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Characterization, classification and alignment of protein-protein interfaces [Elektronische Ressource] / Zhu, Hongbo

187 pages
Characterization, Classi cation and Alignmentof Protein-Protein InterfacesZhu, HongboA DissertationSubmitted to the Faculty ofNatural Sciences and Technology IMathematics and Computer ScienceSaarland UniversityIn Partial Ful llment of theRequirements for the Degree ofDoktor der Naturwissenschaften (Dr. rer. nat.)Saarbruc ken2010Date of Colloquium: 24-06-2010Dean of the Faculty: Prof. Dr. Holger HermannsChairman: Prof. Dr. Hans-Peter LenhofDoctorate Committee Members: Prof. Dr. Dr. Thomas LengauerProf. Dr. Peter LacknerTo my parents.viiAbstractProtein structural models provide essential information for the research on protein-protein interactions. In this dissertation, we describe two projects on the analysis ofprotein interactions using structural information. The focus of the rst is to charac-terize and classify di erent types of interactions. We discriminate between biologicalobligate and biological non-obligate interactions, and crystal packing contacts. Tothis end, we de ned six interface properties and used them to compare the threetypes of interactions in a hand-curated dataset. Based on the analysis, a classi- er, named NOXclass, was constructed using a support vector machine algorithmin order to generate predictions of interaction types. NOXclass was tested on anon-redundant dataset of 243 protein-protein interactions and reaches an accuracyof 91.8%.
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Characterization, Classi cation and Alignment
of Protein-Protein Interfaces
Zhu, Hongbo
A Dissertation
Submitted to the Faculty of
Natural Sciences and Technology I
Mathematics and Computer Science
Saarland University
In Partial Ful llment of the
Requirements for the Degree of
Doktor der Naturwissenschaften (Dr. rer. nat.)
Saarbruc ken
2010Date of Colloquium: 24-06-2010
Dean of the Faculty: Prof. Dr. Holger Hermanns
Chairman: Prof. Dr. Hans-Peter Lenhof
Doctorate Committee Members: Prof. Dr. Dr. Thomas Lengauer
Prof. Dr. Peter LacknerTo my parents.vii
Abstract
Protein structural models provide essential information for the research on protein-
protein interactions. In this dissertation, we describe two projects on the analysis of
protein interactions using structural information. The focus of the rst is to charac-
terize and classify di erent types of interactions. We discriminate between biological
obligate and biological non-obligate interactions, and crystal packing contacts. To
this end, we de ned six interface properties and used them to compare the three
types of interactions in a hand-curated dataset. Based on the analysis, a classi-
er, named NOXclass, was constructed using a support vector machine algorithm
in order to generate predictions of interaction types. NOXclass was tested on a
non-redundant dataset of 243 protein-protein interactions and reaches an accuracy
of 91.8%. The program is bene cial for structural biologists for the interpretation of
protein quaternary structures and to form hypotheses about the nature of protein- interactions when experimental data are yet unavailable.
In the second part of the dissertation, we present Galinter, a novel program for
the geometrical comparison of protein-protein interfaces. The Galinter aims
at identifying similar patterns of di erent non-covalent interactions at interfaces. It
is a graph-based approach optimized for aligning non-covalent interactions. A scor-
ing scheme was developed for estimating the statistical signi cance of the alignments.
We tested the Galinter method on a published dataset of interfaces. Galinter align-
ments agree with those delivered by methods based on interface residue comparison
and backbone structure comparison. In addition, we applied Galinter on four medi-
cally relevant examples of protein mimicry. Our results are consistent with previous
human-curated analysis. The Galinter program provides an intuitive method of com-
parative analysis and visualization of binding modes and may assist in the prediction
of interaction partners, and the design and engineering of protein interactions and
in inhibitors.viii
Acknowledgements
The work presented in the dissertation had been carried out in the group of Com-
putational Biology and Applied Algorithmics at the Max-Planck-Institute for Infor-
matics in Saarbruc ken. First, I would like to express my gratitude to the group
leader and my supervisor Professor Dr. Dr. Thomas Lengauer for his guidance dur-
ing my research studies. He had provided me with generous support, advice and
encouragement, which are indispensable for me to nish my work.
