دانلود کتاب Protein Folding Dynamics and Stability: Experimental and Computational Methods

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Preface
Contents
About the Editors
Applications of Circular Dichroism Spectroscopy in Studying Protein Folding, Stability, and Interaction
1 Introduction
2 Determination of Secondary and Tertiary Structures of Proteins Using CD Spectroscopy
2.1 Servers to Estimate the Secondary Structure of Proteins from CD Data
2.1.1 DichroWeb
2.1.2 BeStSel
2.1.3 K2D3
3 Determination of Conformational Changes in the Protein Using CD Spectroscopy
4 Analyzing the Conformational Changes in a Polypeptide Sequence upon Mutations Using CD
5 Analysis of Protein-Ligand Interactions
6 Determination of Protein Folding Pathways
7 Determination of Protein Stability
7.1 Thermal Denaturation
7.2 Chemical Denaturation
8 Time-Resolved CD Measurements
9 Concluding Remarks
References
Fluorescence Spectroscopy-Based Methods to Study Protein Folding Dynamics
1 Introduction
2 Fluorescence Spectroscopy to Study the Kinetics of Protein Folding Dynamics
2.1 Fluorescence Principle
2.2 Fluorescence Instrumentation
2.3 Fluorescence Measurement Using Intrinsic Fluorophores
2.4 Fluorescence Measurement Using Extrinsic Fluorophores
2.4.1 Steady-State Fluorescence
2.4.2 Steady-State Fluorescence Anisotropy
2.4.3 Time-Resolved Fluorescence
2.4.4 Fluorescence Correlation Spectroscopy
3 Conclusions
References
Applications of Differential Scanning Calorimetry in Studying Folding and Stability of Proteins
1 Introduction
2 Theory and Governing Equations
3 Instrumentation
3.1 Types of DSC Instruments
3.1.1 Heat-Compensated DSC
3.1.2 Power-Compensated DSC
3.1.3 Nano-Calorimeter or Flash DSC
3.1.4 Temperature-Modulated DSC
3.2 Method and Sample Preparation for DSC
4 Current Approaches to Studying Protein Folding and Stability
5 DSC as a Tool to Study the Protein Folding
5.1 Folding of PBX DB (Pre-B-Cell Leukaemia Transcription Factor Homeodomain)
5.2 Folding of Tetratricopeptide Repeats
5.3 Folding Mechanism of the Bovine Pancreatic Trypsin Inhibitor
5.4 Studying Protein Aggregation
5.5 Fast Folding Proteins
5.6 DSC as a Tool to Measure Barrier Heights in Protein Folding
6 DSC as a Tool to Determine Protein Stability
6.1 Advantages of DSC over Other Techniques in Studying Thermal Denaturation
6.2 DSC to Determine the Stability of Coacervation: Lysozyme and Heparin
6.3 Structural Transitions in Recombinant Human IFNα2a as a Function of pH and Temperature
6.4 Analysing Thermal Stability of Therapeutic Monoclonal Antibodies Using DSC
6.5 Effects of Electrostatic Repulsions on the Stability and Aggregation of the NIST Monoclonal Antibody
7 Conclusions
References
Nuclear Magnetic Resonance Spectroscopy to Analyse Protein Folding and Dynamics
1 Introduction
2 Studies of Protein Folding and Unfolding at Equilibrium
2.1 Folding and Unfolding Studies by 1D NMR
2.2 Folding and Unfolding Studies by 2D NMR
2.3 Measurement of Residue-Wise Stability by Hydrogen Exchange (HX) Experiments
2.4 Equilibrium HX Experiments
2.5 Relaxation Dispersion Experiments
3 Studies of Protein Folding-Unfolding Kinetics
3.1 Protein Folding Studies by Fast 2D NMR Experiments
3.2 Protein Folding by Real-Time NMR Spectroscopy
