紫菜降压肽酶膜耦合反应制备工艺RBF神经网络优化
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ACE Inhibitor Peptides from Porphyra yezoensis in Batch Membrane Reactor Based on RBF-ANN
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    摘要:

    以条斑紫菜为原料,利用建立的酶膜反应器制备紫菜降压肽,为获得最大蛋白转化率,采用径向基人工神经网络模型(RBF-ANN)对该工艺进行优化,并采用交互验证的方法优化并建立最优模型。通过模型的模拟及优化,得到间歇式酶膜耦合制备紫菜降压肽的最佳工艺条件:底物质量浓度1.0 g/mL、加酶量4%、反应温度50℃、pH值9.0、循环泵转速300r/min的条件下反应60min。其蛋白转化率为55.67%,多肽得率为22.27%,单位酶产肽量为13.91,IC50质量浓度为0.492 mg/mL。在优化工艺条件基础上进行连续酶膜耦合研究,结果表明:与传统酶解反应相比,蛋白转化率提高21.98%,多肽得率提高8.79%,单位酶肽产量比间歇反应提高

    Abstract:

    4.7倍。To explore an optimal preparation method of angiotensin converting enzyme (ACE) inhibitor peptides from Porphyra yezoensis with protease, several conditions about batch membrane reaction with raw material feeding were attempted in enzymatic membrane reactor. Radial basis function neural network (RBF-ANN) models were employed to optimize the condition. Some parameters were optimized based on cross-validation to calibrate a robust model. The optimal operating conditions for the maximum protein conversion rate obtained by the model were as followings: substrate concentration 1.0g/mL, enzyme concentration 4%, reaction temperature 50℃, pH value 9.0, pump rotation speed 300 r/min and reaction time 60 min. Under these conditions, protein conversion rate was 55.67%, the yield of peptides was 22.27%, quantity of peptides per gram of enzyme was 13.91 and IC50 was 0.492mg/mL. Base on the optimum conditions enzyme membrane reaction with continuous feeding Porphyra yezoensis was also studied: compared to the traditional methods, protein conversion rate improved by 21.98%, yield of peptides increased by 8.79%, and quantity of peptides per gram of enzyme was improved by 4.7 times.

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刘斌,马海乐,李树君,李文,辛君伟.紫菜降压肽酶膜耦合反应制备工艺RBF神经网络优化[J].农业机械学报,2010,41(5):120-125.

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