Practical Bioinformatics

By: Janusz M. Bujnicki (Editor)

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Paperback | 2 October 2007

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284 Pages

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23.5 x 15.5 x 1.27

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This book presents applications of bioinformatics tools that experimental research scientists use in "daily practice." Its interdisciplinary approach combines computational and experimental methods to solve scientific problems. The book begins with reviews of computational methods for protein sequence-structure-function analysis, followed by methods that use experimental data obtained in the laboratory to improve functional predictions.

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Computational Methods for Protein Structure Prediction and Fold Recognition	p. 1
Primary Structure Analysis	p. 1
Database Searches	p. 1
Protein Domain Identification	p. 3
Prediction of Disordered Regions	p. 5
Secondary Structure Prediction	p. 5
Helices and Strands and Otherwise	p. 5
Transmembrane Helices	p. 8
Protein Fold Recognition	p. 8
Predicting All-in-One-Go	p. 12
Pitfalls of Fold Recognition	p. 14
References	p. 16
'Meta' Approaches to Protein Structure Prediction	p. 23
Introduction	p. 23
The Utility of Servers as Standard Tools for Protein Structure Prediction	p. 24
Consensus 'Meta-Predictors': Is the Whole Greater Than the Sum of the Parts?	p. 25
Automated Meta-Predictors	p. 26
Hybrid Methods: Going Beyond the "Simple Selection" of Models	p. 29
Future Prospects	p. 31
References	p. 32
From Molecular Modeling to Drug Design	p. 35
Introduction	p. 35
General Context	p. 35
Comparative Modeling	p. 36
Drug Design and Screening	p. 37
Comparative Modeling	p. 38
Sequence Gathering and Alignment	p. 38
Sequence Database Searches	p. 38
Multiple Sequence Alignments	p. 39
Structural Alignments	p. 39
Fold Recognition	p. 40
Structural Alignment Refinement	p. 40
Active Site Recognition	p. 41
A Biological Application	p. 42
Complete Model Achievement	p. 43
Global Structure Modeling	p. 44
Optimization of Side-Chain Conformation	p. 44
Insertions/Deletions Building	p. 46
Modeling Protein Quaternary Structures	p. 47
Energy Minimization and Molecular Dynamics	p. 48
Model Validation	p. 49
Theoretical Model Validation	p. 49
Ligand-Based Model Selection	p. 50
Experimental Evaluation of Models	p. 50
Current Limitations	p. 51
Model-Based Drug Design	p. 52
Comparative Drug Design	p. 53
Docking Methodologies	p. 55
Knowledge-Based Potentials	p. 55
Regression-Based (or Empirical) Methods	p. 56
Physics-Based Methods	p. 56
Flexible Models	p. 57
Fragment-Based Drug Design	p. 58
Virtual Screening Using Models	p. 58
Docking Onto Medium Resolution Models	p. 58
Docking Onto High-Resolution Models	p. 59
Pharmacogenomic Applications	p. 60
A Challenging Application: the GPCRs	p. 60
Family-Wide Docking	p. 60
Side Effect Predictions	p. 61
Drug Metabolization Predictions	p. 61
Conclusions	p. 62
References	p. 63
Structure Determination of Macromolecular Complexes by Experiment and Computation	p. 73
Introduction	p. 73
Hybrid Approaches to Determination of Assembly Structures	p. 77
Modeling the Low-Resolution Structures of Assemblies	p. 78
Representation of Molecular Assemblies	p. 80
Scoring Function Consisting of Individual Spatial Restraints	p. 80
Optimization of the Scoring Function	p. 81
Analysis of the Models	p. 81
Comparative Modeling for Structure Determination of Macromolecular Complexes	p. 82
Automated Comparative Protein Structure Modeling	p. 82
Accuracy of Comparative Models	p. 84
Prediction of Model Accuracy	p. 86
Docking of Comparative Models into Low-Resolution Cryo-EM Maps	p. 86
Example 1: A Partial Molecular Model of the 80S Ribosome from Saccharomyces cerevisiae	p. 88
Example 2: A Molecular Model of the E. coli 70S Ribosome	p. 90
Conclusions	p. 91
References	p. 92
Modeling Protein Folding Pathways	p. 97
Introduction: Darwin Versus Boltzmann	p. 95
Protein Folding Pathway History	p. 98
Knowledge-Based Models for Folding Pathways	p. 99
I-sites: A Library of Folding Initiation Site Motifs	p. 99
HMMSTR: A Hidden Markov Model for Grammatical Structure	p. 100
ROSETTA: Folding Simulations Using a Fragment Library	p. 101
Results of Fully Automated I-SITES/ROSETTA Simulations	p. 102
Summary	p. 102
Topologically Correct Large Fragment Predictions Are Found	p. 103
Good Local Structure Correlates Weakly with Good Tertiary Structure	p. 104
Average Contact Order Is Too Low	p. 105
How Could Automated ROSETTA Be Improved?	p. 105
HMMSTR-CM: Folding Pathways Using Contact Maps	p. 106
A Knowledge-Based Potential for Motif-Motif Interactions	p. 106
