Reinhard Schweitzer-Stenner, PhD, is Professor and currently the Head of the Chemistry Department at Drexel University. Dr. Schweitzer-Stenner also heads the biospectroscopy research group. His research investigates peptide structure and functionally relevant heme distortions as well as ligand-receptor binding on the surface of mast cells. With more than 150 published research articles, Dr. Schweitzer-Stenner is widely recognized as a leader and pioneer in the study of the conformational properties of unfolded peptides.

• Introduction to the Wiley Series on Protein and Peptide Science xiii Preface xvContributors xixINTRODUCTION 11 Why Are We Interested in the Unfolded Peptides and Proteins? 3Vladimir N. Uversky and A. Keith Dunker1.1 Introduction, 31.2 Why Study IDPs?, 41.3 Lesson 1: Disorderedness Is Encoded in the Amino Acid Sequence and Can Be Predicted, 51.4 Lesson 2: Disordered Proteins Are Highly Abundant in Nature, 71.5 Lesson 3: Disordered Proteins Are Globally Heterogeneous, 91.6 Lesson 4: Hydrodynamic Dimensions of Natively Unfolded Proteins Are Charge Dependent, 141.7 Lesson 5: Polymer Physics Explains Hydrodynamic Behavior of Disordered Proteins, 161.8 Lesson 6: Natively Unfolded Proteins Are Pliable and Very Sensitive to Their Environment, 181.9 Lesson 7: When Bound, Natively Unfolded Proteins Can Gain Unusual Structures, 201.10 Lesson 8: IDPs Can Form Disordered or Fuzzy Complexes, 251.11 Lesson 9: Intrinsic Disorder Is Crucial for Recognition, Regulation, and Signaling, 251.12 Lesson 10: Protein Posttranslational Modifi cations Occur at Disordered Regions, 281.13 Lesson 11: Disordered Regions Are Primary Targets for AS, 301.14 Lesson 12: Disordered Proteins Are Tightly Regulated in the Living Cells, 311.15 Lesson 13: Natively Unfolded Proteins Are Frequently Associated with Human Diseases, 331.16 Lesson 14: Natively Unfolded Proteins Are Attractive Drug Targets, 351.17 Lesson 15: Bright Future of Fuzzy Proteins, 38Acknowledgments, 39References, 40I CONFORMATIONAL ANALYSIS OF UNFOLDED STATES 552 Exploring the Energy Landscape of Small Peptides and Proteins by Molecular Dynamics Simulations 57Gerhard Stock, Abhinav Jain, Laura Riccardi, and Phuong H. Nguyen2.1 Introduction: Free Energy Landscapes and How to Construct Them, 572.2 Dihedral Angle PCA Allows Us to Separate Internal and Global Motion, 612.3 Dimensionality of the Free Energy Landscape, 622.4 Characterization of the Free Energy Landscape: States, Barriers, and Transitions, 652.5 Low-Dimensional Simulation of Biomolecular Dynamics to Catch Slow and Rare Processes, 672.6 PCA by Parts: The Folding Pathways of Villin Headpiece, 692.7 The Energy Landscape of Aggregating Aβ-Peptides, 732.8 Concluding Remarks, 74Acknowledgments, 75References, 753 Local Backbone Preferences and Nearest-Neighbor Effects in the Unfolded and Native States 79Joe DeBartolo, Abhishek Jha, Karl F. Freed, and Tobin R. Sosnick3.1 Introduction, 793.2 Early Days: Random Coil—Theory and Experiment, 803.3 Denatured Proteins as Self-Avoiding Random Coils, 823.4 Modeling the Unfolded State, 823.5 NN Effects in Protein Structure Prediction, 863.6 Utilizing Folding Pathways for Structure Prediction, 873.7 Native State Modeling, 883.8 Secondary-Structure Propensities: