Computational methods for protein structure prediction and modeling: - Structure prediction

0387333215......Page 1
Computational Methods\rfor Protein Structure\rPrediction and Modeling\rVolume 2: Structure Prediction......Page 4
Copyright Page......Page 5
Preface......Page 6
Acknowledgments......Page 13
Table of Contents......Page 14
Contributors......Page 16
12.1 Introduction......Page 20
12.2 Protein Domains, Structural Folds, and Structure Space......Page 21
12.3 Fitting a Protein Sequence onto a Protein Structure......Page 26
12.4 Calculating Optimal Sequence-Structure Alignments......Page 31
12.4.1 PROSPECT......Page 33
12.4.3 Tree-Decomposition-Based Threading Algorithm......Page 35
12.4.3.1 Graph Representation......Page 36
12.4.3.2 Tree Decomposition of Structure Graph......Page 38
12.4.3.4 Time Complexity Analysis......Page 40
12.5 Assessing Statistical Significance of Threading Alignments......Page 42
12.6.1 Database of Template Structures......Page 44
12.6.4 Assessing Prediction Reliability......Page 45
12.7 Improving Threading-Based Structure Prediction......Page 48
12.7.1 Application of Experimental Data as Threading Constraints......Page 49
12.8 Challenging Issues......Page 51
Consensus Building and Subdomain Threading......Page 52
Acknowledgments......Page 53
References......Page 54
13.1 Introduction......Page 62
13.2.1 Energy Functions......Page 63
13.2.2 Knowledge-Based Energies......Page 64
13.2.4 Lattice Methods......Page 65
13.2.5 Fragment Assembly......Page 66
13.2.6 Continuous Torsional Distributions......Page 68
13.2.7 Selection of the Best Conformers......Page 69
13.2.8 PROTINFO, an Example de Novo Prediction Protocol......Page 72
13.2.9 Other de Novo Structure Prediction Protocols......Page 74
13.3.1 Faster Computers and Larger Databases......Page 75
13.3.2 Future Directions......Page 76
References......Page 77
14.1 Introduction......Page 83
14.2.1.1 Hydrophobicity......Page 86
14.2.1.2 Hydrophobic Moment......Page 88
14.2.1.3 The Positive-Inside Rule......Page 89
Hydropathy Analysis......Page 90
An Example......Page 92
ALOM2......Page 93
SOSUI......Page 94
14.2.2.2 Statistical (Propensity Based) Methods......Page 95
SPLIT......Page 96
An Example......Page 97
14.2.2.3 Learning Algorithm-Based Methods......Page 98
TMHMM......Page 99
ENSEMBLE......Page 100
14.2.3 The Prediction Methods for the Topology of Transmembrane Barrels......Page 101
BIOSINO-HMM......Page 105
PRED-TMBB......Page 106
14.2.3.2 Accessibility......Page 107
Per-Residue Accuracy......Page 109
Per-Segment Accuracy......Page 110
14.2.4.2 Performance of Secondary Structure Predictors......Page 112
14.3.1 Molecular Determinants of Helix-Helix Interactions......Page 115
14.3.2.1 Potential Functions Based on Physical Models......Page 116
14.3.3 Algorithms for Optimizing Helix-Helix Packing......Page 117
References......Page 118
15.1.1 Protein Docking: Definition......Page 127
15.1.3 Will the Proteins Interact?......Page 128
15.1.4 Input Structures......Page 129
15.2 Unbound Docking: Current Approaches......Page 130
15.2.1 Rigid Body Docking: Search......Page 132
15.2.1.2 Other Search Techniques......Page 133
15.2.2.1 Shape Complementarity......Page 134
15.2.2.3 Desolvation and Statistical Potentials......Page 136
15.2.4 Clustering......Page 137
15.3.1 Determining Accuracy of Predictions......Page 138
15.3.2 Docking Benchmark......Page 139
15.4.1 ZDOCK Algorithm......Page 140
15.4.2.1 RDOCK: Energy Minimization......Page 141
15.4.3.1 Development of a Scoring Function......Page 142
15.4.3.2 Exploring the Search Space......Page 143
15.5.1 CAPRI Success/Lessons......Page 144
Books......Page 146
References......Page 147
16.1 Introduction to Modern Drug Discovery......Page 153
16.1.2 Role of Protein Structure in Modern Pharmaceutical Sciences......Page 154
16.1.3 Structure-Based Drug Design......Page 155
16.2.1 Cytokines......Page 156
16.2.2 Antibodies......Page 158
16.2.3 Engineered Enzymes......Page 160
16.2.4 Summary of Protein Therapeutics......Page 161
16.3.1 Docking......Page 162
16.3.1.1 Search Algorithms......Page 164
16.3.1.2 Scoring Functions......Page 165