3.3 Determination of Folding Pathways by HX Labelling Experiments
4 Monitoring Protein Folding in Live Cells
5 Conclusions
References
Molecular Dynamics Simulation Methods to Study Structural Dynamics of Proteins
1 Introduction
2 Statistical Mechanics
3 Classical Mechanics
3.1 Newton´s Second Law of Motion
3.2 Integration Algorithms
3.2.1 Verlet Algorithm
3.2.2 The Leap-Frog Algorithm
3.2.3 The Velocity Verlet Algorithm
3.2.4 Beeman´s Algorithm
4 Principle of MD Simulation
4.1 Periodic Boundary Condition
4.2 Ewald Summation
4.3 Particle Mesh Ewald (PME) Method
4.4 Thermostat in MD
4.5 Solvent Models
4.6 Energy Minimization
5 Current Tools for Molecular Dynamics
5.1 Gromacs
5.2 Amber
5.3 CHARMM
5.4 NAMD
5.5 HyperChem
6 GUI-Based Software for MD Trajectories Analysis
6.1 Visual Molecular Dynamics (VMD)
6.2 PyMOL
6.3 Chimera
7 Other Advanced MD Simulation Methods
7.1 Metadynamics
7.2 Umbrella Sampling
8 Structural Parameters to Analyse MD Simulation Data
8.1 Root Mean Square Deviation (RMSD)
8.2 Root Mean Square Fluctuation (RMSF)
8.3 Radius of Gyration (Rg)
8.4 Solvent Accessible Surface Area (SASA)
8.5 Hydrogen Bonds
9 Summary
References
Molecular Dynamics Simulation to Study Protein Conformation and Ligand Interaction
1 Introduction
2 Background of MD Simulation
2.1 Theory Behind MD Simulation
3 Steps in MD Simulation
3.1 Initialization
3.2 Periodic Boundary Conditions
3.3 Energy Minimization
3.3.1 First-Derivative Techniques
3.3.2 Second-Derivative Techniques
3.4 Thermostats and Barostats
3.5 Production Stage
3.6 Analysis of the MD Data
4 Ligand Binding and Fold Transitions
5 Case Studies
6 Conclusions
References
Monte Carlo Approaches to Study Protein Conformation Ensembles
1 Introduction
2 Monte Carlo Simulations
2.1 Lagrangian and Hamiltonian Dynamics (or How to Formulate the Problem)
2.2 Partition Functions, Probability Density Functions, and Expectation (or How to Compute Observables)
2.3 How to Sample Efficiently Thermodynamical Quantities
2.4 Canonical Ensemble (NVT) Sampling (or How to Sample in Realistic Experimental Conditions)
2.5 Isobaric-Isothermal Ensemble (NPT) Sampling (or How to Sample in Even More Realistic Experimental Conditions)
2.6 Sampling and Local Minima (or When Temperature May Help to Escape Local Minima)
3 Advantages and Limitations of MC Simulations
3.1 Advantages
3.2 Limitations
4 Case Study of the MC Simulations of a Trp-Cage Protein
5 Conclusions
References
Markov State Models of Molecular Simulations to Study Protein Folding and Dynamics
1 Introduction
1.1 Importance of Molecular Dynamics
1.2 Motivation Behind Using MSM Technique
2 Markov State Model
2.1 Building of MSM
2.2 Microstates and Macrostates Generation
2.3 MSM Model and Validation
3 MSM to Understand Protein Folding and Dynamics
3.1 Peptide Modeling
3.2 Protein Folding
3.3 Protein-Ligand Binding
3.4 Analyzing Intrinsically Disordered Proteins
3.5 Native State Conformation Changes
4 Summary
References
Enhanced Sampling and Free Energy Methods to Study Protein Folding and Dynamics
1 Introduction
2 Protein Folding and Dynamics
3 Free Energy and Sampling Methods
3.1 Collective Variables and Free Energy
4 Collective Variable-Based Sampling
4.1 Umbrella Sampling
4.2 Metadynamics
