Prediction of Optimal pH in Hydrolytic Reaction of Beta-glucosidase
- PDF / 500,392 Bytes
- 11 Pages / 439.37 x 666.142 pts Page_size
- 87 Downloads / 182 Views
Prediction of Optimal pH in Hydrolytic Reaction of Beta-glucosidase Shaomin Yan & Guang Wu
Received: 31 July 2012 / Accepted: 13 January 2013 / Published online: 24 January 2013 # Springer Science+Business Media New York 2013
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. Keywords Amino acid feature . Beta-glucosidase . Distribution probability . Optimal pH . Prediction
Introduction To maximize the outputs of enzymatic reactions, many elegant reaction parameters need to be met. These reaction parameters are generally found through experiments, and thus become very valuable because they may guide researchers to work more effectively and
Electronic supplementary material The online version of this article (doi:10.1007/s12010-013-0103-8) contains supplementary material, which is available to authorized users. S. Yan : G. Wu (*) 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 e-mail: [email protected] G. Wu DreamSciTech.com
Appl Biochem Biotechnol (2013) 169:1884–1894
1885
efficiently with newly mutated and found enzymes. Unfortunately, many enzymatic reaction parameters are not properly documented in scientific literature, although numerous time and money were spent to determine them in experiments. With fast developments in sequencing technology, more and more new enzymes become available but their reaction parameters are still unknown because experiments to determine them could not catch up with the pace of generating new enzymes. Therefore, the gap between available enzyme sequences and available reaction parameters is widening. One way to narrow this gap is to use the information about newly mutated and found enzymes to predict their reaction parameters to meet the demand of industry for screening new enzymes. This should be done as early as possible with as little information as possible because the suitability of an enzyme can be determined at early stage in such a manner without spending too many resources. Indeed,
Data Loading...