Native Backbones in Unfolded Proteins, 923.9 Conclusions, 92Acknowledgments, 93References, 944 Short-Distance FRET Applied to the Polypeptide Chain 99Maik H. Jacob and Werner M. Nau4.1 A Short Timeline of Resonance Energy Transfer Applied to the Polypeptide Chain, 994.2 A Short Theory of FRET Applied to the Polypeptide Chain, 1014.3 DBO and Dbo, 1054.4 Short-Distance FRET Applied to the Structured Polypeptide Chain, 1074.5 Short-Distance FRET to Monitor Chain-Structural Transitions upon Phosphorylation, 1164.6 Short-Distance FRET Applied to the Structureless Chain, 1204.7 The Future of Short-Distance FRET, 125Acknowledgments, 125Dedication, 126References, 1265 Solvation and Electrostatics as Determinants of Local Structural Order in Unfolded Peptides and Proteins 131Franc Avbelj5.1 Local Structural Order in Unfolded Peptides and Proteins, 1315.2 ESM, 1345.3 The ESM and Strand-Coil Transition Model, 1375.4 The ESM and Backbone Conformational Preferences, 1385.5 The Nearest-Neighbor Effect, 1415.6 The ESM and Cooperative Local Structures—Fluctuating β-Strands, 1415.7 The ESM and β-Sheet Preferences in Native Proteins—Significance of Unfolded State, 1445.8 The ESM and Secondary Chemical Shifts of Polypeptides, 1455.9 Role of Backbone Solvation in Determining Hydrogen Exchange Rates of Unfolded Polypeptides, 1485.10 Other Theoretical Models of Unfolded Polypeptides, 148Acknowledgments, 149References, 1496 Experimental and Computational Studies of Polyproline II Propensity 159W. Austin Elam, Travis P. Schrank, and Vincent J. Hilser6.1 Introduction, 1596.2 Experimental Measurement of PII Propensities, 1616.3 Computational Studies of Denatured State Conformational Propensities, 1686.4 A Steric Model Reveals Common PII Propensity of the Peptide Backbone, 1726.5 Correlation of PII Propensity to Amino Acid Properties, 1756.6 Summary, 180Acknowledgments, 180References, 1807 Mapping Conformational Dynamics in Unfolded Polypeptide Chains Using Short Model Peptides by NMR Spectroscopy 187Daniel Mathieu, Karin Rybka, Jürgen Graf, and Harald Schwalbe7.1 Introduction, 1877.2 General Aspects of NMR Spectroscopy, 1897.3 NMR Parameters and Their Measurement, 1917.4 Translating NMR Parameters to Structural Information, 2027.5 Conclusions, 213Acknowledgments, 215References, 2158 Secondary Structure and Dynamics of a Family of Disordered Proteins 221Pranesh Narayanaswami and Gary W. Daughdrill8.1 Introduction, 2218.2 Materials and Methods, 2238.3 Results and Discussion, 226Acknowledgments, 235References, 235II DISORDERED PEPTIDES AND MOLECULAR RECOGNITION 2399 Binding Promiscuity of Unfolded Peptides 241Christopher J. Oldfi eld, Bin Xue, A. Keith Dunker, and Vladimir N. Uversky9.1 Protein–Protein Interaction Networks, 2419.2 Role of Intrinsic Disorder in PPI Networks, 2429.3 Transient Structural Elements in Protein-Based Recognition, 2439.4 Chameleons and Adaptors: Binding Promiscuity of Unfolded Peptides, 2569.5 Principles of Using the Unfolded Protein Regions for Binding, 2629.6 Conclusions, 266Acknowledgments, 266References, 26610 Intrinsic Flexibility of Nucleic Acid Chaperone Proteins from Pathogenic RNA Viruses 279Roland Ivanyi-Nagy, Zuzanna Makowska, and Jean-Luc Darlix10.1 Introduction, 27910.2 Retroviruses