TollML: a database of toll-like receptor structural motifs

Ancient fish lineages illuminate toll-like receptor diversification in early vertebrate evolution

Since its initial discovery over 50 years ago, understanding the evolution of the vertebrate RAG- mediated adaptive immune response has been a major area of research focus for comparative geneticists. However, how the evolutionary novelty of an adaptive immune response impacted the diversity of receptors associated with the innate immune response has received considerably less attention until recently. Here, we investigate the diversification of vertebrate toll-like receptors (TLRs), one of the most ancient and well conserved innate immune receptor families found across the Tree of Life, integrating genomic data that represent all major vertebrate lineages with new transcriptomic data from Polypteriformes, the earliest diverging ray-finned fish lineage. Our analyses reveal TLR sequences that reflect the 6 major TLR subfamilies, TLR1, TLR3, TLR4, TLR5, TLR7, and TLR11, and also currently unnamed, yet phylogenetically distinct TLR clades. We additionally recover evidence for a pulse of gene gain coincident with the rise of the RAG-mediated adaptive immune response in jawed vertebrates, followed by a period of rapid gene loss during the Cretaceous. These gene losses are primarily concentrated in marine teleost fish and synchronous with the mid Cretaceous anoxic event, a period of rapid extinction for marine species. Finally, we reveal a mismatch between phylogenetic placement and gene nomenclature for up to 50% of TLRs found in clades such as ray-finned fishes, cyclostomes, amphibians, and elasmobranchs. Collectively, these results provide an unparalleled perspective of TLR diversity and offer a ready framework for testing gene annotations in non-model species.

Host-pathogen protein-nucleic acid interactions: A comprehensive review

Recognition of pathogen-derived nucleic acids by host cells is an effective host strategy to detect pathogenic invasion and trigger immune responses. In the context of pathogen-specific pharmacology, there is a growing interest in mapping the interactions between pathogen-derived nucleic acids and host proteins. Insight into the principles of the structural and immunological mechanisms underlying such interactions and their roles in host defense is necessary to guide therapeutic intervention. Here, we discuss the newest advances in studies of molecular interactions involving pathogen nucleic acids and host factors, including their drug design, molecular structure and specific patterns. We observed that two groups of nucleic acid recognizing molecules, Toll-like receptors (TLRs) and the cytoplasmic retinoic acid-inducible gene (RIG)-I-like receptors (RLRs) form the backbone of host responses to pathogen nucleic acids, with additional support provided by absent in melanoma 2 (AIM2) and DNA-dependent activator of Interferons (IFNs)-regulatory factors (DAI) like cytosolic activity. We review the structural, immunological, and other biological aspects of these representative groups of molecules, especially in terms of their target specificity and affinity and challenges in leveraging host-pathogen protein-nucleic acid interactions (HP-PNI) in drug discovery.

Synthesis and characterization of new potent TLR7 antagonists based on analysis of the binding mode using biomolecular simulations

Aberrant activation of the endosomal Toll-like receptor 7 (TLR7) has been implicated in myriad autoimmune diseases and is an established therapeutic target in such conditions. Development of diverse TLR7 antagonists is mainly accomplished through random screening. To correlate human TLR7 (hTLR7) antagonistic activity with the structural features in different chemotypes, we derived a hypothetical binding model based on molecular docking analysis along with molecular dynamics (MD) simulations study. The binding hypothesis revealed different pockets, grooves and a central cavity where ligand-receptor interaction with specific residues through hydrophobic and hydrogen bond interactions take place, which correlate with TLR7 antagonistic activity thus paving the way for rational design using varied chemotypes. Based on the structural insight thus gained, TLR7 antagonists with quinazoline were designed to understand the effect of engagement of these pockets as well as boundaries of the chemical space associated with them. The newly synthesized most potent hTLR7 antagonist, i.e. compound 63, showed IC₅₀ value of 1.03 ± 0.05 μM and was validated by performing primary assay in human plasmacytoid dendritic cells (pDC) (IC₅₀^pDC: 1.42 μM). The biological validation of the synthesized molecules was performed in TLR7-reporter HEK293 cells as well as in human plasmacytoid dendritic cells (pDCs). Our study provides a rational design approach thus facilitating further development of novel small molecule hTLR7 antagonists based on different chemical scaffolds.