5 Collective Variable-Free Sampling
5.1 Replica Exchange Molecular Dynamics
5.2 Accelerated Molecular Dynamics
6 Conclusion and Outlook
References
Investigating Protein Unfolding and Stability Using Chaotropic Agents and Molecular Dynamics Simulation
1 Introduction
2 Basic Concept of Protein Folding
3 Chaotropic Agents and Their Mechanism of Action
4 Molecular Dynamics (MD) Simulation
5 Application of MD Simulation in Investigating Protein Unfolding
6 Case Studies
6.1 Urea-Induced Unfolding
6.2 GdnHCl-Induced Unfolding
7 Conclusions
References
pH-Based Molecular Dynamics Simulation for Analysing Protein Structure and Folding
1 Introduction
2 Protein Folding and the Intermediate States
3 Effect of pH on Amino Acids
4 Simulating Proteins at Multiple pHs
5 Case Study of Leishmania donovani Tyrosine Aminotransferase (LdTAT) Enzyme
5.1 Root Mean Square Deviation
5.2 Radius of Gyration
5.3 Solvent Accessible Surface Area
5.4 Root Mean Square Fluctuation
5.5 Secondary Structure Analysis
5.6 Intramolecular Hydrogen Bonding and Internal Energy Analysis
5.7 Principal Component Analysis
6 Other Case Studies
7 Conclusions and Future Perspectives
References
Molecular Dynamics Simulation to Study Thermal Unfolding in Proteins
1 Introduction
2 Effect of Temperature on Protein Structure
3 Temperature-Induced Protein Unfolding
4 MD Simulation to Understand Protein Denaturation
4.1 Force Field in MD Simulations
4.2 Strong Coupling Methods
4.2.1 Velocity Rescaling
4.2.2 Velocity Reassignment
4.3 Weak Coupling Methods
4.3.1 Berendsen Thermostat
4.4 Stochastic Methods
4.4.1 Andersen Thermostat
4.4.2 Lowe-Andersen Thermostat
4.4.3 Bussi´s Stochastic Velocity Rescaling Thermostat
4.4.4 Langevin Thermostat
4.5 Extended System Dynamics
4.5.1 Nosé-Hoover Thermostat
4.5.2 Nosé-Hoover-Chains
4.6 Analysis of MD Simulation Trajectories
4.7 Root Mean Square Deviation
4.8 Root Mean Square Fluctuation
4.9 Hydrogen Bonding Analysis
4.10 Dihedral Angle Analysis
4.11 Radius of Gyration
4.12 Protein Solvent Accessible Surface Area
4.13 Principal Component Analysis
4.14 Free Energy Landscape Analysis
4.15 Dynamic Cross-Correlation Matrix
4.16 Loss of Secondary Structures in High Temperatures
4.17 Analysing the Unfolding of Human Prion Protein Under Low pH and High-Temperature Conditions
5 Applications of MD Simulation in Understanding Biological Problems
6 Conclusion and Future Prospects
References
Principles, Methods, and Applications of Protein Folding Inside Cells
1 Introduction
2 Protein Folding in Cells
3 Cellular Factors That Facilitate Protein Folding in Cells
3.1 Macromolecular Crowding and Compartmentalization
3.2 Inter- and Intramolecular Interactions in Proteins
3.3 Post-Translational Modifications
3.4 Chaperones
3.4.1 Hsp70 Chaperone
3.4.2 Chaperonins
3.4.3 Hsp90 Chaperone
3.5 Solution Properties
4 Protein Misfolding Diseases
5 Biophysical Methods to Study Protein Folding in Cells
5.1 In-Cell NMR Spectroscopy
5.2 In-Cell FRET
5.3 Fast Relaxation Imaging (FREI)
5.4 FlAsH as an In-Cell Protein Folding Probe
6 Applications of Protein Folding in Cells
6.1 De Novo Protein Design
6.2 Drug Design
6.2.1 For Cancer
6.2.2 For Human Immunodeficiency Virus
6.2.3 For Alzheimer´s Disease
7 Conclusions
References