyde, acetic acid, and acetone were selected as representative VOCs in the exhaled breath during the COVID-19 infection. Computational docking and prediction tools were utilized for OBPs peptide characterization and analysis. Multiple parameters, including the docking model, binding affinity, sequence specification, and structural folding, were investigated. The results demonstrated a rational, rapid, and efficient approach for designing breath-borne VOC-recognition peptides, which could further improve the biosensor performance for pioneering COVID-19 screening and many other applications.
キーワード
rational design
odorant-binding protein
peptide
SARS-CoV-2
volatile organic compounds
computational tools
発行日
2022-06-18
出版物タイトル
Molecules
27巻
12号
出版者
MDPI
開始ページ
3917
ISSN
1420-3049
資料タイプ
学術雑誌論文
言語
英語
OAI-PMH Set
岡山大学
著作権者
© 2022 by the authors.
論文のバージョン
publisher
PubMed ID
DOI
Web of Science KeyUT
関連URL
isVersionOf https://doi.org/10.3390/molecules27123917
ライセンス
https://creativecommons.org/licenses/by/4.0/
助成機関名
Japan Society for the Promotion of Science
助成番号
21K14169