Sending Innate Immune Signals Across the Membrane: A Multiscale Simulation Approach to Toll-Like Receptor Assembly
Sending Innate Immune Signals Across the Membrane: A Multiscale Simulation Approach to Toll-Like Receptor Assembly
Toll-like receptors (TLRs) are single transmembrane-spanning proteins that sense pathogenic molecular patterns within the innate immune system. Upon activation, TLRs form homodimers or heterodimers and initiate immune response pathways. The ability of TLRs to dimerize is therefore critical to their function in responding to invading pathogens. Crystallographic structures have been solved for the ectodomains of various TLR homodimers, but high-resolution structural information is not available for the full-length proteins, or for the transmembrane (TM) regions. We performed ab-initio modelling of the TM regions of all ten human TLRs, based on secondary structural predictions and spectroscopic data. Subsequently, coarse grained (CG) molecular dynamics (MD) simulations were performed to follow assembly and homo/hetero-dimerization within a phospholipid membrane environment. Our results have been used to evaluate the stability of TLR dimers, and to identify key sequence motifs that stabilize TM interactions, helping to rationalize in vitro data. Using acceptor photobleaching FRET on live cells, it has been demonstrated that TM domains including TLR2-TLR1 and TLR2-TLR6 interact within the plasma membrane. Additionally, multiscale models of entire TLR receptors have been built to determine the link between ligand recognition, assembly and cross-membrane/downstream signaling. In particular, we have focused on TLR4, which recognizes lipopolysaccharide (LPS) from the outer membranes of Gram-negative bacteria, for which a variety of structural/biophysical and MD data are available. Modelling of mutant constructs containing variable linkers revealed the structural basis for experimentally demonstrated tight coupling between extra- and intra-cellular domains and the TM region, based on receptor stability and dimerization efficiency. These data improve our understanding of the assembly and signalling mechanisms in TLRs, and may facilitate design of ligands with specific immunomodulatory properties, paving the way for new therapeutic treatments of inflammatory diseases.
- Bioinformatics Institute Singapore
- University of Salford United Kingdom
- National University of Singapore Singapore
- University of Colorado Boulder United States
- Agency for Science, Technology and Research Singapore
Biophysics
Biophysics
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