Computational Methods for Protein Structure Prediction and Modeling (eBook)

Dr. Ying Xu is Regents-GRA Eminent Scholar and Professor at the University of Georgia.  Dr. Dong Xu is the Director of the Digital Biology Laboratory at the University of Missouri-Columbia.  Dr. Jie Liang is the Director for the Center for Bioinformatics at the University of Illinois at Chicago.

Preface 6
Acknowledgments 13
Contents 14
Contributors 16
1 A Historical Perspective and Overview of Protein Structure Prediction 20
1.1 Introduction 20
1.2 The Development of Protein Structure Prediction Methodologies 22
1.3 A Shift in the Focus for Protein Modeling 35
1.4 Summary 50
References 51
2 Empirical Force Fields 63
2.1 Potential Energy Functions 63
2.2 Implementation of Potential Energy Functions 66
2.3 Treatment of Aqueous Solvation 67
2.4 Empirical Force Field Optimization 69
2.5 Protein Force Fields 72
2.6 Extended or United Atom Protein Force Fields 76
2.7 Summary 77
Acknowledgments 77
Appendix 78
References 78
3 Knowledge-Based Energy Functions for Computational Studies of Proteins 88
3.1 Introduction 88
3.2 General Framework 89
3.3 Statistical Method 91
3.4 Optimization Method 110
3.5 Applications 118
3.6 Online Resources 124
3.7 Discussion 124
3.8 Summary 132
3.9 Further Reading 132
Acknowledgments 133
References 133
4 Computational Methods for Domain Partitioning of Protein Structures 141
4.1 Introduction 141
4.2 Definitions of Structural Domains 142
4.3 Computational Methods 144
4.4 In-depth Look into Algorithmic Domain Decomposition 151
4.5 Evaluating Automatic Methods with Manual Consensus Benchmark 155
4.6 Future Goals 158
4.7 Summary 159
4.8 Suggested Further Reading 159
References 160
5 Protein Structure Comparison and Classification 162
5.1 Introduction 162
5.2 Pairwise Alignment of Protein Structures 164
5.3 Multiple Structure Comparison and Structural Motif Search 172
5.4 Structure Search in Protein Databases 175
5.5 Protein Classification 180
5.6 Concluding Remarks 188
5.7 References and Resources 189
5.8 Further Reading 190
Acknowledgment 191
References 191
6 Computation of Protein Geometry and Its Applications: Packing and Function Prediction 196
6.1 Introduction 196
6.2 Theory and Model 197
6.3 Computation and Software 206
6.4 Applications: Packing Analysis 209
6.5 Applications: Protein Function Prediction from Structures 211
6.6 Discussion 215
6.7 Summary 216
6.8 Further Reading 217
Acknowledgments 217
References 217
7 Local Structure Prediction of Proteins 222
7.1 Introduction 222
7.2 Protein Secondary Structure Prediction 222
7.3 Protein Supersecondary Structure Prediction 236
7.4 Protein Disordered Region Detection 239
7.5 Internal Repeats Detection 241
7.6 Applications to Multiple Sequence Alignment 243
7.7 Applications to Local Protein Tertiary Structure Prediction 245
7.8 Software Packages 247
7.9 Resources 258
7.10 Summary 258
References 258
Further Reading 269
8 Protein Contact Map Prediction 270
8.1 Introduction 270
8.2 Definition of Interresidue Contacts and Contact Maps 270
8.3 Features of a Contact Map 272
8.4 From Contact Map Prediction to 3D Structure 275
8.5 Contact Map Prediction 277
8.6 Evaluation of Contact Map Predictions 285
8.7 Other Applications of Contact Maps 286
8.8 Conclusions 287
Recommended Reading 288
References 288
9 Modeling Protein Aggregate Assembly and Structure 293
9.1 Introduction 293
9.2 Folding and Misfolding 294
9.3 Experimental Approaches to Aggregate Structure 298
9.4 Computational Approaches to Aggregate Structure 305
9.5 Summary 318
Suggested Further Reading 319
Acknowledgments 319
References 319
10 Homology-Based Modeling of Protein Structure 332
10.1 Introduction 332
10.2 Procedures in Homology Modeling 336
10.3 Homology Modeling with JACKAL 351
10.4 Application of Homology Modeling 358
10.5 Summary 360
Further Reading 361
Acknowledgments 361
References 362
11 Modeling Protein Structures Based on Density Maps at Intermediate Resolutions 371
11.1 Introduction 371
11.2 Sheetminer: Locating Sheets in Intermediate- Resolution Density Maps 372
11.3 Sheettracer: Building Pseudo-traces for ß-Strands in Intermediate-Resolution Density Maps 378
11.4 Determining Protein Topology Based on Skeletons of Secondary Structures 385
11.5 Future Perspectives 396
Acknowledgment 397
References 397
Index 401