Chemical 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.
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Table of Contents
1. Introduction
Part I Basic knowledge2. Molecular Mechanics and force field3. Quantum Chemistry Theory4. Machine Learning
Part II Methods and Approaches5. Monte Carlo and Molecular Dynamics6. Control and adjustment of simulation conditions7. Multiscale Model8. Enhanced sampling9. Software and Hardware
Part III Applications and case studies10. Protein folding and structure prediction11. RNA folding and structure prediction12. Enzyme catalysis13. Post-translational modification of proteins14. Regulation of small molecule on proteins15. Recognition of protein with nucleic acid16. Dynamics and functions of membrane proteins17. Assembly and functions of multiple components complex18. Protein and small molecule design
Part IV Future directions and perspectives
