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[求助] 求助，建立的蛋白模型如何进行评价已有1人参与

请教各位师兄师姐，老师让对突变的酶进行同源建模，建模之后，应该如何进行评价呢，用什么专门的软件呢？？？

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1楼 2014-07-09 19:50:11

已阅回复此楼关注TA 给TA发消息送TA红花 TA的回帖

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【答案】应助回帖

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感谢参与，应助指数 +1
myprayer: 金币+2, 赠人玫瑰手有余香，分子生物期待你更多精彩。 2014-07-10 12:16:54

不是一两句话说得清楚，请见参考文献：

1.蛋白质结构预测实验指南
http://muchong.com/bbs/viewthread.php?tid=6363934&fpage=1&target=blank

2.Daniel John Rigden Edits, From Protein Structure to Function with  Bioinformatics,Springer Science,2009,
下载：http://muchong.com/bbs/viewthread.php?tid=6382178&fpage=1&target=blank

非常感谢原作者！也感谢电子版制作者和首发者！

Contents
Section I  Generating and Inferring Structures
1  Ab InitioProtein Structure Prediction...................................................  3
Jooyoung Lee, Sitao Wu, and Yang Zhang
1.1 Introduction .......................................................................................  3
1.2 Energy Functions ..............................................................................  5
1.2.1  Physics-Based Energy Functions ..........................................  5
1.2.2  Knowledge-Based Energy Function Combined
with Fragments .....................................................................  9
1.3 Conformational Search Methods ......................................................  13
1.3.1  Monte Carlo Simulations ......................................................  14
1.3.2 Molecular Dynamics .............................................................  15
1.3.3 Genetic Algorithm ................................................................  15
1.3.4 Mathematical Optimization ..................................................  16
1.4 Model Selection ................................................................................  16
1.4.1  Physics-Based Energy Function ...........................................  17
1.4.2  Knowledge-Based Energy Function .....................................  17
1.4.3  Sequence-Structure Compatibility Function .........................  18
1.4.4  Clustering of Decoy Structures .............................................  19
1.5  Remarks and Discussions .................................................................  19
2 Fold Recognition......................................................................................  27
Lawrence A. Kelley
2.1 Introduction .......................................................................................  27
2.1.1  The Importance of Blind Trials:
The CASP Competition ........................................................  28
2.1.2  Ab InitioStructure Prediction Versus
Homology Modelling ............................................................  28
2.1.3  The Limits of Fold Space ......................................................  30
2.1.4  A Note on Terminology: ‘Threading’
and ‘Fold Recognition’ .........................................................  31
2.2 Threading ..........................................................................................  31
ix
2.2.1 Knowledge-Based Potentials ................................................  32
2.2.2 Finding an Alignment ...........................................................  34
2.2.3 Heuristics for Alignment ......................................................  35
2.3  Remote Homology Detection Without Threading ............................  38
2.3.1  Using Predicted Structural Features .....................................  39
2.3.2  Sequence Profiles and Hidden Markov Models ....................  41
2.3.3  Fold Classification and Support Vector Machines ................  43
2.3.4 Consensus Approaches .........................................................  45
2.3.5  Traversing the Homology Network ......................................  45
2.4  Alignment Accuracy, Model Quality and Statistical
Significance .......................................................................................  47
2.4.1  Algorithms for Alignment Generation
and Assessment .....................................................................  47
2.4.2  Estimation of Statistical Significance ...................................  48
2.5  Tools for Fold Recognition on the Web ............................................  49
2.6 The Future .........................................................................................  50
3  Comparative Protein Structure Modelling............................................  57
András Fiser
3.1 Introduction .......................................................................................  57
3.1.1 Structure Determines Function .............................................  57
3.1.2  Sequences, Structures, Structural Genomics ........................  58
3.1.3  Approaches to Protein Structure Prediction ..........................  58
3.2  Steps in Comparative Protein Structure Modelling ..........................  60
3.2.1  Searching for Structures Related
to the Target Sequence ..........................................................  62
3.2.2 Selecting Templates ..............................................................  64
3.2.3  Sequence to Structure Alignment .........................................  65
3.2.4 Model Building .....................................................................  67
3.2.5 Model Evaluation ..................................................................  76
3.3  Performance of Comparative Modelling ...........................................  77
3.3.1  Accuracy of Methods ............................................................  77
3.3.2  Errors in Comparative Models ..............................................  78
3.4  Applications of Comparative Modelling ...........................................  80
3.4.1  Modelling of Individual Proteins ..........................................  80
3.4.2  Comparative Modelling and the Protein
Structure Initiative ................................................................  80
3.5 Summary ...........................................................................................  81
4  Membrane Protein Structure Prediction...............................................  91
Timothy Nugent and David T. Jones
4.1 Introduction .......................................................................................  91
4.2 Structural Classes ..............................................................................  92
x  Contents
4.2.1  Alpha-Helical Bundles .........................................................  92
4.2.2 Beta-Barrels ..........................................................................  92
4.3  Membrane Proteins Are Difficult to Crystallise ...............................  94
4.4 Databases ..........................................................................................  94
4.5  Multiple Sequence Alignments .........................................................  96
4.6  Transmembrane Protein Topology Prediction ..................................  98
