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Wei, Tiandi (2010): Homology Modeling of Toll-Like Receptor Ligand-Binding Domains: A Leucine-Rich Repeat Assembly Approach. Dissertation, LMU München: Faculty of Geosciences
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Abstract

Toll-like receptors (TLRs) are in the front-line during the initiation of an innate immune response against invading pathogens. TLRs are type I transmembrane proteins that are expressed on the surface of immune system cells. They are evolutionarily conserved between insects and vertebrates. To date, 13 groups of mammalian TLRs have been identified, ten in humans and 13 in mice. They share a modular structure that consists of a leucine-rich repeat (LRR) ectodomain, a single transmembrane helix and a cytoplasmic Toll/interleukin-1 receptor (TIR) domain. Most TLRs have been shown to recognize pathogen-associated molecular patterns (PAMPs) from a wide range of invading agents and initiate intracellular signal transduction pathways to trigger expression of genes, the products of which can control innate immune responses. The TLR signaling pathways, however, must be under tight negative regulation to maintain immune balance because over-activation of immune responses in the body can cause autoimmune diseases. The TLR ectodomains are highly variable and are directly involved in ligand recognition. So far, crystal structures are missing for most TLR ectodomains because structure determination by X-ray diffraction or nuclear magnetic resonance (NMR) spectroscopy experiments remains time-consuming, and sometimes the crystallization of a protein can be very difficult. Computational modeling enables initial predictions of three-dimensional structures for the investigation of receptor-ligand interaction mechanisms. Computational methods are also helpful to develop new TLR agonists and antagonists that have therapeutic significance for diseases. In this dissertation, an LRR template assembly approach for homology modeling of TLR ligand-binding domains is discussed. To facilitate the modeling work, two databases, TollML and LRRML, have been established. With this LRR template assembly approach, the ligand-binding domains of human TLR5-10 and mouse TLR11-13 were modeled. Based on the models of human TLR7, 8 and 9, we predicted potential ligand-binding residues and possible configurations of the receptor-ligand complex using a combined procedure. In addition, we modeled the cytoplasmic TIR domains of TLR4 and 7, the TLR adaptor protein MyD88 (myeloid differentiation primary response protein 88) and the TLR inhibitor SIGIRR (Single immunoglobulin interleukin-1 receptor-related molecule) to investigate the structural mechanism of TLR negative regulation.