Objective: To investigate the antioxidant, anti-a-glucosidase and pancreatic b-cell protective potential of Ensete superbum(E. superbum) seeds.Methods: A variety of in vitro assays including radical scavenging, reduci...Objective: To investigate the antioxidant, anti-a-glucosidase and pancreatic b-cell protective potential of Ensete superbum(E. superbum) seeds.Methods: A variety of in vitro assays including radical scavenging, reducing power potential, phenolic content determination, a-glucosidase assay and pancreatic b-cell(1.4E7 cells) viability were employed for assessing the effect of methanolic extract of E. superbum seeds.Results: The radical scavenging and reducing power effects comparable with the standard rutin were obtained while the enzyme inhibitory activity of the extract was 68-fold better than the standard antidiabetic drug, acarbose. The seed extract of E. superbum was packed-full of polyphenols with mean percentage gallic acid equivalent value of(38.2 ± 1.8)(n = 3). The protection of pancreatic cells from massive onslaught of hydrogen peroxide was far superior to that obtained for rutin.Conclusions: The reputed antidiabetic therapeutic uses of the seeds extract of E. superbum may be justified on the basis of inhibition of carbohydrate enzymes, antioxidant effects and pancreatic b-cell protection.展开更多
The working conditions for enzymatic reaction are elegant, but not many optimal conditions are documented in literatures. For newly mutated and newly found enzymes, the optimal working conditions can only be extrapola...The working conditions for enzymatic reaction are elegant, but not many optimal conditions are documented in literatures. For newly mutated and newly found enzymes, the optimal working conditions can only be extrapolated from our previous experience. Therefore a question raised here is whether we can use the knowledge on enzyme structure to predict the optimal working conditions. Although working conditions for enzymes can be easily measured in experiments, the predictions of working conditions for enzymes are still important because they can minimize the experimental cost and time. In this study, we develop a 20-1 feedforward backpropagation neural network with information on amino acid sequence to predict the pH optimum for the activity of beta-glucosidase, because this enzyme has drawn much attention for its role in bio-fuel industries. Among 25 features of amino acids being screened, the results show that 11 features can be used as predictors in this model and the amino-acid distribution probability is the best in predicting the pH optimum for the activity of beta-glucosidases. Our study paves the way for predicting the optimal working conditions of enzymes based on the amino-acid features.展开更多
This is the continuation of our studies on beta-glucosidase, which plays an important role in biological processes and recently strong interests focus on their potential role in biofeul production. In order to develop...This is the continuation of our studies on beta-glucosidase, which plays an important role in biological processes and recently strong interests focus on their potential role in biofeul production. In order to develop simple methods to predict the optimal working condition for beta-glucosidase, we used a 20-1 feedforward backpropagation neural network to screen possible predictors to predict the temperature optimum of beta-glucosidase from 25 amino-acid properties related to the primary structure of beta-glucosidases. The results show that the normalized polarizability index and amino-acid distribution probability can predict the temperature optimum of beta-glucosidase, which highlights a cost-effective way to predict various enzymatic parameters of beta-glucosidase.展开更多
基金Supported by a local grant from the University of Greenwich(GRE Mini-Proof-of-Concept No.HEIF-Po C-SCI-02/13)
文摘Objective: To investigate the antioxidant, anti-a-glucosidase and pancreatic b-cell protective potential of Ensete superbum(E. superbum) seeds.Methods: A variety of in vitro assays including radical scavenging, reducing power potential, phenolic content determination, a-glucosidase assay and pancreatic b-cell(1.4E7 cells) viability were employed for assessing the effect of methanolic extract of E. superbum seeds.Results: The radical scavenging and reducing power effects comparable with the standard rutin were obtained while the enzyme inhibitory activity of the extract was 68-fold better than the standard antidiabetic drug, acarbose. The seed extract of E. superbum was packed-full of polyphenols with mean percentage gallic acid equivalent value of(38.2 ± 1.8)(n = 3). The protection of pancreatic cells from massive onslaught of hydrogen peroxide was far superior to that obtained for rutin.Conclusions: The reputed antidiabetic therapeutic uses of the seeds extract of E. superbum may be justified on the basis of inhibition of carbohydrate enzymes, antioxidant effects and pancreatic b-cell protection.
文摘The working conditions for enzymatic reaction are elegant, but not many optimal conditions are documented in literatures. For newly mutated and newly found enzymes, the optimal working conditions can only be extrapolated from our previous experience. Therefore a question raised here is whether we can use the knowledge on enzyme structure to predict the optimal working conditions. Although working conditions for enzymes can be easily measured in experiments, the predictions of working conditions for enzymes are still important because they can minimize the experimental cost and time. In this study, we develop a 20-1 feedforward backpropagation neural network with information on amino acid sequence to predict the pH optimum for the activity of beta-glucosidase, because this enzyme has drawn much attention for its role in bio-fuel industries. Among 25 features of amino acids being screened, the results show that 11 features can be used as predictors in this model and the amino-acid distribution probability is the best in predicting the pH optimum for the activity of beta-glucosidases. Our study paves the way for predicting the optimal working conditions of enzymes based on the amino-acid features.
文摘This is the continuation of our studies on beta-glucosidase, which plays an important role in biological processes and recently strong interests focus on their potential role in biofeul production. In order to develop simple methods to predict the optimal working condition for beta-glucosidase, we used a 20-1 feedforward backpropagation neural network to screen possible predictors to predict the temperature optimum of beta-glucosidase from 25 amino-acid properties related to the primary structure of beta-glucosidases. The results show that the normalized polarizability index and amino-acid distribution probability can predict the temperature optimum of beta-glucosidase, which highlights a cost-effective way to predict various enzymatic parameters of beta-glucosidase.
基金supported by Guangxi Academy of Sciences(08YJ6SW06)Guangxi Science Foundation(0907016,0991013,0991006Z,1004606,1103111,2010GXNSFF013003 and 2010GXNSFA013046)
