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Lipopolysaccharides (LPS) are major players in bacterial infection through the recognition by Toll-like receptor 4 (TLR4). The LPS chemical structure, including the oligosaccharide core and the lipid A moiety, can be strongly influenced by adaptation and modulated to assure bacteria protection, evade immune surveillance, or reduce host immune responses. Deep structural understanding of TLRs signaling is essential for the modulation of the innate immune system in sepsis control and inflammation, during bacterial infection. To advance this knowledge, we have employed computational techniques to characterize the TLR4 molecular recognition of atypical LPSs from different opportunistic members of α2-Proteobacteria, including Brucella melitensis, Ochrobactrum anthropi, and Ochrobactrum intermedium, with diverse immunostimulatory activities. We contribute to unraveling the role of uncommon lipid A chemical features such as bearing very long-chain fatty acid chains, whose presence has been rarely reported, on modulating the proper heterodimerization of the TLR4 receptor complex. Moreover, we further evaluated the influence of the different oligosaccharide cores, including sugar composition and net charge, on TLR4 activation. Our studies contribute to elucidating, from the molecular and biological perspectives, the impact of the α2-Proteobacteria LPS cores and the chemical structure of the atypical lipid A for immune system evasion in opportunistic bacteria.
Computational simulations, Lipopolysaccharides, Atypical lipopolysaccharides, Bacteria, immuno-evasion, molecular modeling, toll-like receptor 4, Molecular modeling, Oligosaccharides, Bacterial Infections, computational simulations, Biología y Biomedicina / Biología, Toll-like receptor 4, Toll-Like Receptor 4, Lipid A, Proteobacteria, Humans, Immuno-evasion, Immune Evasion
Computational simulations, Lipopolysaccharides, Atypical lipopolysaccharides, Bacteria, immuno-evasion, molecular modeling, toll-like receptor 4, Molecular modeling, Oligosaccharides, Bacterial Infections, computational simulations, Biología y Biomedicina / Biología, Toll-like receptor 4, Toll-Like Receptor 4, Lipid A, Proteobacteria, Humans, Immuno-evasion, Immune Evasion
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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