and Retroviral Nucleocapsid Proteins, 28010.3 Core Proteins in the Flaviviridae Family of Viruses, 28810.4 Coronavirus Nucleocapsid Protein, 29010.5 Hantavirus Nucleocapsid Protein, 291Acknowledgments, 293References, 293III AGGREGATION OF DISORDERED PEPTIDES 30711 Self-Assembling Alanine-Rich Peptides of Biomedical and Biotechnological Relevance 309Thomas J. Measey and Reinhard Schweitzer-Stenner11.1 Biomolecular Self-Assembly, 30911.2 Misfolding and Human Disease, 31011.3 Exploitation of Peptide Self-Assembly for Biotechnological Applications, 32611.4 Concluding Remarks, 340Acknowledgments, 340References, 34012 Structural Elements Regulating Interactions in the Early Stages of Fibrillogenesis: A Human Calcitonin Model System 351Rosa Maria Vitale, Giuseppina Andreotti, Pietro Amodeo, and Andrea Motta12.1 Stating the Problem, 35112.2 Aggregation Models: The State of The Art, 35412.3 Human Calcitonin hCT as a Model System for Self-Assembly, 35612.4 The “Prefi brillar” State of hCT, 35812.5 How Many Molecules for the Critical Nucleus?, 36112.6 Modeling Prefi brillar Aggregates, 36612.7 hCT Helical Oligomers, 36612.8 The Role of Aromatic Residues in the Early Stages of Amyloid Formation, 37212.9 The Folding of hCT before Aggregation, 37312.10 Model Explains the Differences in Aggregation Properties between hCT and sCT, 37412.11 hCT Fibril Maturation, 37512.12 α-Helix →β-Sheet Conformational Transition and hCT Fibrillation, 37712.13 Concluding Remarks, 378Acknowledgments, 378References, 37913 Solution NMR Studies of Aβ Monomers and Oligomers 389Chunyu Wang13.1 Introduction, 38913.2 Overexpression and Purifi cation of Recombinant Aβ, 39013.3 Aβ Monomers, 39313.4 Aβ Oligomers and Monomer–Oligomer Interaction, 40313.5 Conclusion, 406References, 40614 Thermodynamic and Kinetic Models for Aggregation of Intrinsically Disordered Proteins 413Scott L. Crick and Rohit V. Pappu14.1 Introduction, 41314.2 Thermodynamics of Protein Aggregation—the Phase Diagram Approach, 41514.3 Thermodynamics of IDP Aggregation (Phase Separation)—MPM Description, 42014.4 Kinetics of Homogeneous Nucleation and Elongation Using MPMs, 42514.5 Concepts from Colloidal Science, 42714.6 Conclusions, 433Acknowledgments, 433References, 43415 Modifiers of Protein Aggregation—From Nonspecific to Specific Interactions 441Michal Levy-Sakin, Roni Scherzer-Attali, and Ehud Gazit15.1 Introduction, 44115.2 Nonspecific Modifi ers, 44215.3 Specific Modifiers, 454Acknowledgments, 465References, 46616 Computational Studies of Folding and Assembly of Amyloidogenic Proteins 479J. Srinivasa Rao, Brigita Urbanc, and Luis Cruz16.1 Introduction, 47916.2 Amyloids, 48016.3 Computer Simulations, 48516.4 Summary, 514References, 515INDEX 529

Reinhard Schweitzer-Stenner, PhD, is Professor and currently the Head of the Chemistry Department at Drexel University. Dr. Schweitzer-Stenner also heads the biospectroscopy research group. His research investigates peptide structure and functionally relevant heme distortions as well as ligand-receptor binding on the surface of mast cells. With more than 150 published research articles, Dr. Schweitzer-Stenner is widely recognized as a leader and pioneer in the study of the conformational properties of unfolded peptides.

