Computational Methods for Understanding Riboswitches - 1st Edition - ISBN: 9780128014295, 9780128016183

Computational Methods for Understanding Riboswitches, Volume 553

1st Edition

Serial Volume Editors: Shi-Jie Chen Donald H. Burke-Aguero
eBook ISBN: 9780128016183
Hardcover ISBN: 9780128014295
Imprint: Academic Press
Published Date: 1st February 2015
Page Count: 422
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Table of Contents

  • List of Videos
  • Series Page
  • Preface
  • Section I: RNA Structure Prediction
  • Chapter One. Automated 3D RNA Structure Prediction Using the RNAComposer Method for Riboswitches
    • Abstract
    • 1 Introduction
    • 2 RNA FRABASE—Opening the Route to RNAComposer
    • 3 RNAComposer—From the RNA Secondary Structure to RNA 3D Structure
    • 4 Predicting the Tertiary Structure of Riboswitches with RNAComposer
    • 5 Conclusions and Perspectives
    • Acknowledgments
    • References
  • Chapter Two. Modeling Complex RNA Tertiary Folds with Rosetta
    • Abstract
    • 1 Introduction
    • 2 Setting the Stage for 3D Modeling Using Experimental Data
    • 3 Making Models of RNA Tertiary Folds
    • 4 Evaluation
    • 5 Conclusion
    • Acknowledgments
    • References
  • Chapter Three. Computational Methods Toward Accurate RNA Structure Prediction Using Coarse-Grained and All-Atom Models
    • Abstract
    • 1 Introduction
    • 2 Discrete Molecular Dynamics
    • 3 Three-Bead Model
    • 4 Use of Hydroxyl-Radical Probing to Refine RNA Three-Dimensional Structure
    • 5 All-Atom Structure Reconstruction
    • 6 iFoldRNA
    • 7 Conclusions
    • References
  • Chapter Four. Improving RNA Secondary Structure Prediction with Structure Mapping Data
    • Abstract
    • 1 Introduction
    • 2 Overview of Probing Methods
    • 3 Improving the Accuracy of Secondary Structure Prediction Using Probing Data
    • 4 Using SHAPE Data on a Single Sequence to Improve Secondary Structure Prediction Accuracy
    • 5 Open Questions
    • 6 Conclusions
    • References
  • Chapter Five. Computational Prediction of Riboswitch Tertiary Structures Including Pseudoknots by RAGTOP: A Hierarchical Graph Sampling Approach
    • Abstract
    • 1 Introduction
    • 2 Hierarchical Graph Folding Approach
    • 3 Application to Riboswitch Structure Prediction
    • 4 Future Challenges and Perspectives
    • Acknowledgments
    • References
  • Section II: RNA Dynamics and Thermodynamics
  • Chapter Six. Using Reweighted Pulling Simulations to Characterize Conformational Changes in Riboswitches
    • Abstract
    • 1 Introduction
    • 2 Methods and Theory
    • 3 Results and Discussion
    • 4 Conclusions
    • Acknowledgments
    • References
  • Chapter Seven. Force Field Dependence of Riboswitch Dynamics
    • Abstract
    • 1 Introduction
    • 2 Methods
    • 3 Results and Discussion
    • Acknowledgments
    • References
  • Chapter Eight. Thermodynamic and Kinetic Folding of Riboswitches
    • Abstract
    • 1 Introduction
    • 2 Characterization and Prediction of Riboswitches
    • 3 Thermodynamic RNA folding
    • 4 RNA Folding Kinetics on Static Landscapes
    • 5 RNA Folding Kinetics on Dynamic Landscapes
    • 6 Conclusion
    • Acknowledgments
    • References
  • Chapter Nine. Integrating Molecular Dynamics Simulations with Chemical Probing Experiments Using SHAPE-FIT
    • Abstract
    • 1 Introduction
    • 2 Materials and Methods
    • 3 Results
    • 4 Discussions
    • Acknowledgments
    • References
  • Chapter Ten. Using Simulations and Kinetic Network Models to Reveal the Dynamics and Functions of Riboswitches
    • Abstract
    • 1 Introduction and Scope of the Review
    • 2 Hydration Dynamics Around the Folded State: All Atom Simulations
    • 3 Stability of Isolated Helices Control the Folding Landscapes of Purine Riboswitches
    • 4 Folding Landscapes of SAM Riboswitch
    • 5 Is SAM Riboswitch Under Thermodynamic Control?
    • 6 Kinetic Network Model of Gene Regulation and the Role of Negative Feedback in Control of Transcription
    • 7 Concluding Remarks
    • Acknowledgments
    • References
  • Section III: Ions, Ligands, and RNA Interactions
  • Chapter Eleven. Computational Methods for Prediction of RNA Interactions with Metal Ions and Small Organic Ligands
    • Abstract
    • 1 Introduction
    • 2 Computational Modeling of RNA–Ligand Complex Structures
    • 3 MetalionRNA and LigandRNA
    • Acknowledgments
    • References
  • Chapter Twelve. Computational Prediction of Riboswitches
    • Abstract
    • 1 Introduction
    • 2 Riboswitches
    • 3 Riboswitch gene finders
    • 4 Conformational switches
    • 5 Conclusion
    • 6 Acknowledgments
    • References
  • Chapter Thirteen. Computational and Experimental Studies of Reassociating RNA/DNA Hybrids Containing Split Functionalities
    • Abstract
    • 1 Introduction
    • 2 Thermodynamic Prediction of Different Compositions of RNA and DNA Strand Associations
    • 3 Sequence Design of RNA/DNA Hybrids
    • 4 Enzyme-Assisted In Vitro Production of RNA/DNA Hybrids
    • 5 Experimental Testing of RNA/DNA Hybrids
    • 6 Concluding Remarks
    • Acknowledgments
    • References
  • Chapter Fourteen. Multiscale Methods for Computational RNA Enzymology
    • Abstract
    • 1 Introduction
    • 2 The “Problem Space” of Computational RNA Enzymology
    • 3 Multiscale Modeling Strategy
    • 4 Catalytic Strategies for Cleavage of the RNA Backbone
    • 5 Modeling Ion and Nucleic Acid Interactions
    • 6 Modeling pH-Rate Profiles for Enzymes
    • 7 Modeling Conformational States
    • 8 Modeling the Chemical Steps of Catalysis
    • 9 Computing KIEs to Verify Transition State Structure
    • 10 Conclusions
    • Acknowledgments
    • References
  • Author Index
  • Subject Index
  • Color Plate