16.3.1.3 Input Receptor Structures......Page 167
16.3.2.1 VS Library Generation......Page 170
16.3.3 Lead Optimization......Page 171
16.4 Ligand-Based Drug Design......Page 172
16.4.1 Pharmacophore Modeling......Page 173
16.4.2 Quantitative Structure-Activity Relationship (QSAR)......Page 176
16.4.2.2 Descriptor Selection......Page 177
A. Linear Models......Page 179
16.4.2.4 Model Validation......Page 180
16.4.2.5 3D-QSAR......Page 181
16.4.3 Summary of Ligand-Based Drug Design......Page 182
16.6 Conclusions......Page 183
References......Page 184
17.1 Introduction: The Complexity of Protein Structure Prediction......Page 195
17.2 Consensus-Based Approach for Protein Structure Prediction......Page 198
17.3 Pipeline Approach for Protein Structure Prediction......Page 200
17.4 Expert System for Protein Structure Prediction......Page 204
17.5 From Structure to Function......Page 207
17.6 Benchmark and Evaluation......Page 210
17.7 Genome-Scale Protein Structure Prediction......Page 212
17.7.2 Global Analysis of Protein Structural Folds in Three Genomes......Page 213
17.7.3 Computational Analysis of Predicted Carboxysome Proteins......Page 214
1. Protein representation......Page 216
5. New computational technology development......Page 217
References......Page 218
18.1 Introduction......Page 225
18.2 PDB and Related Databases/Servers......Page 226
18.4 Protein Sequence and Function Databases......Page 230
18.5 Structural Bioinformatics Tools......Page 235
18.7 General Online Resources......Page 238
18.8 Major Journals and Further Readings......Page 239
18.10 Summary......Page 240
Acknowledgments......Page 241
References......Page 242
A 1.1 Amino Acid Residues......Page 246
A 1.2 Nucleic Acids......Page 248
A 1.3 Protein Structures......Page 250
Suggested Further Readings......Page 255
A 2.1 Introduction......Page 257
A 2.2 Efficient Data Structures......Page 258
A 2.2.1 Hash Tables......Page 259
A 2.2.2 Suffix Trees......Page 260
A 2.2.3 Disjoint Sets......Page 261
A 2.2.4 Heaps......Page 262
A 2.3.1 Concept of Computational Complexity......Page 263
A 2.3.2 Optimization Problems......Page 266
A 2.4 Algorithmic Techniques......Page 267
A 2.4.1 Exhaustive Enumeration......Page 268
A 2.4.2 Dynamic Programming......Page 269
A 2.4.3 Integer Programming......Page 270
A 2.4.4 Branch-and-Bound......Page 271
A 2.4.5 A* Search......Page 272
A 2.4.7 Greedy Algorithms......Page 273
A 2.4.8 Reduction Techniques......Page 274
A 2.4.9 Divide-and-Conquer Algorithms......Page 276
A 2.5 Parallel Computing......Page 277
A 2.7 Summary......Page 278
A 2.8 Acknowledgments......Page 279
References......Page 280
A 3.1 Introduction......Page 283
A 3.2.1 Units......Page 284
A 3.2.2 Potential Energy Surface......Page 285
A 3.2.3 Coordinate Systems......Page 286
A 3.3.2 Formation of the Peptide Bond......Page 289
A 3.4.1 Covalent Bond......Page 290
A 3.4.3 van der Waals Interactions......Page 291
A 3.4.6 Solvation......Page 292
A 3.4.7 Hydrophobic Interactions......Page 293
A 3.5.2 The Most Probable Distribution......Page 294
A 3.5.3 Entropy......Page 296
A 3.5.4 Information Entropy......Page 299
A 3.5.5 Enthalpy......Page 300
A 3.5.6.1 Helmholtz Free Energy......Page 301
A 3.5.6.2 Gibbs Free Energy......Page 303
A 3.5.7 Kinetic Barrier......Page 304
A 3.6.1 Newtonian Laws......Page 305
A 3.6.2 Numeric Solution: Finite Difference Method......Page 306
A 3.6.3 Time-Dependent Properties......Page 308
A 3.7.4 Euler Angles......Page 309
Further Reading......Page 312
References......Page 313
A 4.2 Probability Distributions......Page 314
Uniform Distribution......Page 315
Binomial and Multinomial Distributions......Page 316
Gamma Distribution......Page 317
Extreme Value Distribution......Page 318
Mutual Information......Page 319
Markovian Process......Page 320
Evaluation......Page 321
Decoding......Page 322
Null Test......Page 323
Z-Test and T-test......Page 324
Maximum Likelihood......Page 325
Importance and Rejection Samplings......Page 326
Metropolis-Hastings Algorithm......Page 327
Gibbs sampling......Page 328
References......Page 329
Index......Page 331