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Ebook: RNA 3D Structure Analysis and Prediction

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With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.




With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.




With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.


Content:
Front Matter....Pages i-x
Introduction....Pages 1-3
Modeling RNA Molecules....Pages 5-17
Methods for Predicting RNA Secondary Structure....Pages 19-41
Why Can’t We Predict RNA Structure At Atomic Resolution?....Pages 43-65
Template-Based and Template-Free Modeling of RNA 3D Structure: Inspirations from Protein Structure Modeling....Pages 67-90
The RNA Folding Problems: Different Levels of sRNA Structure Prediction....Pages 91-117
Computational Prediction and Modeling Aid in the Discovery of a Conformational Switch Controlling Replication and Translation in a Plus-Strand RNA Virus....Pages 119-142
Methods for Building and Refining 3D Models of RNA....Pages 143-166
Multiscale Modeling of RNA Structure and Dynamics....Pages 167-184
Statistical Mechanical Modeling of RNA Folding: From Free Energy Landscape to Tertiary Structural Prediction....Pages 185-212
Simulating Dynamics in RNA–Protein Complexes....Pages 213-238
Quantum Chemical Studies of Recurrent Interactions in RNA 3D Motifs....Pages 239-279
Nonredundant 3D Structure Datasets for RNA Knowledge Extraction and Benchmarking....Pages 281-298
Ions in Molecular Dynamics Simulations of RNA Systems....Pages 299-318
Modeling RNA Folding Pathways and Intermediates Using Time-Resolved Hydroxyl Radical Footprinting Data....Pages 319-334
A Top-Down Approach to Determining Global RNA Structures in Solution Using NMR and Small-Angle X-ray Scattering Measurements....Pages 335-359
RNA Structure Determination by Structural Probing and Mass Spectrometry: MS3D....Pages 361-389
Back Matter....Pages 391-400


With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.


Content:
Front Matter....Pages i-x
Introduction....Pages 1-3
Modeling RNA Molecules....Pages 5-17
Methods for Predicting RNA Secondary Structure....Pages 19-41
Why Can’t We Predict RNA Structure At Atomic Resolution?....Pages 43-65
Template-Based and Template-Free Modeling of RNA 3D Structure: Inspirations from Protein Structure Modeling....Pages 67-90
The RNA Folding Problems: Different Levels of sRNA Structure Prediction....Pages 91-117
Computational Prediction and Modeling Aid in the Discovery of a Conformational Switch Controlling Replication and Translation in a Plus-Strand RNA Virus....Pages 119-142
Methods for Building and Refining 3D Models of RNA....Pages 143-166
Multiscale Modeling of RNA Structure and Dynamics....Pages 167-184
Statistical Mechanical Modeling of RNA Folding: From Free Energy Landscape to Tertiary Structural Prediction....Pages 185-212
Simulating Dynamics in RNA–Protein Complexes....Pages 213-238
Quantum Chemical Studies of Recurrent Interactions in RNA 3D Motifs....Pages 239-279
Nonredundant 3D Structure Datasets for RNA Knowledge Extraction and Benchmarking....Pages 281-298
Ions in Molecular Dynamics Simulations of RNA Systems....Pages 299-318
Modeling RNA Folding Pathways and Intermediates Using Time-Resolved Hydroxyl Radical Footprinting Data....Pages 319-334
A Top-Down Approach to Determining Global RNA Structures in Solution Using NMR and Small-Angle X-ray Scattering Measurements....Pages 335-359
RNA Structure Determination by Structural Probing and Mass Spectrometry: MS3D....Pages 361-389
Back Matter....Pages 391-400
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