• Introduction to the Wiley Series on Protein and Peptide Science xiii Preface xvContributors xixINTRODUCTION 11 Why Are We Interested in the Unfolded Peptides and Proteins? 3Vladimir N. Uversky and A. Keith Dunker1.1 Introduction, 31.2 Why Study IDPs?, 41.3 Lesson 1: Disorderedness Is Encoded in the Amino Acid Sequence and Can Be Predicted, 51.4 Lesson 2: Disordered Proteins Are Highly Abundant in Nature, 71.5 Lesson 3: Disordered Proteins Are Globally Heterogeneous, 91.6 Lesson 4: Hydrodynamic Dimensions of Natively Unfolded Proteins Are Charge Dependent, 141.7 Lesson 5: Polymer Physics Explains Hydrodynamic Behavior of Disordered Proteins, 161.8 Lesson 6: Natively Unfolded Proteins Are Pliable and Very Sensitive to Their Environment, 181.9 Lesson 7: When Bound, Natively Unfolded Proteins Can Gain Unusual Structures, 201.10 Lesson 8: IDPs Can Form Disordered or Fuzzy Complexes, 251.11 Lesson 9: Intrinsic Disorder Is Crucial for Recognition, Regulation, and Signaling, 251.12 Lesson 10: Protein Posttranslational Modifi cations Occur at Disordered Regions, 281.13 Lesson 11: Disordered Regions Are Primary Targets for AS, 301.14 Lesson 12: Disordered Proteins Are Tightly Regulated in the Living Cells, 311.15 Lesson 13: Natively Unfolded Proteins Are Frequently Associated with Human Diseases, 331.16 Lesson 14: Natively Unfolded Proteins Are Attractive Drug Targets, 351.17 Lesson 15: Bright Future of Fuzzy Proteins, 38Acknowledgments, 39References, 40I CONFORMATIONAL ANALYSIS OF UNFOLDED STATES 552 Exploring the Energy Landscape of Small Peptides and Proteins by Molecular Dynamics Simulations 57Gerhard Stock, Abhinav Jain, Laura Riccardi, and Phuong H. Nguyen2.1 Introduction: Free Energy Landscapes and How to Construct Them, 572.2 Dihedral Angle PCA Allows Us to Separate Internal and Global Motion, 612.3 Dimensionality of the Free Energy Landscape, 622.4 Characterization of the Free Energy Landscape: States, Barriers, and Transitions, 652.5 Low-Dimensional Simulation of Biomolecular Dynamics to Catch Slow and Rare Processes, 672.6 PCA by Parts: The Folding Pathways of Villin Headpiece, 692.7 The Energy Landscape of Aggregating Aβ-Peptides, 732.8 Concluding Remarks, 74Acknowledgments, 75References, 753 Local Backbone Preferences and Nearest-Neighbor Effects in the Unfolded and Native States 79Joe DeBartolo, Abhishek Jha, Karl F. Freed, and Tobin R. Sosnick3.1 Introduction, 793.2 Early Days: Random Coil—Theory and Experiment, 803.3 Denatured Proteins as Self-Avoiding Random Coils, 823.4 Modeling the Unfolded State, 823.5 NN Effects in Protein Structure Prediction, 863.6 Utilizing Folding Pathways for Structure Prediction, 873.7 Native State Modeling, 883.8 Secondary-Structure Propensities: Native Backbones in Unfolded Proteins, 923.9 Conclusions, 92Acknowledgments, 93References, 944 Short-Distance FRET Applied to the Polypeptide Chain 99Maik H. Jacob and Werner M. Nau4.1 A Short Timeline of Resonance Energy Transfer Applied to the Polypeptide Chain, 994.2 A Short Theory of FRET Applied to the Polypeptide Chain, 1014.3 DBO and Dbo, 1054.4 Short-Distance FRET Applied to the Structured Polypeptide Chain, 1074.5 Short-Distance FRET to Monitor Chain-Structural Transitions upon Phosphorylation, 1164.6 Short-Distance FRET Applied to the Structureless Chain, 1204.7 The Future of Short-Distance FRET, 125Acknowledgments, 125Dedication, 126References, 1265 Solvation and Electrostatics as Determinants of Local Structural Order in Unfolded Peptides and Proteins 131Franc Avbelj5.1 Local Structural Order in Unfolded Peptides and Proteins, 1315.2 