Modeling Solvent Environments Applications to Simulations of Biomolecules 1st Edition by Michael Feig – Ebook PDF Instant Download/Delivery: 978-3527324217, 3527324216
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Product details:
ISBN 10: 3527324216
ISBN 13: 978-3527324217
Author: Michael Feig
A comprehensive view of the current methods for modeling solvent environments with contributions from the leading researchers in the field. Throughout, the emphasis is placed on the application of such models in simulation studies of biological processes, although the coverage is sufficiently broad to extend to other systems as well. As such, this monograph treats a full range of topics, from statistical mechanics-based approaches to popular mean field formalisms, coarse-grained solvent models, more established explicit, fully atomic solvent models, and recent advances in applying ab initio methods for modeling solvent properties.
Table of contents:
Biomolecular Solvation in Theory and Experiment
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Introduction
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Theoretical Views of Solvation
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Computer Simulation Methods in the Study of Solvation
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Experimental Methods in the Study of Solvation
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Hydration of Proteins
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Hydration of Nucleic Acids
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Non-Aqueous Solvation
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Summary
Model-Free “Solvent Modeling” in Chemistry and Biochemistry Based on the Statistical Mechanics of Liquids
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Introduction
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Outline of the RISM and 3D-RISM Theories
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Partial Molar Volume of Proteins
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Detecting Water Molecules Trapped Inside Protein
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Selective Ion Binding by Protein
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Water Molecules Identified as a Substrate for Enzymatic Hydrolysis of Cellulose
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CO Escape Pathway in Myoglobin
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Perspective
Developing Force Fields from the Microscopic Structure of Solutions: The Kirkwood-Buff Approach
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Introduction
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Biomolecular Force Fields
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Examples of Problems with Current Force Fields
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Kirkwood-Buff Theory
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Applications of Kirkwood-Buff Theory
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The General KBFF Approach
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Technical Aspects of the KBFF Approach
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Results for Urea and Water Binary Solutions
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Preferential Interactions of Urea
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Conclusions and Future Directions
Osmolyte Influence on Protein Stability: Perspectives of Theory and Experiment
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Introduction
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Denaturing Osmolytes
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Protecting Osmolytes
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Mixed Osmolytes
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Conclusions
Modeling Aqueous Solvent Effects through Local Properties of Water
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The Role of Water and Cosolutes on Macromolecular Thermodynamics
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Forces Induced by Water in Aqueous Solutions
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Continuum Representation of Water
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Modeling Water Effects on Proteins and Nucleic Acids
Continuum Electrostatics Solvent Modeling with the Generalized Born Model
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Introduction: The Implicit Solvent Framework
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The Generalized Born Model
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Applications of the GB Model
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Some Practical Considerations
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Limitations of the GB Model
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Conclusions and Outlook
Implicit Solvent Force-Field Optimization
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Introduction
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Theoretical Foundations of Implicit Solvent
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Optimization of Implicit Solvent Force Fields
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Concluding Remarks and Outlook
Modeling Protein Solubility in Implicit Solvent
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Introduction
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The Models
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Applications
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Summary and Outlook
Fast Analytical Continuum Treatments of Solvation
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Introduction
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The SASA Implicit Solvent Model: A Fast Surface Area Model
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The FACTS Implicit Solvent Model: A Fast Generalized Born Approach
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Conclusions
On the Development of State-Specific Coarse-Grained Potentials of Water
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Introduction
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Methods of Computing Coarse-Grained Potentials of Liquid Water
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Structural Properties and the “Representability” Problem of Coarse-Grained Liquid Water Models
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Conclusions
Molecular Dynamics Simulations of Biomolecules in a Polarizable Coarse-Grained Solvent
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Introduction
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Theory
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Applications: Solvation of All-Atom Models of Biomolecules
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Conclusions and Prospects
Modeling Electrostatic Polarization in Biological Solvents
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Introduction
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Current Approaches for Modeling Electrostatic Polarization in Classical Force Fields
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Parameterization of Charge Equilibration Models
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Applications of Charge Equilibration Models for Biological Solvents
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Toward Modeling of Membrane Ion Channel Systems: Molecular Dynamics Simulations of DMPC-Water and DPPC-Water Bilayer Systems
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Conclusions and Future Directions
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Tags: Michael Feig, Modeling Solvent Environments, Applications to Simulations


