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Prediction of Optimal pH in Hydrolytic Reaction of Beta-glucosidase

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Abstract

This is the continuation of our studies to use very basic information on enzyme to predict optimal reaction parameters in enzymatic reactions because the gap between available enzyme sequences and their available reaction parameters is widening. In this study, 23 features selected from 540 plus features of individual amino acid as well as a feature combined whole protein information were screened as independents in a 20-1 feedforward backpropagation neural network for predicting optimal pH in beta-glucosidase’s hydrolytic reaction because this enzyme drew attention recently due to its role in biofuel industry. The results show that 11 features can be used as independents for the prediction, while the feature of amino acid distribution probability works better than the rest independents for the prediction. Our study paves a way to predict the optimal reaction parameters of enzymes based on the amino acid features of enzyme sequences.

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Acknowledgments

This study was partly supported by Guangxi Science Foundation (0991006Z, 10-046-06, 2010GXNSFF013003, 11-031-11, and 12-071-10) and by Guangxi Academy of Sciences (11YJ24KY01). The authors wish to thank the Library of Guangxi Zhuang Autonomous Region for purchasing the book, Biometry.

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Authors and Affiliations

  1. State Key Laboratory of Non-food Biomass Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Key Laboratory of Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi, 530007, China

    Shaomin Yan & Guang Wu

  2. DreamSciTech.com

    Guang Wu

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  1. Shaomin Yan
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  2. Guang Wu
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Correspondence to Guang Wu.

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Yan, S., Wu, G. Prediction of Optimal pH in Hydrolytic Reaction of Beta-glucosidase. Appl Biochem Biotechnol 169, 1884–1894 (2013). https://doi.org/10.1007/s12010-013-0103-8

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  • DOI: https://doi.org/10.1007/s12010-013-0103-8

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