Chemical Theory and Multiscale Simulation in Biomolecules
From Principles to Case Studies
- 1st Edition - March 28, 2024
- Author: Guohui Li
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 5 9 1 7 - 9
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 9 1 8 - 6
Chemical Theory and Multiscale Simulation in Biomolecules: From Principles to Case Studies helps readers understand what simulation is, what information modeling of biomolecu… Read more
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Request a sales quoteChemical Theory and Multiscale Simulation in Biomolecules: From Principles to Case Studies helps readers understand what simulation is, what information modeling of biomolecules can provide, and how to compare this information with experiments. Beginning with an introduction to computational theory for modeling, the book goes on to describe how to control the conditions of modeling systems and possible strategies for time-cost savings in computation. Part Two further outlines key methods, with step-by-step guidance supporting readers in studying and practicing simulation processes. Part Three then shows how these theories are controlled and applied in practice, through examples and case studies on varied applications.
This book is a practical guide for new learners, supporting them in learning and applying molecular modeling in practice, whilst also providing more experienced readers with the knowledge needed to gain a deep understanding of the theoretical background behind key methods.
- Presents computational theory alongside case studies to help readers understand the use of simulation in practice
- Includes extensive examples of different types of simulation methods and approaches to result analysis
- Provides an overview of the current academic frontier and research challenges, encouraging creativity and directing attention to current problems
- Cover image
- Title page
- Table of Contents
- Copyright
- About the author
- Preface
- Acknowledgments
- Chapter 1. Introduction to biomolecular simulations
- Abstract
- 1.1 Introduction
- References
- Section 1: Basic knowledge
- Chapter 2. Molecular mechanics and force field
- Abstract
- 2.1 Introduction
- 2.2 All-atom model
- 2.3 Polarizable model
- 2.4 Coarse-grained model
- 2.5 Summary
- References
- Chapter 3. Quantum chemistry theory
- Abstract
- 3.1 Quantum chemistry theory
- 3.2 Conclusion
- References
- Chapter 4. Machine learning
- Abstract
- 4.1 Artificial neural network
- 4.2 Cluster analysis
- 4.3 Classification
- 4.4 Dimensionality reduction
- References
- Section 2: Methods and approaches
- Chapter 5. Monte Carlo and molecular dynamics
- Abstract
- 5.1 Monte Carlo and molecular dynamics
- Chapter 6. Control and adjustment of simulation conditions
- Abstract
- 6.1 Solvent
- 6.2 Boundary conditions
- 6.3 Restraints and constraints
- 6.4 Temperature and pressure
- References
- Chapter 7. Multiscale model
- Abstract
- 7.1 Multiscale model 张跃斌 >15页
- Chapter 8. Enhanced sampling
- Abstract
- 8.1 Introduction
- 8.2 Collective variables-based enhanced sampling
- 8.3 Collective variables free enhanced sampling
- 8.4 Combination of enhanced sampling methods
- 8.5 Programs and packages
- 8.6 Summary and outlook
- Notes
- References
- Chapter 9. Software and hardware
- Abstract
- 9.1 QM software
- 9.2 Software for molecular dynamics simulations
- 9.3 CPU, GPU, FPGA, and ASIC
- References
- Section 3: Applications and case studies
- Chapter 10. Protein folding
- Abstract
- 10.1 Introduction
- 10.2 Preparing for an IaMD simulation
- 10.3 Reweighting and free energy calculation
- 10.4 Protein folding simulation
- 10.5 Summary
- Notes
- References
- Chapter 11. RNA folding and structure prediction
- Abstract
- 11.1 Introduction
- 11.2 Case study: RNA folding simulation based on AIMS_RNA_B3 model
- 11.3 Data folder
- 11.4 Trajectory converter
- 11.5 Cluster analysis
- 11.6 Packed all-atom nonbonding parameters
- 11.7 Fitting van der Waals parameters
- 11.8 Fitting electrostatic parameters
- 11.9 Generate coarse-grained topology
- 11.10 Fitting bond parameters (bond length, angle, and dihedral)
- 11.11 Cluster analyses
- 11.12 Summary
- References
- Chapter 12. Enzyme catalysis
- Abstract
- 12.1 Background
- 12.2 Modeling details
- 12.3 Results and discussion
- 12.4 Conclusion
- References
- Chapter 13. Post-translational modification of proteins
- Abstract
- 13.1 Preparation of simulation system
- 13.2 Molecular dynamics simulations
- 13.3 Trajectories analysis
- References
- Chapter 14. Regulation of small molecule on proteins
- Abstract
- 14.1 Introduction
- 14.2 The analysis of molecular dynamics simulation
- 14.3 Examples of regulation of small molecules on proteins
- References
- Chapter 15. Recognition of protein with nucleic acid
- Abstract
- 15.1 Preparation of simulation system
- 15.2 Molecular dynamics simulations
- 15.3 Trajectories analysis
- References
- Chapter 16. Dynamics and functions of membrane proteins
- Abstract
- 16.1 Introduction
- 16.2 Methodology and analysis
- 16.3 Electric potential calculation in membrane systems
- 16.4 Ion transport and conduction
- 16.5 PMF calculations of GIRK2 in different complex states
- 16.6 Maximum conductance estimation from umbrella sampling
- 16.7 Global functional motions of GIRK2
- Appendix
- References
- Chapter 17. Assembly and functions of complex of multiple components
- Abstract
- 17.1 Preparing Alphafold2 and AF2Complex environment
- 17.2 The assembly of the entire NDH-1L complex using AF2Complex
- 17.3 The assembly of the homotrimer of cyanobacterial photosystem I using AF2Complex
- References
- Chapter 18. Protein small molecule design
- 18.1 Setup scaffold library
- 18.2 Software required
- 18.3 Calculations
- 18.4 Conclusions
- Section 4: Future directions and perspectives
- Chapter 19. Molecule scale
- Abstract
- References
- Chapter 20. System scale
- Abstract
- 20.1 Physical aspect
- 20.2 Time-scale aspect
- 20.3 Development and future
- References
- Index
- No. of pages: 398
- Language: English
- Edition: 1
- Published: March 28, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780323959179
- eBook ISBN: 9780323959186
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