4.6.1 Alpha-Helical Proteins ..........................................................  98
4.6.2 Beta-Barrel Proteins .............................................................. 102
4.6.3  Whole Genome Analysis ......................................................  102
4.6.4  Data Sets, Homology, Accuracy
and Cross-Validation .............................................................  103
4.7  3D Structure Prediction .....................................................................  105
4.8 Future Developments ........................................................................ 107
5  Bioinformatics Approaches to the Structure
and Function of Intrinsically Disordered Proteins...............................  113
Peter Tompa
5.1  The Concept of Protein Disorder ......................................................  113
5.2  Sequence Features of IDPs ...............................................................  115
5.2.1  The Unusual Amino Acid
Composition of IDPs ............................................................  115
5.2.2  Sequence Patterns of IDPs ....................................................  115
5.2.3  Low Sequence Complexity and Disorder .............................  116
5.3 Prediction of Disorder ....................................................................... 116
5.3.1  Prediction of Low-Complexity Regions ...............................  116
5.3.2 Charge-Hydropathy Plot ....................................................... 117
5.3.3 Propensity-Based Predictors ................................................. 117
5.3.4  Predictors Based on the Lack
of Secondary Structure ..........................................................  118
5.3.5 Machine Learning Algorithms .............................................. 119
5.3.6  Prediction Based on Contact Potentials ................................  120
5.3.7  A Reduced Alphabet Suffices
to Predict Disorder ................................................................  121
5.3.8  Comparison of Disorder Prediction Methods .......................  122
5.4 Functional Classification of IDPs .....................................................  122
5.4.1  Gene Ontology-Based Functional
Classification of IDPs ...........................................................  122
5.4.2  Classification of IDPs Based
on Their Mechanism of Action .............................................  123
5.4.3  Function-Related Structural Elements in IDPs .....................  126
5.5  Prediction of the Function of IDPs ...................................................  128
5.5.1  Correlation of Disorder Pattern and Function .......................  128
5.5.2  Predicting Short Recognition Motifs in IDRs .......................  128
5.5.3 Prediction of MoRFs ............................................................. 129
Contents  xi
5.5.4  Combination of Information on Sequence
and Disorder: Phosphorylation Sites
and CaM Binding Motifs ......................................................  131
5.5.5  Flavours of Disorder .............................................................  131
5.6  Limitations of IDP Function Prediction ............................................  132
5.6.1  Rapid Evolution of IDPs .......................................................  132
5.6.2  Sequence Independence of Function
and Fuzziness ........................................................................  133
5.6.3  Good News: Conservation and Disorder ..............................  134
5.7 Conclusions ....................................................................................... 135
Section II  From Structures to Functions
6  Function Diversity Within Folds and Superfamilies.............................  143
Benoit H. Dessailly and Christine A. Orengo
6.1 Defining Function .............................................................................  143
6.2  From Fold to Function ......................................................................  145
6.2.1  Definition of a Fold ...............................................................  145
6.2.2  Prediction of Function Using Fold
Relationships .........................................................................  148
6.3  Function Diversity Between Homologous Proteins ..........................  151
6.3.1 Definitions ............................................................................. 151
6.3.2  Evolution of Protein Superfamilies .......................................  152
6.3.3  Function Divergence During Protein Evolution ...................  154
6.4 Conclusion ........................................................................................ 162
7  Predicting Protein Function from Surface Properties..........................  167
Nicholas J. Burgoyne and Richard M. Jackson
7.1 Surface Descriptions ......................................................................... 167
7.1.1  The van der Waals Surface ....................................................  167
7.1.2  Molecular Surface (Solvent Excluded Surface) ....................  168
7.1.3  The Solvent Accessible Surface ............................................  168
7.2 Surface Properties ............................................................................. 169
7.2.1 Hydrophobicity ..................................................................... 169
7.2.2 Electrostatics Properties ........................................................ 170
7.2.3 Surface Conservation ............................................................ 171
7.3  Function Predictions Using Surface Properties ................................  171
7.3.1 Hydrophobic Surface ............................................................ 172
7.3.2 Electrostatic Surface ............................................................. 172
7.3.3 Surface Conservation ............................................................ 173
7.3.4 Combining Surface Properties
for Function Prediction .........................................................  174
7.4 Protein-Ligand Interactions .............................................................. 174
7.4.1  Properties of Protein-Ligand Interactions .............................  174
xii  Contents
7.4.2  Predicting Binding Site Locations ........................................  175
7.4.3 Predictions of Druggability ................................................... 178
7.4.4  Annotation of Ligand Binding Sites .....................................  178
7.5 Protein-Protein Interfaces ................................................................. 180
7.5.1  Properties of Protein-Protein Interfaces ................................  180
7.5.2  Hot-Spot Regions in Protein Interfaces ................................  181
7.5.3  Predictions of Interface Location ..........................................  182
7.6 Summary ........................................................................................... 184
8 3D Motifs...................................................................................................  187
Elaine C. Meng, Benjamin J. Polacco,
and Patricia C. Babbitt