ESM, 1345.3 The ESM and Strand-Coil Transition Model, 1375.4 The ESM and Backbone Conformational Preferences, 1385.5 The Nearest-Neighbor Effect, 1415.6 The ESM and Cooperative Local Structures—Fluctuating β-Strands, 1415.7 The ESM and β-Sheet Preferences in Native Proteins—Significance of Unfolded State, 1445.8 The ESM and Secondary Chemical Shifts of Polypeptides, 1455.9 Role of Backbone Solvation in Determining Hydrogen Exchange Rates of Unfolded Polypeptides, 1485.10 Other Theoretical Models of Unfolded Polypeptides, 148Acknowledgments, 149References, 1496 Experimental and Computational Studies of Polyproline II Propensity 159W. Austin Elam, Travis P. Schrank, and Vincent J. Hilser6.1 Introduction, 1596.2 Experimental Measurement of PII Propensities, 1616.3 Computational Studies of Denatured State Conformational Propensities, 1686.4 A Steric Model Reveals Common PII Propensity of the Peptide Backbone, 1726.5 Correlation of PII Propensity to Amino Acid Properties, 1756.6 Summary, 180Acknowledgments, 180References, 1807 Mapping Conformational Dynamics in Unfolded Polypeptide Chains Using Short Model Peptides by NMR Spectroscopy 187Daniel Mathieu, Karin Rybka, Jürgen Graf, and Harald Schwalbe7.1 Introduction, 1877.2 General Aspects of NMR Spectroscopy, 1897.3 NMR Parameters and Their Measurement, 1917.4 Translating NMR Parameters to Structural Information, 2027.5 Conclusions, 213Acknowledgments, 215References, 2158 Secondary Structure and Dynamics of a Family of Disordered Proteins 221Pranesh Narayanaswami and Gary W. Daughdrill8.1 Introduction, 2218.2 Materials and Methods, 2238.3 Results and Discussion, 226Acknowledgments, 235References, 235II DISORDERED PEPTIDES AND MOLECULAR RECOGNITION 2399 Binding Promiscuity of Unfolded Peptides 241Christopher J. Oldfi eld, Bin Xue, A. Keith Dunker, and Vladimir N. Uversky9.1 Protein–Protein Interaction Networks, 2419.2 Role of Intrinsic Disorder in PPI Networks, 2429.3 Transient Structural Elements in Protein-Based Recognition, 2439.4 Chameleons and Adaptors: Binding Promiscuity of Unfolded Peptides, 2569.5 Principles of Using the Unfolded Protein Regions for Binding, 2629.6 Conclusions, 266Acknowledgments, 266References, 26610 Intrinsic Flexibility of Nucleic Acid Chaperone Proteins from Pathogenic RNA Viruses 279Roland Ivanyi-Nagy, Zuzanna Makowska, and Jean-Luc Darlix10.1 Introduction, 27910.2 Retroviruses and Retroviral Nucleocapsid Proteins, 28010.3 Core Proteins in the Flaviviridae Family of Viruses, 28810.4 Coronavirus Nucleocapsid Protein, 29010.5 Hantavirus Nucleocapsid Protein, 291Acknowledgments, 293References, 293III AGGREGATION OF DISORDERED PEPTIDES 30711 Self-Assembling Alanine-Rich Peptides of Biomedical and Biotechnological Relevance 309Thomas J. Measey and Reinhard Schweitzer-Stenner11.1 Biomolecular Self-Assembly, 30911.2 Misfolding and Human Disease, 31011.3 Exploitation of Peptide Self-Assembly for Biotechnological Applications, 32611.4 Concluding Remarks, 340Acknowledgments, 340References, 34012 Structural Elements Regulating Interactions in the Early Stages of Fibrillogenesis: A Human Calcitonin Model System 351Rosa Maria Vitale, Giuseppina Andreotti, Pietro Amodeo, and Andrea Motta12.1 Stating the Problem, 35112.2 Aggregation Models: The State of The Art, 35412.3 Human Calcitonin hCT as a Model System for Self-Assembly, 35612.4 The “Prefi brillar” State of hCT, 35812.5 How Many Molecules for the Critical Nucleus?, 36112.6 Modeling Prefi brillar Aggregates, 36612.7 hCT Helical Oligomers, 36612.8 The Role of Aromatic Residues in the Early Stages of Amyloid