The research has been performed under the guidance of Francisco Domingues and
Ingolf Sommer. I would like to thank them for their invaluable advice to my work.
The discussions with them were always inspiring and fruitful, the time spent with
them was indeed great and unforgettable.
The work had bene ted from helpful discussions with many colleagues. Thanks
to Oliver Sander, Gabriele Mayr, J org Rahnenfuhrer, Andreas Ste en, and Tobias
Sing for their expertise and the discussions with them on work.
I want to thank all group members for the unique stimulating and friendly working
atmosphere. The discussions and conversations with them make my stay in the group
a colorful memory.
I want to thank Dr. Joachim Buc h and Ruth Schneppen-Christmann for their
support and help with many technical, administrative and other problems.
Finally, I would like to thank my family and friends for their constant support,
especially my wife Dongmei and my parents.Contents
1 Introduction 1
1.1 Protein-Protein Interactions . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1 Introduction to Proteins . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Identification of Protein-Protein Interactions . . . . . . . . . . 3
1.1.3 Inference of Interactions . . . . . . . . . . . . 8
1.1.4 Management and Analysis of Interaction Data . . . . . . . . 13
1.1.5 Classification of Protein-Protein Interactions . . . . . . . . . . 16
1.2 Structure Models of Protein Complexes . . . . . . . . . . . . . . . . 19
1.2.1 Determination of Protein Structures . . . . . . . . . . . . . . 19
1.2.2 Crystal Packing in Structure Models . . . . . . . . . . 24
1.2.3 Binding Sites and Interfaces . . . . . . . . . . . . . . . . . . . 28
1.3 Outline of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . 34
2 Characterization and Prediction of Protein-Protein Interaction Types 37
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.2 Characterization of Protein-Protein Interactions . . . . . . . . . . . . 40
2.2.1 Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.2.2 Definition of Interfaces Properties . . . . . . . . . . . . . . . 42
2.2.3 Analysis of Interface Properties . . . . . . . . . . . . . . . . . 47
2.3 Classification of Protein-Protein Interactions . . . . . . . . . . . . . . 53
2.3.1 Machine Learning Techniques related to Classification . . . . 53
2.3.2 Classification Methods . . . . . . . . . . . . . . . . . . . . . . 59
2.3.3 Performance Measures . . . . . . . . . . . . . . . . . . . . . 60
2.3.4 Results . . . . . . . . . . . . . . . . . . . . . . 61
2.3.5 Classification Using Atomic Contact Vectors . . . . . . . . . . 68
2.3.6 NOXclass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
2.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
2.4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
2.4.2 Related Work after NOXclass . . . . . . . . . . . . . . . . . . 76
2.4.3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
ixx CONTENTS
3 Alignment of Non-covalent Interactions at Protein-Protein Interfaces 81
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
3.1.3 Detection of Structural Similarity . . . . . . . . . . . . . . . . 87
3.2 Alignment of Non-Covalent Interactions . . . . . . . . . . . . . . . . 91
3.2.1 Alignment Algorithm . . . . . . . . . . . . . . . . . . . . . . . 91
3.2.2 Validation of Alignment Algorithm . . . . . . . . . . . . . . . . 100
3.2.3 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
3.3 Scoring of Alignments . . . . . . . . . . . . . . . . . . . . . . . . . . 117
3.3.1 The Poisson Index . . . . . . . . . . . . . . . . . . . . . . . . 117
3.3.2 Parameter Estimation for Poisson Index . . . . . . . . . . . . 119
3.3.3 Database Scans using Poisson Index . . . . . . . . . . . . . 128
3.4 Galinter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
4 Summary and Outlook 141
4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
4.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Appendices 147
A List of Publications 147
Bibliography 149

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