Fold Recognition Using Contact Potential Maps	p. 108
Consensus and Composite Contact Map Predictions	p. 111
Ab Initio Rule-Based Pathway Predictions	p. 111
Selected Results of HMMSTR-CM Blind Structure Predictions	p. 112
A Prediction Using Templates and a Pathway	p. 113
A Prediction Using Several Templates	p. 113
Correct Prediction Using Only the Folding Pathway	p. 114
False Prediction Using the Folding Pathway. What Went Wrong?	p. 116
Future Directions for HMMTR-CM	p. 117
Conclusions	p. 118
References	p. 118
Structural Bioinformatics and NMR Structure Determination	p. 123
Introduction: NMR and Structural Bioinformatics	p. 123
Algorithms for NMR Structure Calculation	p. 124
Distance Geometry and Data Consistency	p. 124
Nonlinear Optimization	p. 125
Sampling Conformational Space	p. 126
Modelling Structures with Limited Data Sets	p. 126
Internal Dynamics and NMR Structure Determination	p. 127
Calculating NMR Parameters from Molecular Dynamics Simulations	p. 127
Inferring Dynamics from NMR Data	p. 127
Structure Validation	p. 128
Structural Genomics by NMR	p. 129
Automated Assignment and Data Analysis	p. 129
Collaborative Computing Project for NMR (CCPN)	p. 130
SPINS	p. 132
Databanks and Databases	p. 132
BioMagResBank and PDB/RCSB	p. 133
Conclusions	p. 133
References	p. 134
Bioinformatics-Guided Identification and Experimental Characterization of Novel RNA Methyltransferases	p. 139
Introduction	p. 139
Diversity of Methylated Nucleosides in RNA	p. 139
RNA Methyltransferases	p. 141
Structural Biology of RNA MTases and Their Relatives	p. 142
Traditional and Novel Approaches to Identification of New RNA-Modification Enzymes	p. 145
Bioinformatics: Terminology, Methodology, and Applications to RNA MTases	p. 146
The Top-Down Approach	p. 149
Top-Down Search for Novel RNA:m[superscript 5]C MTases in Yeast	p. 151
Top-Down Search for Bacterial and Archaeal m[superscript 1]A MTases	p. 152
Top-Down Search for Novel Yeast 2'-O-MTases	p. 153
The Bottom-Up Approach	p. 155
Bottom-Up Search for New Yeast RNA MTases	p. 157
Conclusions	p. 160
References	p. 162
Finding Missing tRNA Modification Genes: A Comparative Genomics Goldmine	p. 169
Missing tRNA Modification Genes	p. 169
tRNA Modifications	p. 169
Compilation of the Missing tRNA Modification Genes	p. 170
Comparative Genomics: an Emerging Tool to Identify Missing Genes	p. 173
Finding Genes for Simple tRNA Modifications	p. 175
Paralog- and Ortholog-Based Identifications	p. 175
Comparative Genomics-Based Identifications	p. 176
Finding Complex Modification Pathway Genes	p. 178
Finding Missing Steps in Known Pathways	p. 178
Finding Uncharacterized Pathway Genes	p. 179
Identification of the preQ Biosynthesis Pathway Genes	p. 179
Hunting for the Wyeosine Biosynthesis Genes	p. 182
Conclusions	p. 183
References	p. 184
Evolution and Function of Processosome, the Complex That Assembles Ribosomes in Eukaryotes: Clues from Comparative Sequence Analysis	p. 191
Introduction	p. 191
Sequence Analysis of the Processosome Components	p. 192
Intrinsic Features	p. 193
Evolutionarily Conserved Sequence Domains	p. 195
Kre33p, or Possibly AtAc: Protein with Multiple Predicted Activities	p. 204
Imp4/Ssf1/Rpf1/Brx1/Peter Pan Family of Proteins	p. 209
Diverse RNA-Binding Domains and Limited Repertoire of Globular Protein Interaction Modules	p. 211
Phyletic Patterns	p. 212
Concluding Remarks	p. 216
References	p. 217
Bioinformatics-Guided Experimental Characterization of Mismatch-Repair Enzymes and Their Relatives	p. 221
Introduction	p. 221
Sau3AI and Related Restriction Endonucleases	p. 222
DNA Mismatch Repair	p. 223
Nicking Endonuclease MutH	p. 224
Sau3AI - Similar Folds for N- and C-Terminal Domains	p. 225
Fold Recognition for the C-terminal of Sau3AI	p. 225
Biochemical and Biophysical Analysis - Evidence for a Pseudotetramer That Induces DNA Looping	p. 227
Identification of the Methylation Sensor of MutH	p. 232
Evolutionary Trace Analysis	p. 233
Superposition of MutH with REases in Complexes with DNA	p. 235
Mutational Analysis of MutH	p. 236
Conclusions	p. 238
References	p. 239
Predicting Functional Residues in DNA Glycosylases by Analysis of Structure and Conservation	p. 243
Introduction	p. 243
Generating Predictions: Sequence Selection and Analysis	p. 244
Testing the Predictions: Mutational Analysis of Residues Defining Substrate Specificity in Formamidopyrimidine-DNA Glycosylase	p. 251
Refining the Predictions: Analysis of Substrate Specificity in the Endonuclease III Family	p. 254
References	p. 259
Subject Index	p. 263
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Practical Bioinformatics

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