Formation, 37212.9 The Folding of hCT before Aggregation, 37312.10 Model Explains the Differences in Aggregation Properties between hCT and sCT, 37412.11 hCT Fibril Maturation, 37512.12 α-Helix →β-Sheet Conformational Transition and hCT Fibrillation, 37712.13 Concluding Remarks, 378Acknowledgments, 378References, 37913 Solution NMR Studies of Aβ Monomers and Oligomers 389Chunyu Wang13.1 Introduction, 38913.2 Overexpression and Purifi cation of Recombinant Aβ, 39013.3 Aβ Monomers, 39313.4 Aβ Oligomers and Monomer–Oligomer Interaction, 40313.5 Conclusion, 406References, 40614 Thermodynamic and Kinetic Models for Aggregation of Intrinsically Disordered Proteins 413Scott L. Crick and Rohit V. Pappu14.1 Introduction, 41314.2 Thermodynamics of Protein Aggregation—the Phase Diagram Approach, 41514.3 Thermodynamics of IDP Aggregation (Phase Separation)—MPM Description, 42014.4 Kinetics of Homogeneous Nucleation and Elongation Using MPMs, 42514.5 Concepts from Colloidal Science, 42714.6 Conclusions, 433Acknowledgments, 433References, 43415 Modifiers of Protein Aggregation—From Nonspecific to Specific Interactions 441Michal Levy-Sakin, Roni Scherzer-Attali, and Ehud Gazit15.1 Introduction, 44115.2 Nonspecific Modifi ers, 44215.3 Specific Modifiers, 454Acknowledgments, 465References, 46616 Computational Studies of Folding and Assembly of Amyloidogenic Proteins 479J. Srinivasa Rao, Brigita Urbanc, and Luis Cruz16.1 Introduction, 47916.2 Amyloids, 48016.3 Computer Simulations, 48516.4 Summary, 514References, 515INDEX 529

Reinhard Schweitzer-Stenner, PhD, is Professor and currently the Head of the Chemistry Department at Drexel University. Dr. Schweitzer-Stenner also heads the biospectroscopy research group. His research investigates peptide structure and functionally relevant heme distortions as well as ligand-receptor binding on the surface of mast cells. With more than 150 published research articles, Dr. Schweitzer-Stenner is widely recognized as a leader and pioneer in the study of the conformational properties of unfolded peptides.

• Introduction to the Wiley Series on Protein and Peptide Science xiii Preface xvContributors xixINTRODUCTION 11 Why Are We Interested in the Unfolded Peptides and Proteins? 3Vladimir N. Uversky and A. Keith Dunker1.1 Introduction, 31.2 Why Study IDPs?, 41.3 Lesson 1: Disorderedness Is Encoded in the Amino Acid Sequence and Can Be Predicted, 51.4 Lesson 2: Disordered Proteins Are Highly Abundant in Nature, 71.5 Lesson 3: Disordered Proteins Are Globally Heterogeneous, 91.6 Lesson 4: Hydrodynamic Dimensions of Natively Unfolded Proteins Are Charge Dependent, 141.7 Lesson 5: Polymer Physics Explains Hydrodynamic Behavior of Disordered Proteins, 161.8 Lesson 6: Natively Unfolded Proteins Are Pliable and Very Sensitive to Their Environment, 181.9 Lesson 7: When Bound, Natively Unfolded Proteins Can Gain Unusual Structures, 201.10 Lesson 8: IDPs Can Form Disordered or Fuzzy Complexes, 251.11 Lesson 9: Intrinsic Disorder Is Crucial for Recognition, Regulation, and Signaling, 251.12 Lesson 10: Protein Posttranslational Modifi cations Occur at Disordered Regions, 281.13 Lesson 11: Disordered Regions Are Primary Targets for AS, 301.14 Lesson 12: Disordered Proteins Are Tightly Regulated in the Living Cells, 311.15 Lesson 13: Natively Unfolded Proteins Are Frequently Associated with Human Diseases, 331.16 Lesson 14: Natively Unfolded Proteins Are Attractive Drug Targets, 351.17 Lesson 15: Bright Future of Fuzzy Proteins, 38Acknowledgments, 39References, 40I CONFORMATIONAL ANALYSIS OF UNFOLDED STATES 552 Exploring