
| ID | 71385 |
| フルテキストURL | |
| 著者 |
Wang, Jin
Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University
Kiwa, Toshihiko
Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University
ORCID
Kaken ID
publons
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| 抄録 | Precise detection of small molecules—including neurotransmitters, hormones, pesticides, and environmental toxins—remains a fundamental challenge in chemical sensing and bioelectronics due to their low molecular weight, structural similarity, and limited intrinsic signal transduction. Bio-inspired molecular recognition strategies have therefore played an important role in enabling selective and sensitive small-molecule detection across diverse sensing platforms. This account summarizes the author's research trajectory on small-molecule biosensors, systematically covering the development of molecular recognition elements and their integration into electrochemical, plasmonic, fluorescence, and terahertz-based sensing devices. The work spans antibody-derived peptide recognition elements, enzyme-based microelectrochemical sensors for multiplex pesticide detection, peptide-based surface plasmon resonance sensors, fluorescence-based molecular probes, and DNA-aptamer-functionalized sensors for label-free, real-time detection. Collectively, these studies illustrate a coherent approach to sensor development that couples bio-inspired recognition with device engineering and signal transduction optimization. Building on these established bio-inspired methodologies, recent efforts have begun to explore the use of artificial intelligence (AI) and data-driven modeling as supportive tools for the design and optimization of molecular recognition elements. While these AI-guided strategies are still at an early, largely prospective stage, they highlight a potential transition from empirical discovery toward more predictive and scalable design paradigms. Together, this body of work highlights a transformative, AI-enabled framework for small-molecule biosensing, in which molecular recognition design, physics-based simulation, and biosensor engineering converge to enable predictive, self-adaptive, and accelerated discovery of next-generation sensing systems.
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| キーワード | AI-guided molecular recognition
recognition elements
small molecule biosensor
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| 発行日 | 2026-02-19
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| 出版物タイトル |
Bulletin of the Chemical Society of Japan
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| 巻 | 99巻
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| 号 | 3号
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| 出版者 | Oxford University Press (OUP)
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| 開始ページ | uoag031
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| ISSN | 0009-2673
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| NCID | AA00580132
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| 資料タイプ |
学術雑誌論文
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| 言語 |
英語
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| OAI-PMH Set |
岡山大学
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| 著作権者 | © The Author(s) 2026.
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| 論文のバージョン | publisher
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| DOI | |
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| 関連URL | isVersionOf https://doi.org/10.1093/bulcsj/uoag031
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| ライセンス | https://creativecommons.org/licenses/by/4.0/
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| Citation | Jin Wang, Toshihiko Kiwa, Small-molecule biosensing: from bio-inspired recognition elements and sensor devices to AI-guided design, Bulletin of the Chemical Society of Japan, Volume 99, Issue 3, March 2026, uoag031, https://doi.org/10.1093/bulcsj/uoag031
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| 助成情報 |
JPJS00420230010:
( 独立行政法人日本学術振興会 / Japan Society for the Promotion of Science )
24K07524:
AuNPs and DNA Aptamer-Driven Terahertz Sensor for Highly Sensitive Detection of Small Molecules
( 独立行政法人日本学術振興会 / Japan Society for the Promotion of Science )
( 公益財団法人島津科学技術振興財団 / Shimadzu Science Foundation )
( 公益財団法人ウエスコ学術振興財団 / Wesco Scientific Promotion Foundation )
( 公益財団法人八雲環境科学振興財団 / Yakumo Foundation for Environmental Science )
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