Identification, characterization and expression analysis of TLR5 in the mucosal tissues of turbot (Scophthalmus maximus L.) following bacterial challenge

TLRs (Toll-like receptors) are very important pathogen pattern recognition receptors, which control the host immune responses against pathogens through recognition of molecular patterns specific to microorganisms. In this regard, investigation of the turbot TLRs could help to understand the immune responses for pathogen recognition. Here, transcripts of two TLR5 (TLR5a and TLR5b) were captured, and their protein structures were also predicted. Meanwhile, we characterized their expression patterns with emphasis on mucosal barriers following different bacterial infection. The phylogenetic analysis revealed the turbot TLR5 genes showed the closest relationship to Paralichthys olivaceus. These two TLR5 genes were ubiquitously expressed in healthy tissues although expression levels varied among the tested tissues. In addition, the two copies of turbot TLR5 showed different expression patterns after bacterial infections. After Vibrio anguillarum infection, TLR5a was generally up-regulated in intestine and skin while down-regulated in gill, while TLR5b showed a general down-regulation in mucosal tissues. After Streptococcus iniae infection, the TLR5a was down-regulated at 2 h while generally up-regulated after 4 h in mucosal tissues. Interestingly, the TLR5b was up-regulated in intestine while down-regulated in skin and gill after Streptococcus iniae infection. These findings suggested a possible irreplaceable role of TLR5 in the immune responses to the infections of a broad range of pathogens that include Gram-negative and Gram-positive bacteria. Future studies should apply the bacteriological and immune-histochemical techniques to study the main sites on the mucosal tissue for bacteria entry and identify the ligand specificity of the turbot TLRs after challenge.

Structure modeling of Toll-like receptors

Toll-like receptors (TLRs) recognize invasion of microbial pathogens and initiate innate immune responses that are essential for inhibiting pathogen dissemination and for the development of acquired immunity. To understand how these receptors work, it is crucial to investigate them from a structural perspective. High-throughput genome sequencing projects have led to the identification of more than 3,000 TLR sequences. However, only several structures of TLRs have been determined because structure determination by X-ray diffraction or nuclear magnetic resonance spectroscopy experiments remains difficult and time-consuming. Protein structure modeling methods are powerful tools for bridging the gap between sequence determination and structure determination. Due to different repeat numbers and distinct arrangements of leucine-rich repeats (LRRs) contained in TLR ectodomains, an automated homology modeling method often failed to predict a proper model. Here, we describe an LRR template assembly method for homology modeling of TLRs. This method was successfully validated through the comparison of a predicted model with the crystal structures, and showed better performance than other Protein structure modeling tools. The resulting models can be used to perform protein-ligand interaction studies or to design mutagenesis experiments, and hence to investigate TLR ligand-binding mechanisms.

Toll-like receptor 7 agonists: chemical feature based pharmacophore identification and molecular docking studies

Chemical feature based pharmacophore models were generated for Toll-like receptors 7 (TLR7) agonists using HypoGen algorithm, which is implemented in the Discovery Studio software. Several methods tools used in validation of pharmacophore model were presented. The first hypothesis Hypo1 was considered to be the best pharmacophore model, which consists of four features: one hydrogen bond acceptor, one hydrogen bond donor, and two hydrophobic features. In addition, homology modeling and molecular docking studies were employed to probe the intermolecular interactions between TLR7 and its agonists. The results further confirmed the reliability of the pharmacophore model. The obtained pharmacophore model (Hypo1) was then employed as a query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit was identified as a potent TLR7 agonist, which has antiviral activity against hepatitis virus in vitro. Therefore, our current work provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 agonists with desired biological activity.

Comparative analysis of species-specific ligand recognition in Toll-like receptor 8 signaling: a hypothesis

Toll-like receptors (TLRs) play a central role in the innate immune response by recognizing conserved structural patterns in a variety of microbes. TLRs are classified into six families, of which TLR7 family members include TLR7, 8, and 9, which are localized to endolysosomal compartments recognizing viral infection in the form of foreign nucleic acids. In our current study, we focused on TLR8, which has been shown to recognize different types of ligands such as viral or bacterial ssRNA as well as small synthetic molecules. The primary sequences of rodent and non-rodent TLR8s are similar, but the antiviral compound (R848) that activates the TLR8 pathway is species-specific. Moreover, the factors underlying the receptor's species-specificity remain unknown. To this end, comparative homology modeling, molecular dynamics simulations refinement, automated docking and computational mutagenesis studies were employed to probe the intermolecular interactions between this anti-viral compound and TLR8. Furthermore, comparative analyses of modeled TLR8 (rodent and non-rodent) structures have shown that the variation mainly occurs at LRR14-15 (undefined region); hence, we hypothesized that this variation may be the primary reason for the exhibited species-specificity. Our hypothesis was further bolstered by our docking studies, which clearly showed that this undefined region was in close proximity to the ligand-binding site and thus may play a key role in ligand recognition. In addition, the interface between the ligand and TLR8s varied depending upon the amino acid charges, free energy of binding, and interaction surface. Therefore, our current work provides a hypothesis for previous in vivo studies in the context of TLR signaling.