the Energy Landscape of Small Peptides and Proteins by Molecular Dynamics Simulations 57Gerhard Stock, Abhinav Jain, Laura Riccardi, and Phuong H. Nguyen2.1 Introduction: Free Energy Landscapes and How to Construct Them, 572.2 Dihedral Angle PCA Allows Us to Separate Internal and Global Motion, 612.3 Dimensionality of the Free Energy Landscape, 622.4 Characterization of the Free Energy Landscape: States, Barriers, and Transitions, 652.5 Low-Dimensional Simulation of Biomolecular Dynamics to Catch Slow and Rare Processes, 672.6 PCA by Parts: The Folding Pathways of Villin Headpiece, 692.7 The Energy Landscape of Aggregating Aβ-Peptides, 732.8 Concluding Remarks, 74Acknowledgments, 75References, 753 Local Backbone Preferences and Nearest-Neighbor Effects in the Unfolded and Native States 79Joe DeBartolo, Abhishek Jha, Karl F. Freed, and Tobin R. Sosnick3.1 Introduction, 793.2 Early Days: Random Coil—Theory and Experiment, 803.3 Denatured Proteins as Self-Avoiding Random Coils, 823.4 Modeling the Unfolded State, 823.5 NN Effects in Protein Structure Prediction, 863.6 Utilizing Folding Pathways for Structure Prediction, 873.7 Native State Modeling, 883.8 Secondary-Structure Propensities: Native Backbones in Unfolded Proteins, 923.9 Conclusions, 92Acknowledgments, 93References, 944 Short-Distance FRET Applied to the Polypeptide Chain 99Maik H. Jacob and Werner M. Nau4.1 A Short Timeline of Resonance Energy Transfer Applied to the Polypeptide Chain, 994.2 A Short Theory of FRET Applied to the Polypeptide Chain, 1014.3 DBO and Dbo, 1054.4 Short-Distance FRET Applied to the Structured Polypeptide Chain, 1074.5 Short-Distance FRET to Monitor Chain-Structural Transitions upon Phosphorylation, 1164.6 Short-Distance FRET Applied to the Structureless Chain, 1204.7 The Future of Short-Distance FRET, 125Acknowledgments, 125Dedication, 126References, 1265 Solvation and Electrostatics as Determinants of Local Structural Order in Unfolded Peptides and Proteins 131Franc Avbelj5.1 Local Structural Order in Unfolded Peptides and Proteins, 1315.2 ESM, 1345.3 The ESM and Strand-Coil Transition Model, 1375.4 The ESM and Backbone Conformational Preferences, 1385.5 The Nearest-Neighbor Effect, 1415.6 The ESM and Cooperative Local Structures—Fluctuating β-Strands, 1415.7 The ESM and β-Sheet Preferences in Native Proteins—Significance of Unfolded State, 1445.8 The ESM and Secondary Chemical Shifts of Polypeptides, 1455.9 Role of Backbone Solvation in Determining Hydrogen Exchange Rates of Unfolded Polypeptides, 1485.10 Other Theoretical Models of Unfolded Polypeptides, 148Acknowledgments, 149References, 1496 Experimental and Computational Studies of Polyproline II Propensity 159W. Austin Elam, Travis P. Schrank, and Vincent J. Hilser6.1 Introduction, 1596.2 Experimental Measurement of PII Propensities, 1616.3 Computational Studies of Denatured State Conformational Propensities, 1686.4 A Steric Model Reveals Common PII Propensity of the Peptide Backbone, 1726.5 Correlation of PII Propensity to Amino Acid Properties, 1756.6 Summary, 180Acknowledgments, 180References, 1807 Mapping Conformational Dynamics in Unfolded Polypeptide Chains Using Short Model Peptides by NMR Spectroscopy 187Daniel Mathieu, Karin Rybka, Jürgen Graf, and Harald Schwalbe7.1 Introduction, 1877.2 General Aspects of NMR Spectroscopy, 1897.3 NMR Parameters and Their Measurement, 1917.4 Translating NMR Parameters to Structural Information, 2027.5 Conclusions, 213Acknowledgments, 215References, 2158 Secondary Structure and Dynamics of a Family of Disordered Proteins 221Pranesh Narayanaswami