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

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

Signal Integration by the IκB Protein Pickle Shapes <i>Drosophila</i> Innate Host Defense

SummaryPattern recognition receptors are activated following infection and trigger transcriptional programs important for host defense. Tight regulation of NF-κB activation is critical to avoid detrimental and misbalanced responses. We describe Pickle, a Drosophila nuclear IκB that integrates signaling inputs from both the Imd and Toll pathways by skewing the transcriptional output of the NF-κB dimer repertoire. Pickle interacts with the NF-κB protein Relish and the histone deacetylase dHDAC1, selectively repressing Relish homodimers while leaving other NF-κB dimer combinations unscathed. Pickle’s ability to selectively inhibit Relish homodimer activity contributes to proper host immunity and organismal health. Although loss of pickle results in hyper-induction of Relish target genes and improved host resistance to pathogenic bacteria in the short term, chronic inactivation of pickle causes loss of immune tolerance and shortened lifespan. Pickle therefore allows balanced immune responses that protect from pathogenic microbes while permitting the establishment of beneficial commensal host-microbe relationships

Structure-Function Relationship of Cytoplasmic and Nuclear IκB Proteins: An In Silico Analysis

Cytoplasmic IκB proteins are primary regulators that interact with NF-κB subunits in the cytoplasm of unstimulated cells. Upon stimulation, these IκB proteins are rapidly degraded, thus allowing NF-κB to translocate into the nucleus and activate the transcription of genes encoding various immune mediators. Subsequent to translocation, nuclear IκB proteins play an important role in the regulation of NF-κB transcriptional activity by acting either as activators or inhibitors. To date, molecular basis for the binding of IκBα, IκBβ and IκBζ along with their partners is known; however, the activation and inhibition mechanism of the remaining IκB (IκBNS, IκBε and Bcl-3) proteins remains elusive. Moreover, even though IκB proteins are structurally similar, it is difficult to determine the exact specificities of IκB proteins towards their respective binding partners. The three-dimensional structures of IκBNS, IκBζ and IκBε were modeled. Subsequently, we used an explicit solvent method to perform detailed molecular dynamic simulations of these proteins along with their known crystal structures (IκBα, IκBβ and Bcl-3) in order to investigate the flexibility of the ankyrin repeat domains (ARDs). Furthermore, the refined models of IκBNS, IκBε and Bcl-3 were used for multiple protein-protein docking studies for the identification of IκBNS-p50/p50, IκBε-p50/p65 and Bcl-3-p50/p50 complexes in order to study the structural basis of their activation and inhibition. The docking experiments revealed that IκBε masked the nuclear localization signal (NLS) of the p50/p65 subunits, thereby preventing its translocation into the nucleus. For the Bcl-3- and IκBNS-p50/p50 complexes, the results show that Bcl-3 mediated transcription through its transactivation domain (TAD) while IκBNS inhibited transcription due to its lack of a TAD, which is consistent with biochemical studies. Additionally, the numbers of identified flexible residues were equal in number among all IκB proteins, although they were not conserved. This could be the primary reason for their binding partner specificities

Harnessing the Therapeutic Potential of Capsaicin and Its Analogues in Pain and Other Diseases

Capsaicin is the most predominant and naturally occurring alkamide found in Capsicum fruits. Since its discovery in the 19th century, the therapeutic roles of capsaicin have been well characterized. The potential applications of capsaicin range from food flavorings to therapeutics. Indeed, capsaicin and few of its analogues have featured in clinical research covered by more than a thousand patents. Previous records suggest pleiotropic pharmacological activities of capsaicin such as an analgesic, anti-obesity, anti-pruritic, anti-inflammatory, anti-apoptotic, anti-cancer, anti-oxidant, and neuro-protective functions. Moreover, emerging data indicate its clinical significance in treating vascular-related diseases, metabolic syndrome, and gastro-protective effects. The dearth of potent drugs for management of such disorders necessitates the urge for further research into the pharmacological aspects of capsaicin. This review summarizes the historical background, source, structure and analogues of capsaicin, and capsaicin-triggered TRPV1 signaling and desensitization processes. In particular, we will focus on the therapeutic roles of capsaicin and its analogues in both normal and pathophysiological conditions

In silico approach to inhibition of signaling pathways of Toll-like receptors 2 and 4 by ST2L.

