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Reviews in Computational Chemistry, Volume 28

ISBN: 978-1-118-40777-6
560 pages
April 2015
Reviews in Computational Chemistry, Volume 28 (1118407776) cover image

Description

The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered around molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 28 include:

  • Free-energy Calculations with Metadynamics
  • Polarizable Force Fields for Biomolecular Modeling
  • Modeling Protein Folding Pathways
  • Assessing Structural Predictions of Protein-Protein Recognition
  • Kinetic Monte Carlo Simulation of Electrochemical Systems
  • Reactivity and Dynamics at Liquid Interfaces
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Table of Contents

Preface xi

List of Contributors xv

Contributors to Previous Volumes xvii

1. Free-Energy Calculations with Metadynamics: Theory and Practice 1
Giovanni Bussi and Davide Branduardi

Introduction 1

Molecular Dynamics and Free-Energy Estimation 3

Molecular Dynamics 3

Free-Energy Landscapes 4

A Toy Model: Alanine Dipeptide 6

Biased Sampling 8

Adaptive Biasing with Metadynamics 9

Reweighting 12

Well-Tempered Metadynamics 12

Reweighting 14

Metadynamics How-To 14

The Choice of the CV(s) 15

The Width of the Deposited Gaussian Potential 17

The Deposition Rate of the Gaussian Potential 18

A First Test Run Using Gyration Radius 19

A Better Collective Variable: Φ Dihedral Angle 23

Well-Tempered Metadynamics Using Gyration Radius 24

Well-Tempered Metadynamics Using Dihedral Angle Φ 27

Advanced Collective Variables 28

Path-Based Collective Variables 30

Collective Variables Based on Dimensional Reduction Methods 32

Template-Based Collective Variables 34

Potential Energy as a Collective Variable 35

Improved Variants 36

Multiple Walkers Metadynamics 36

Replica Exchange Metadynamics 37

Bias Exchange Metadynamics 38

Adaptive Gaussians 39

Conclusion 41

Acknowledgments 42

Appendix A: Metadynamics Input Files with PLUMED 42

References 44

2. Polarizable Force Fields for Biomolecular Modeling 51
Yue Shi, Pengyu Ren, Michael Schnieders, and Jean-Philip

Piquemal

Introduction 51

Modeling Polarization Effects 52

Induced Dipole Models 52

Classic Drude Oscillators 54

Fluctuating Charges 54

Recent Developments 55

AMOEBA 55

SIBFA 57

NEMO 58

CHARMM-Drude 58

CHARMM-FQ 59

X-Pol 60

PFF 60

Applications 61

Water Simulations 61

Ion Solvation 62

Small Molecules 63

Proteins 64

Lipids 66

Continuum Solvents for Polarizable Biomolecular Solutes 66

Macromolecular X-ray Crystallography Refinement 67

Prediction of Organic Crystal Structure, Thermodynamics, and Solubility 70

Summary 71

Acknowledgment 71

References 72

3. Modeling Protein Folding Pathways 87
Clare-Louise Towse and Valerie Daggett

Introduction 87

Outline of this Chapter 90

Protein Simulation Methodology 90

Force Fields, Models and Solvation Approaches 90

Unfolding: The Reverse of Folding 97

Elevated Temperature Unfolding Simulations 100

Biological Relevance of Forced Unfolding 103

Biased or Restrained MD 108

Characterizing Different States 111

Protein Folding and Refolding 115

Folding in Families 118

Conclusions and Outlook 121

Acknowledgment 122

References 122

4. Assessing Structural Predictions of Protein–Protein Recognition: The CAPRI Experiment 137
Joël Janin, Shoshana J. Wodak, Marc F. Lensink, and Sameer Velankar

Introduction 137

Protein–Protein Docking 138

A Short History of Protein–Protein Docking 138

Major Current Algorithms 141

The CAPRI Experiment 144

Why Do Blind Predictions? 144

Organizing CAPRI 145

The CAPRI Targets 146

Creating a Community 149

Assessing Docking Predictions 150

The CAPRI Evaluation Procedure 150

A Survey of the Results of 12 Years of Blind Predictions on 45 Targets 154

Recent Developments in Modeling Protein–Protein Interaction 160

Modeling Multicomponent Assemblies. The Multiscale Approach 160

Genome-Wide Modeling of Protein–Protein Interaction 161

Engineering Interactions and Predicting Affinity 162

Conclusion 164

Acknowledgments 165

References 165

5. Kinetic Monte Carlo Simulation of Electrochemical Systems 175
C. Heath Turner, Zhongtao Zhang, Lev D. Gelb, and Brett I. Dunlap

