Abstract
Cellulase is an important enzyme widely used in various industries, and now in fermentation of biomass into biofuels. Enzymatic function of cellulase is closely related to pH, temperature, substrate concentration, etc. For newly found cellulase, it would be more cost-effective to predict its optimal pH and temperature before conducting the costly experiments. In this study, we used a 20-2 feedforward backpropagation neural network to build the relationship between information obtained from primary structure of cellulase with optimal pH and temperature to predict the optimal pH and temperature in cellulases. The results show that the amino-acid distribution probability representing the primary structure of cellulase can predict both optimal pH and temperature, whereas various properties of amino acids related to the primary structure cannot do so.
Keywords: Cellulase, backpropagation, haemoglobins, HIV protease, Prediction Model, Amino-Acid Distribution, Statistics, hydrophilicity, hydrophobicity, cross-validation, jackknife test, neural network, optimal pH, tan-sigmoid, fastest algorithm
Protein & Peptide Letters
Title: Prediction of Optimal pH and Temperature of Cellulases Using Neural Network
Volume: 19 Issue: 1
Author(s): Shao-Min Yan and Guang Wu
Affiliation:
Keywords: Cellulase, backpropagation, haemoglobins, HIV protease, Prediction Model, Amino-Acid Distribution, Statistics, hydrophilicity, hydrophobicity, cross-validation, jackknife test, neural network, optimal pH, tan-sigmoid, fastest algorithm
Abstract: Cellulase is an important enzyme widely used in various industries, and now in fermentation of biomass into biofuels. Enzymatic function of cellulase is closely related to pH, temperature, substrate concentration, etc. For newly found cellulase, it would be more cost-effective to predict its optimal pH and temperature before conducting the costly experiments. In this study, we used a 20-2 feedforward backpropagation neural network to build the relationship between information obtained from primary structure of cellulase with optimal pH and temperature to predict the optimal pH and temperature in cellulases. The results show that the amino-acid distribution probability representing the primary structure of cellulase can predict both optimal pH and temperature, whereas various properties of amino acids related to the primary structure cannot do so.
Export Options
About this article
Cite this article as:
Yan Shao-Min and Wu Guang, Prediction of Optimal pH and Temperature of Cellulases Using Neural Network, Protein & Peptide Letters 2012; 19 (1) . https://dx.doi.org/10.2174/092986612798472794
DOI https://dx.doi.org/10.2174/092986612798472794 |
Print ISSN 0929-8665 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5305 |
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Recent Developments in the Synthesis and Biological Activity of Muramylpeptides
Current Medicinal Chemistry Gallic Acid Protects from Acute Multiorgan Injury Induced by Lipopolysaccharide and D-galactosamine
Current Pharmaceutical Biotechnology Multiple Lipid-lowering Treatment in Pediatric Patients with Hyperlipidemia
Medicinal Chemistry Neuroinflammation and its Modulation by Flavonoids
Endocrine, Metabolic & Immune Disorders - Drug Targets Lipoamino Acids as Major Components of Absorption Promoters in Drug Delivery
Current Topics in Medicinal Chemistry A Multicenter Study of IgE Sensitization to <i>Anisakis simplex</i> and Diet Recommendations
Endocrine, Metabolic & Immune Disorders - Drug Targets New Sides of Aldosterone Action in Cardiovascular System as Potential Targets for Therapeutic Intervention
Current Drug Targets Role of Vitamins in Human Health and Nutrition: Sources and Morbidity
Current Nutrition & Food Science Influence of Polyphenol-plasma Protein Interaction on the Antioxidant Properties of Polyphenols
Current Drug Metabolism The Phosphoinositide Signal Transduction Pathway in the Pathogenesis of Alzheimer’s Disease
Current Alzheimer Research Eicosanoids Derived From Arachidonic Acid and Their Family Prostaglandins and Cyclooxygenase in Psychiatric Disorders
Current Neuropharmacology Potential Role of IL-18 in the Immunopathogenesis of AIDS, HIVAssociated Lipodystrophy and Related Clinical Conditions
Current HIV Research Ligand-Peroxidase Conjugates for Quantification of Receptor-Mediated Transport into Cells
Combinatorial Chemistry & High Throughput Screening Response to <i>Letter to the Editor</i> by Briana and Malamitsi-Puchner: Effects of Pregnancy-induced Insulin Resistance on the Fetus and the Future Development of Metabolic Diseases in Adulthood
Current Vascular Pharmacology Exploring the Role of Gene Therapy for Neurological Disorders
Current Gene Therapy Gender and Cardiovascular Mortality in Northern and Southern European Populations
Current Pharmaceutical Design Insulin Sensitivity is Modified by a Glycogen Phosphorylase Inhibitor: Glucopyranosylidene-Spiro-Thiohydantoin in Streptozotocin-Induced Diabetic Rats
Current Topics in Medicinal Chemistry Editorial: Limited Utility of the Handgrip Test for the Diagnosis of Diabetic Cardiovascular Autonomic Neuropathy: “There’s Time Enough, But None to Spare”
Current Vascular Pharmacology Glucose Analog Inhibitors of Glycogen Phosphorylases as Potential Antidiabetic Agents: Recent Developments
Current Pharmaceutical Design 2,4-Thiazolidinediones as PTP 1B Inhibitors: A Mini Review (2012-2018)
Mini-Reviews in Medicinal Chemistry