由于紫外分光光度法、NBT/PMS显色法、荧光分析法，MTS/PMS还原法等黄嘌呤氧化酶（XO）抑制活性检测方法对多肽检测的局限性，本文建立了适用于筛选降尿酸多肽类物质的体外测定方法，采用双酶偶联法联合高效液相色谱法（HPLC法）测定多肽类物质的体外黄嘌呤氧化酶抑制活性。以双酶偶联法优化样品测定的反应体系，得到最适反应条件：黄嘌呤浓度0.22 mmol/L，酶浓度0.52 u/mL，缓冲液pH 8.0，反应温度30 ℃，反应时间20 min；优化尿酸分离的液相条件，确定最适检测条件：95% 15 mmol/L NH4H2PO4+5%甲醇，pH 6.5，流速1 mL/min，柱温25 ℃，检测波长290 nm。实验表明，最适条件下双酶偶联法和HPLC法检测精密度良好，准确度达95%以上。双酶偶联法联合HPLC法可高效、准确进行多肽降尿酸活性检测。双酶偶联法联合HPLC法证明还原型谷胱甘肽（GSH）和氧化型谷胱甘肽（GSSG）具有黄嘌呤氧化酶抑制活性，可作为降尿酸肽。

Because UV spectrophotometry, NBT/PMS colorimetry, fluorescence analysis, MTS/PMS reduction and other xanthine oxidase (XO) inhibitory activity assays had limitations for the detection of peptides, a method for the screening and determination of anti-hyperuricemic peptides in vitro was established and optimized in this study. The in vitro xanthineoxidase inhibitory activity of peptides was determined by double enzymecoupling method combined with high performance liquid chromatography (HPLC). The optimal reaction conditions were determined by double-enzyme coupling method. The optimum reaction conditions were as follows: 0.22 mmol/L xanthine, 0.52 u/mL xanthine oxidase (XO), Tris-HCl pH 8.0, reaction temperature 30℃, and reaction time 20 min for catalytic reaction. Meanwhile, the optimal conditions for the determination of uric acid by HPLC were determined as follows: 95% 15 mmol/L NH4H2PO4 and 5% methanol at pH 6.5, 1 mL/min of flow rate, column temperature 25℃, and detection wavelength 290 nm. The results of double-enzyme coupling assay combing with HPLC method showed a good stability and higher accuracy than single HPLC and double-enzyme coupling detection method with the accuracy more than 95%. Double-enzyme coupling method combined with HPLC could effectively and accurately detect the activity of peptide-reduced uric acid. This novel detection method demonstrated that reduced glutathione (GSH) and oxidized glutathione (GSSG) had xanthine oxidase inhibitory activity which could be used as uric acidlowering peptides.

国家自然科学基金资助项目（31671804）；“广东特支计划”科技青年拔尖人才项目（2014TQ01N645）；广东省科技计划项目（2017B090901063、2015B020230001）；广州市产学研协同创新重大专项（201604020047）；中央高校基本科研业务费项目（2017ZD079）