Document Detail


Prediction of Optimal pH in Hydrolytic Reaction of Beta-glucosidase.
MedLine Citation:
PMID:  23344943     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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.
Authors:
Shaomin Yan; Guang Wu
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-24
Journal Detail:
Title:  Applied biochemistry and biotechnology     Volume:  -     ISSN:  1559-0291     ISO Abbreviation:  Appl. Biochem. Biotechnol.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-24     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8208561     Medline TA:  Appl Biochem Biotechnol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
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.
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