and Gary W. Daughdrill8.1 Introduction, 2218.2 Materials and Methods, 2238.3 Results and Discussion, 226Acknowledgments, 235References, 235II DISORDERED PEPTIDES AND MOLECULAR RECOGNITION 2399 Binding Promiscuity of Unfolded Peptides 241Christopher J. Oldfi eld, Bin Xue, A. Keith Dunker, and Vladimir N. Uversky9.1 Protein–Protein Interaction Networks, 2419.2 Role of Intrinsic Disorder in PPI Networks, 2429.3 Transient Structural Elements in Protein-Based Recognition, 2439.4 Chameleons and Adaptors: Binding Promiscuity of Unfolded Peptides, 2569.5 Principles of Using the Unfolded Protein Regions for Binding, 2629.6 Conclusions, 266Acknowledgments, 266References, 26610 Intrinsic Flexibility of Nucleic Acid Chaperone Proteins from Pathogenic RNA Viruses 279Roland Ivanyi-Nagy, Zuzanna Makowska, and Jean-Luc Darlix10.1 Introduction, 27910.2 Retroviruses and Retroviral Nucleocapsid Proteins, 28010.3 Core Proteins in the Flaviviridae Family of Viruses, 28810.4 Coronavirus Nucleocapsid Protein, 29010.5 Hantavirus Nucleocapsid Protein, 291Acknowledgments, 293References, 293III AGGREGATION OF DISORDERED PEPTIDES 30711 Self-Assembling Alanine-Rich Peptides of Biomedical and Biotechnological Relevance 309Thomas J. Measey and Reinhard Schweitzer-Stenner11.1 Biomolecular Self-Assembly, 30911.2 Misfolding and Human Disease, 31011.3 Exploitation of Peptide Self-Assembly for Biotechnological Applications, 32611.4 Concluding Remarks, 340Acknowledgments, 340References, 34012 Structural Elements Regulating Interactions in the Early Stages of Fibrillogenesis: A Human Calcitonin Model System 351Rosa Maria Vitale, Giuseppina Andreotti, Pietro Amodeo, and Andrea Motta12.1 Stating the Problem, 35112.2 Aggregation Models: The State of The Art, 35412.3 Human Calcitonin hCT as a Model System for Self-Assembly, 35612.4 The “Prefi brillar” State of hCT, 35812.5 How Many Molecules for the Critical Nucleus?, 36112.6 Modeling Prefi brillar Aggregates, 36612.7 hCT Helical Oligomers, 36612.8 The Role of Aromatic Residues in the Early Stages of Amyloid Formation, 37212.9 The Folding of hCT before Aggregation, 37312.10 Model Explains the Differences in Aggregation Properties between hCT and sCT, 37412.11 hCT Fibril Maturation, 37512.12 α-Helix →β-Sheet Conformational Transition and hCT Fibrillation, 37712.13 Concluding Remarks, 378Acknowledgments, 378References, 37913 Solution NMR Studies of Aβ Monomers and Oligomers 389Chunyu Wang13.1 Introduction, 38913.2 Overexpression and Purifi cation of Recombinant Aβ, 39013.3 Aβ Monomers, 39313.4 Aβ Oligomers and Monomer–Oligomer Interaction, 40313.5 Conclusion, 406References, 40614 Thermodynamic and Kinetic Models for Aggregation of Intrinsically Disordered Proteins 413Scott L. Crick and Rohit V. Pappu14.1 Introduction, 41314.2 Thermodynamics of Protein Aggregation—the Phase Diagram Approach, 41514.3 Thermodynamics of IDP Aggregation (Phase Separation)—MPM Description, 42014.4 Kinetics of Homogeneous Nucleation and Elongation Using MPMs, 42514.5 Concepts from Colloidal Science, 42714.6 Conclusions, 433Acknowledgments, 433References, 43415 Modifiers of Protein Aggregation—From Nonspecific to Specific Interactions 441Michal Levy-Sakin, Roni Scherzer-Attali, and Ehud Gazit15.1 Introduction, 44115.2 Nonspecific Modifi ers, 44215.3 Specific Modifiers, 454Acknowledgments, 465References, 46616 Computational Studies of Folding and Assembly of Amyloidogenic Proteins 479J. Srinivasa Rao, Brigita Urbanc, and Luis Cruz16.1 Introduction, 47916.2 Amyloids, 48016.3 Computer Simulations, 48516.4 Summary, 514References, 515INDEX 529