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Abstract <p>D-Amino acid oxidase (DAAO, EC&#xa0;1.4.3.3) is a FAD-dependent enzyme that catalyzes the oxidative deamination of D-amino acids to produce the corresponding α-keto acids, hydrogen peroxide, and ammonium ion. High stereoselectivity toward D-enantiomers and favorable kinetic parameters make DAAO a convenient biocatalytic element for analytical applications. This review systematizes the main areas of DAAO use in bioanalysis, including clinical diagnostics, monitoring of food and biotechnological processes, and environmental surveillance. Sensor platforms and detection modes are discussed, including colorimetry, fluorimetry, chemiluminescence, electrochemistry, photoelectrochemistry, and oxygen-based detection methods. The review also addresses factors determining analytical suitability, strategies to broaden selectivity, as well as engineering approaches and structure-guided discovery of new DAAOs. Current limitations are highlighted and future prospects are outlined, such as improving enzyme stability, scaling up portable devices, and integrating biosensing with digital analytics and machine-learning algorithms.</p>

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Application of D-Amino Acid Oxidase (DAAO) in Bioanalytics

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • Denis L. Atroshenko,
  • Svyatoslav S. Savin,
  • Tatyana S. Oretskaya,
  • Vladimir I. Tishkov

摘要

Abstract

D-Amino acid oxidase (DAAO, EC 1.4.3.3) is a FAD-dependent enzyme that catalyzes the oxidative deamination of D-amino acids to produce the corresponding α-keto acids, hydrogen peroxide, and ammonium ion. High stereoselectivity toward D-enantiomers and favorable kinetic parameters make DAAO a convenient biocatalytic element for analytical applications. This review systematizes the main areas of DAAO use in bioanalysis, including clinical diagnostics, monitoring of food and biotechnological processes, and environmental surveillance. Sensor platforms and detection modes are discussed, including colorimetry, fluorimetry, chemiluminescence, electrochemistry, photoelectrochemistry, and oxygen-based detection methods. The review also addresses factors determining analytical suitability, strategies to broaden selectivity, as well as engineering approaches and structure-guided discovery of new DAAOs. Current limitations are highlighted and future prospects are outlined, such as improving enzyme stability, scaling up portable devices, and integrating biosensing with digital analytics and machine-learning algorithms.