Description

This new volume of Methods in Enzymology continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers computational prediction RNA structure and dynamics, including such topics as computational modeling of RNA secondary and tertiary structures, riboswitch dynamics, and ion-RNA, ligand-RNA and DNA-RNA interactions.

Key Features

  • Continues the legacy of this premier serial with quality chapters authored by leaders in the field
  • Covers computational methods and applications in RNA structure and dynamics
  • Contains chapters with emerging topics such as RNA structure prediction, riboswitch dynamics and thermodynamics, and effects of ions and ligands.

Readership

Biochemists, biophysicists, molecular biologists, analytical chemists, and physiologists.


Details

No. of pages:
422
Language:
English
Copyright:
© Academic Press 2015
Published:
Imprint:
Academic Press
eBook ISBN:
9780128016183
Hardcover ISBN:
9780128014295

Reviews

Praise for the Series:
"Should be on the shelves of all libraries in the world as a whole collection." --Chemistry in Industry
"The work most often consulted in the lab." --Enzymologia
"The Methods in Enzymology series represents the gold-standard." --Neuroscience


About the Serial Volume Editors

Shi-Jie Chen Serial Volume Editor

Shi-Jie Chen is Professor of the Department of Physics Astronomy and Department of Biochemistry and is core faculty member in the Informatics Institute at the University of Missouri-Columbia. Dr. Chen received his Ph.D. in Physics from the University of California, San Diego in 1994. He was a postdoctoral researcher at the University of California, San Francisco in 1994-9 and began his faculty appointment at the University of Missouri-Columbia in 1999. Chen has served the scientific community by his participation on multiple NIH review panels and site visit reviewer teams. He served as Associate Editor of the PLoS Computational Biology. His laboratory developed Vfold and TBI, open source and freely available web servers and software for the computational predictions of RNA structure, folding thermodynamics, and ion effects. Dr. Chen was elected to the fellow of American Physical Society in 2012.

Affiliations and Expertise

Biophysics, Biochemistry and Informatics, University of Missouri-Columbia, USA

Donald H. Burke-Aguero Serial Volume Editor

Affiliations and Expertise

Department of Molecular Microbiology & Immunology and Department of Biochemistry, University of Missouri, USA