Predicting Km values of beta-glucosidases using cellobiose as substrate.
作者： Shao-Min Yan , De-Qiang Shi , Hao Nong , Guang Wu
DOI: 10.1007/S12539-012-0115-Z
关键词: Substrate (chemistry) 、 Biological system 、 Cellulose metabolism 、 Chemistry 、 Economic shortage 、 Cellulose hydrolysis 、 Stereochemistry 、 Enzyme catalysis 、 Feedforward backpropagation neural network 、 Beta-glucosidase 、 Cellobiose
摘要: The Michaelis-Menten constant Km is a very important parameter to relate enzyme with its substrate in enzymatic reaction. Although can be experimentally determined, the values are not easily available literature. With rapid increase of newly designed enzymes, we face shortage parameters related reactions. beta-glucosidase crucial for cellulose hydrolysis and cellobiose one substrates. In this study, attempt develop models predict as substrates using information about primary structure beta-glucosidase. results show that 20-1 feedforward backpropagation neural network amino-acid distribution probability predictor works best prediction values.
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