Databases and computational interaction models of toll-like receptors [Elektronische Ressource] / vorgelegt von Jing Gong

Jing Gong

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2010
• Nombre de lectures: 11
• Langue: English
• Poids de l'ouvrage: 9 Mo

Extrait

Databases and computational
interaction models of Toll-like receptors


Dissertation
Fakultät für Geowissenschaften
Ludwig-Maximilians-Universität München





vorgelegt von
Jing Gong
München, den 24. Februar 2010

















Erstgutachter: Prof. Dr. Wolfgang M. Heckl
Zweitgut. Robert W. Stark
Prüfungstermin: 26.05.2010 Abstract
Abstract
Toll-like receptors (TLRs) recognize pathogen-associated molecular patterns (PAMPs)
on invading organisms and are the first line of defense in innate immunity. To date,
much has been learned about TLRs and their roles in autoimmune diseases are being
unraveled. The autoimmune disease systemic lupus erythematosus (SLE) progresses
as a consequence of the inappropriate recognition of self nucleic acids by TLRs. For
the development of therapeutic approaches of SLE it is necessary to understand
possible negative regulation mechanisms of TLR. Single immunoglobulin
interleukin-1 receptor-related molecule (SIGIRR) is the best characterized TLR
signaling inhibitor. It can interfere with the receptor complexes and attenuate the
recruitment of downstream adaptors to the receptors. So far, the mechanisms of
structural interactions between SIGIRR, TLRs and adaptor molecules are unknown.
To develop a working hypothesis for these interactions, we constructed three-
dimensional models for these single molecules based on computational predictions.
Then, models of essential complexes involved in the TLR signaling and the SIGIRR
inhibiting processes were yielded through protein-protein docking analysis.
With the high-throughput genome sequencing projects, a central repository for the
growing amount of TLR sequence information has been created. However, subsequent
annotations for these TLR sequences are incomplete. For example, the indicated
numbers and positions of leucine-rich repeat (LRR) motifs contained in individual
TLR ectodomains are greatly distinct or missing in established databases. In this vein,
we have developed a database of TLR structural motifs called TollML
(http://tollml.lrz.de). It integrates all TLR protein sequences that have been identified
to date. These sequences were semi-automatically partitioned into three levels of
structural motif categories. The manual motif identification procedure provided
TollML with the most complete and accurate database of LRR motifs compared with
other databases that contain TLR data.
LRR motifs are present not only in TLRs, but also in many other proteins. To date,
more than 6,000 LRR protein sequences and more than 130 crystal structures of them
have been determined. This knowledge has increased our ability to use individual
LRR structures extracted from the crystal structures as building blocks to model LRR
proteins with unknown structures. Because the individual LRR structures are not
directly available from any protein structure database, we have developed a
conformational LRR database called LRRML (http://lrrml.lrz.de). It collects three-
dimensional LRR structures manually identified from all determined crystal structures
of LRR-containing proteins and thus provides a source for the structural modeling and
analysis of LRR proteins. With the help of TollML and LRRML, we constructed
models of the human/mouse TLR5-13 ectodomains and suggested some potential
receptor-ligand interaction residues based on these models.
1 Abstract











2 Contents
Contents
ABSTRACT............................................................................................................................................ 1
CONTENTS.................... 3
1. INTRODUCTION.............................................................................................................................. 5
2. IMMUNE DISEASES AND TOLL-LIKE RECEPTORS .............................................................. 7
2.1 IMMUNE SYSTEM AND IMMUNE DISEASES....................................................................................... 7
2.2 TOLL-LIKE RECEPTORS IN INNATE IMMUNITY ................................................................................. 8
3. BIOLOGICAL DATABASES .........................................................................................................17
3.1 APPLICATION OF BIOLOGICAL DATABASES .................................................................................... 17
3.2 DATA STORAGE AND MANAGEMENT IN DATABASES....................................................................... 18
4. PROTEIN STRUCTURE PREDICTION ..................................................................................... 21
4.1 MOTIF IDENTIFICATION OF TLRS.................................................................................................. 21
4.2 PROTEIN STRUCTURE PREDICTION THEORIES................................................................................ 22
4.3 STRUCTURE PREDICTION OF SIGIRR............................................................................................ 24
4.4 HOMOLOGY MODELING OF TLR ECTODOMAINS ........................................................................... 25
5. METHODS ....................................................................................................................................... 27
5.1 DATABASE CONSTRUCTION........................................................................................................... 27
5.2 PROTEIN STRUCTURE PREDICTION ................................................................................................ 27
5.3 PROTEIN MODEL QUALITY ASSESSMENT....................................................................................... 28
5.4 PROTEIN-PROTEIN DOCKING......................................................................................................... 29
5.5 PROTEIN STRUCTURE VISUALIZATION AND ANALYSIS ................................................................... 29
6. RESULTS (EXTENDED ABSTRACTS OF MANUSCRIPTS)................................................... 31
6.1 PAPER 1: TOLLML: A DATABASE OF TOLL-LIKE RECEPTOR STRUCTURAL MOTIFS ......................... 31
6.2 PAPER 2: LRRML: A CONFORMATIONAL DATABASE AND AN XML DESCRIPTION OF LEUCINE-RICH
REPEATS (LRRS) ................................................................................................................................ 32
6.3 PAPER 3: INHIBITION OF TOLL-LIKE RECEPTORS TLR4 AND 7 SIGNALING PATHWAYS BY SIGIRR: A
COMPUTATIONAL APPROACH .............................................................................................................. 33
6.4 PAPER 4: LACK OF SIGIRR/TIR8 AGGRAVATES HYDROCARBON OIL-INDUCED SYSTEMIC LUPUS.. 35
6.5 PAPER 5: HOMOLOGY MODELING OF HUMAN TOLL-LIKE RECEPTORS TLR7, 8 AND 9
LIGAND-BINDING DOMAINS ................................................................................................................ 35
6.6 PAPER 6: A LEUCINE-RICH REPEAT ASSEMBLY APPROACH FOR HOMOLOGY MODELING OF HUMAN
3 Contents
TLR5-10 AND MOUSE TLR11-13 ECTODOMAINS ............................................................................... 36
7. CONCLUSIONS .............................................................................................................................. 37
REFERENCES..................................................................................................................................... 39
ACKNOWLEDGEMENT................................................................................................................... 47
APPENDIX........................................................................................................................................... 49
PAPER 1.............................................................................................................................................. 49
PAPER 2................ 57
PAPER 3................ 67
PAPER 4................ 76
PAPER 5................ 89
PAPER 6................ 98
CV ....................................................................................................................................................117

4 Introduction
1. Introduction
The recognition of invading pathogenic organisms is critical in the proper activation
of the immune system [1]. Inappropriate activation may cause immunodeficiency
diseases and autoimmune diseases. The immune system consists of the antigen
-unspecific innate immune system and the antigen-specific adaptive immune system.
Toll-like receptors (TLRs) are responsible for the innate immunity. They recognize a
wide variety of pathogen-associated molecular patterns (PAMPs) via their extracellular
domains, acting to trigger intracellular signaling pathways [2]. In the signaling
pathways, the association of receptors and downstream adaptors leads to the induction
of inflammatory cytokines. Nevertheless, excessive production of cytokines
contributes to the pathogenesis of autoimmune diseases [3]. TLR signaling must
therefore be under tight negative regulation to maintain an immune balance. The
single immunoglobulin interleukin-1 rec