Background 175

Introduction to Kinetic Monte Carlo 176

Electrochemical Relationships 180

Applications 184

Transport in Li-ion Batteries 184

Solid Electrolyte Interphase (SEI) Passive Layer Formation 187

Analysis of Impedance Spectra 189

Electrochemical Dealloying 189

Electrochemical Cells 190

Solid Oxide Fuel Cells 193

Other Electrochemical Systems 197

Conclusions and Future Outlook 198

Acknowledgments 199

References 199

6. Reactivity and Dynamics at Liquid Interfaces 205
Ilan Benjamin

Introduction 205

Simulation Methodology for Liquid Interfaces 207

Force Fields for Molecular Simulations of Liquid Interfaces 207

Boundary Conditions and the Treatment of Long-Range Forces 210

Statistical Ensembles for Simulating Liquid Interfaces 213

Comments About Monte Carlo Simulations 214

The Neat Interface 214

Density, Fluctuations, and Intrinsic Structure 215

Surface Tension 221

Molecular Structure 223

Dynamics 230

Solutes at Interfaces: Structure and Thermodynamics 235

Solute Density 236

Solute–Solvent Correlations 240

Solute Molecular Orientation 242

Solutes at Interfaces: Electronic Spectroscopy 243

A Brief General Background on Electronic Spectroscopy in the Condensed Phase 243

Experimental Electronic Spectroscopy at Liquid Interfaces 245

Computer Simulations of Electronic Transitions at Interfaces 249

Solutes at Interfaces: Dynamics 253

Solute Vibrational Relaxation at Liquid Interfaces 253

Solute Rotational Relaxation at Liquid Interfaces 258

Solvation Dynamics 263

Summary 269

Reactivity at Liquid Interfaces 270

Introduction 270

Electron Transfer Reactions at Liquid/Liquid Interfaces 271

Nucleophilic Substitution Reactions and Phase Transfer

Catalysis (PTC) 277

Conclusions 283

Acknowledgments 284

References 284

7. Computational Techniques in the Study of the Properties of Clathrate Hydrates 315
John S. Tse

Historical Perspective 315

Structures 317

The van der Waals–Platteeuw Solid Solution Theory 318

Computational Advancements 322

Thermodynamic Modelling 322

Atomistic Simulations 327

Thermodynamic Stability 344

Hydrate Nucleation and Growth 355

Guest Diffusion Through Hydrate Cages 368

Ab Initio Methods 371

Outlook 381

References 382

8. The Quantum Chemistry of Loosely-Bound Electrons 391
John M. Herbert

Introduction and Overview 391

What Is a Loosely-Bound Electron? 391

Scope of This Review 392

Chemical Significance of Loosely-Bound Electrons 394

Challenges for Theory 400

Terminology and Fundamental Concepts 402

Bound Anions 402

Metastable (Resonance) Anions 415

Quantum Chemistry for Weakly-Bound Anions 425

Gaussian Basis Sets 425

Wave Function Electronic Structure Methods 439

Density Functional Theory 456

Quantum Chemistry for Metastable Anions 471

Maximum Overlap Method 474

Complex Coordinate Rotation 477

Stabilization Methods 483

Concluding Remarks 495

Acknowledgments 495

Appendix A: List of Acronyms 496

References 497

Index 519

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Author Information

Abby L. Parrill, PhD, is Professor of Chemistry in the Department of Chemistry at the University of Memphis, TN. Her research interests are in bioorganic chemistry, protein modeling and NMR Spectroscopy and rational ligand design and synthesis. In 2011, she was awarded the Distinguished Research Award by University of Memphis Alumni Association. She has given more than 100 presentations, more than 100 papers and books.

Kenny B. Lipkowitz, PhD, is a recently retired Professor of Chemistry from North Dakota State University.

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