Document Detail


Prediction of Michaelis-Menten Constant of beta-Glucosidases using Nitrophenyl-beta-D-glucopyranoside as Substrate.
MedLine Citation:
PMID:  21592074     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In this study, we attempted to use the neural network to model a quantitative structure-K(m) (Michaelis-Menten constant) relationship for beta-glucosidase, which is an important enzyme to cut the beta-bond linkage in glucose while K(m) is a very important parameter in enzymatic reactions. Eight feedforward backpropagation neural networks with different layers and neurons were applied for the development of predictive model, and twenty-five different features of amino acids were chosen as predictors one by one. The results show that the 20-1 feedforward backpropagation neural network can serve as a predictive model while the normalized polarizability index as well as the amino-acid distribution probability can serve as the predictors. This study threw lights on the possibility of predicting the K(m) in beta-glucosidases based on their amino-acid features.
Authors:
Shaomin Yan; Guang Wu
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-5-19
Journal Detail:
Title:  Protein and peptide letters     Volume:  -     ISSN:  1875-5305     ISO Abbreviation:  -     Publication Date:  2011 May 
Date Detail:
Created Date:  2011-5-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9441434     Medline TA:  Protein Pept Lett     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. hongguanglishibahao@yahoo.com.
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