8.1 Background and Significance ...........................................................  188
8.1.1  What Is Function? .................................................................  189
8.1.2  Three-Dimensional Motifs: Definition
and Scope ..............................................................................  190
8.2  Overview of Methods ........................................................................  190
8.2.1 Motif Discovery .................................................................... 190
8.2.2  Motif Description and Matching ...........................................  191
8.2.3 Interpretation of Results ........................................................ 193
8.3 Specific Methods ...............................................................................  196
8.3.1 User-Defined Motifs ............................................................. 197
8.3.2 Motif Discovery .................................................................... 201
8.4 Related Methods ............................................................................... 208
8.4.1  Hybrid (Point-Surface) Descriptions ....................................  208
8.4.2 Single-Point-Centred Descriptions ....................................... 208
8.5  Docking for Functional Annotation ..................................................  210
8.6 Discussion ......................................................................................... 212
8.7 Conclusions ....................................................................................... 212
9  Protein Dynamics: From Structure to Function...................................  217
Marcus B. Kubitzki, Bert L. de Groot,
and Daniel Seeliger
9.1 Molecular Dynamics Simulations ..................................................... 217
9.1.1 Principles and Approximations ............................................. 218
9.1.2 Applications .......................................................................... 220
9.1.3  Limitations – Enhanced Sampling
Algorithms ............................................................................  226
9.2  Principal Component Analysis .........................................................  230
9.3  Collective Coordinate Sampling Algorithms ....................................  233
9.3.1 Essential Dynamics ............................................................... 233
9.3.2 TEE-REX .............................................................................. 234
9.4  Methods for Functional Mode Prediction .........................................  237
9.4.1 Normal Mode Analysis ......................................................... 237
Contents  xiii
9.4.2 Elastic Network Models .................................................. 238
9.4.3 CONCOORD .................................................................. 239
9.5 Summary and Outlook .................................................................. 242
10  Integrated Servers for Structure-Informed
Function Prediction...............................................................................  251
Roman A. Laskowski
10.1 Introduction ................................................................................... 251
10.1.1  The Problem of Predicting Function
from Structure .................................................................  252
10.1.2 Structure-Function Prediction
Methods ..........................................................................  253
10.2 ProKnow ....................................................................................... 254
10.2.1 Fold Matching ................................................................. 254
10.2.2 3D Motifs ........................................................................ 256
10.2.3 Sequence Homology ....................................................... 257
10.2.4 Sequence Motifs ............................................................. 257
10.2.5 Protein Interactions ......................................................... 258
10.2.6 Combining the Predictions .............................................. 258
10.2.7 Prediction Success .......................................................... 258
10.3 ProFunc ......................................................................................... 259
10.3.1  ProFunc’s Structure-Based Methods ..............................  259
10.3.2  Assessment of the Structural Methods ............................  267
10.4 Conclusion .................................................................................... 269
11  Case Studies: Function Predictions of Structural
Genomics Results...................................................................................  273
James D. Watson and Janet M. Thornton
11.1 Introduction ................................................................................... 273
11.2  Large Scale Function Prediction
Case Studies ..................................................................................  275
11.3 Some Specific Examples ...............................................................  281
11.4 Community Annotation ................................................................ 287
11.5 Conclusions ................................................................................... 288
12  Prediction of Protein Function from
Theoretical Models.................................................................................  293
Iwona A. Cymerman, Daniel J. Rigden,
and Janusz M. Bujnicki
12.1 Background ................................................................................... 293
12.2  Protein Models as a Community Resource ...................................  295
12.2.1 Model Quality ................................................................. 296
12.2.2  Databases of Models .......................................................  297
xiv  Contents
12.3  Accuracy and Added Value of Model-Derived
Properties ......................................................................................  298
12.3.1 Implementation ............................................................... 300
12.4 Practical Application ..................................................................... 302
12.4.1  Plasticity of Catalytic Site Residues ...............................  302
12.4.2 Mutation Mapping .......................................................... 304
12.4.3 Protein Complexes .......................................................... 305
12.4.4 Function Predictions from
Template-Free Models ....................................................  306
12.4.5  Prediction of Ligand Specificity .....................................  309
12.4.6  Structure Modelling of Alternatively
Spliced Isoforms .............................................................  310
12.4.7  From Broad Function to Molecular Details ....................  312
12.5 What Next? ................................................................................... 314
Index.................................................................................................................  319

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