Similar Structures but Different Roles - An Updated Perspective on TLR Structures

Toll-like receptors (TLRs) are pattern recognition receptors that recognize conserved structures in pathogens, trigger innate immune responses, and prime antigen-specific adaptive immunity. Elucidation of crystal structures of TLRs interacting with their ligands such as TLR1-2 with triacylated lipopeptide, TLR2-6 with diacylated lipopeptide, TLR4-MD-2 with LPS, and TLR3 with double-stranded RNA (dsRNA) have enabled an understanding of the initiation of TLR signaling. Agonistic ligands such as LPS, dsRNA, and lipopeptides induce "m" shaped TLR dimers in which C-termini converge at the center. Such central convergence is necessary to bring the two intracellular receptor TIR domains closer together and promote their dimerization, which serves as an essential step in downstream signaling. In this review, we summarize TLR ECD structures that have been reported to date with special emphasis on ligand recognition and activation mechanism.

Porcine Toll-like receptors: recognition of Salmonella enterica serovar Choleraesuis and influence of polymorphisms

Salmonella enterica serovar Choleraesuis (SC) is a highly invasive pathogen that causes enteric and septicemic diseases in pigs. Although there have been some reports on gene expression profiles in the course of infection with SC in pigs, little is known about the genes involved in the infection. By measuring activation, as represented by nuclear factor-κB activity, after stimulation by the pathogen, we showed the involvement of Toll-like receptor (TLR) 5 and the TLR2-TLR1 heterodimer in the recognition of SC. We previously found single nucleotide polymorphisms (SNPs) in the TLRs of various pig populations. Here we demonstrated that the polymorphisms resulting in amino acid changes TLR5(R148L), TLR5(P402L), and TLR2(V703M) attenuated the responses to SC by the cells transfected with the TLR genes. Each of these three SNPs was differently restricted in distribution among breeds. These results suggest that there are differences in resistance to salmonellosis among breeds; these differences may be of great importance for the pig industry in terms of breeding and vaccine development.

Controlling the response: predictive modeling of a highly central, pathogen-targeted core response module in macrophage activation

We have investigated macrophage activation using computational analyses of a compendium of transcriptomic data covering responses to agonists of the TLR pathway, Salmonella infection, and manufactured amorphous silica nanoparticle exposure. We inferred regulatory relationship networks using this compendium and discovered that genes with high betweenness centrality, so-called bottlenecks, code for proteins targeted by pathogens. Furthermore, combining a novel set of bioinformatics tools, topological analysis with analysis of differentially expressed genes under the different stimuli, we identified a conserved core response module that is differentially expressed in response to all studied conditions. This module occupies a highly central position in the inferred network and is also enriched in genes preferentially targeted by pathogens. The module includes cytokines, interferon induced genes such as Ifit1 and 2, effectors of inflammation, Cox1 and Oas1 and Oasl2, and transcription factors including AP1, Egr1 and 2 and Mafb. Predictive modeling using a reverse-engineering approach reveals dynamic differences between the responses to each stimulus and predicts the regulatory influences directing this module. We speculate that this module may be an early checkpoint for progression to apoptosis and/or inflammation during macrophage activation.

A leucine-rich repeat assembly approach for homology modeling of the human TLR5-10 and mouse TLR11-13 ectodomains

So far, 13 groups of mammalian Toll-like receptors (TLRs) have been identified. Most TLRs have been shown to recognize pathogen-associated molecular patterns from a wide range of invading agents and initiate both innate and adaptive immune responses. The TLR ectodomains are composed of varying numbers and types of leucine-rich repeats (LRRs). As the crystal structures are currently missing for most TLR ligand-binding ectodomains, homology modeling enables first predictions of their three-dimensional structures on the basis of the determined crystal structures of TLR ectodomains. However, the quality of the predicted models that are generated from full-length templates can be limited due to low sequence identity between the target and templates. To obtain better templates for modeling, we have developed an LRR template assembly approach. Individual LRR templates that are locally optimal for the target sequence are assembled into multiple templates. This method was validated through the comparison of a predicted model with the crystal structure of mouse TLR3. With this method, we also constructed ectodomain models of human TLR5, TLR6, TLR7, TLR8, TLR9, and TLR10 and mouse TLR11, TLR12, and TLR13 that can be used as first passes for a computational simulation of ligand docking or to design mutation experiments. This template assembly approach can be extended to other repetitive proteins.