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Small-molecule biosensing: from bio-inspired recognition elements and sensor devices to AI-guided design
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DOI：10.1093/bulcsj/uoag031.png)
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Abstract
En 中文
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.
Keywords:
AI-guided molecular recognition
recognition elements
small molecule biosensor
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