Toll-like receptors (TLRs) activate a potent immunostimulatory response. There is clear evidence that overactivation of TLRs leads to infectious and inflammatory diseases. Recent biochemical studies have shown that the membrane-bound form of ST2 (ST2L), a member of the Toll-like/IL-1 receptor superfamily, negatively regulates MyD88-dependent TLR signaling pathways by sequestrating the adapters MyD88 and Mal (TIRAP). Specifically, ST2L attenuates the recruitment of Mal and MyD88 adapters to their receptors through its intracellular TIR domain. Thus, ST2L is a potent molecule that acts as a key regulator of endotoxin tolerance and modulates innate immunity. So far, the inhibitory mechanism of ST2L at the molecular level remains elusive. To develop a working hypothesis for the interactions between ST2L, TLRs (TLR1, 2, 4, and 6), and adapter molecules (MyD88 and Mal), we constructed three-dimensional models of the TIR domains of TLR4, 6, Mal, and ST2L based on homology modeling. Since the crystal structures of the TIR domains of TLR1, 2 as well as the NMR solution structure of MyD88 are known, we utilized these structures in our analysis. The TIR domains of TLR1, 2, 4, 6, MyD88, Mal and ST2L were subjected to molecular dynamics (MD) simulations in an explicit solvent environment. The refined structures obtained from the MD simulations were subsequently used in molecular docking studies to probe for potential sites of interactions. Through protein-protein docking analysis, models of the essential complexes involved in TLR2 and 4 signaling and ST2L inhibiting processes were developed. Our results suggest that ST2L may exert its inhibitory effect by blocking the molecular interface of Mal and MyD88 adapters mainly through its BB-loop region. Our predicted oligomeric signaling models may provide a basis for the understanding of the assembly process of TIR domain interactions, which has thus far proven to be difficult via in vivo studies

iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree

A soluble carrier growth hormone binding protein (GHBP) that can selectively and non-covalently interact with growth hormone, thereby acting as a modulator or inhibitor of growth hormone signalling. Accurate identification of the GHBP from a given protein sequence also provides important clues for understanding cell growth and cellular mechanisms. In the postgenomic era, there has been an abundance of protein sequence data garnered, hence it is crucial to develop an automated computational method which enables fast and accurate identification of putative GHBPs within a vast number of candidate proteins. In this study, we describe a novel machine-learning-based predictor called iGHBP for the identification of GHBP. In order to predict GHBP from a given protein sequence, we trained an extremely randomised tree with an optimal feature set that was obtained from a combination of dipeptide composition and amino acid index values by applying a two-step feature selection protocol. During cross-validation analysis, iGHBP achieved an accuracy of 84.9%, which was ~7% higher than the control extremely randomised tree predictor trained with all features, thus demonstrating the effectiveness of our feature selection protocol. Furthermore, when objectively evaluated on an independent data set, our proposed iGHBP method displayed superior performance compared to the existing method. Additionally, a user-friendly web server that implements the proposed iGHBP has been established and is available at http://thegleelab.org/iGHBP. Keywords: Extremely randomised tree, Growth hormone binding protein, Machine learning, Random forest, Support vector machin

A Molecular Dynamics Approach to Explore the Intramolecular Signal Transduction of PPAR-α

Dynamics and functions of the peroxisome proliferator-activated receptor (PPAR)-&#945; are modulated by the types of ligands that bind to the orthosteric sites. While several X-ray crystal structures of PPAR-&#945; have been determined in their agonist-bound forms, detailed structural information in their apo and antagonist-bound states are still lacking. To address these limitations, we apply unbiased molecular dynamics simulations to three different PPAR-&#945; systems to determine their modulatory mechanisms. Herein, we performed hydrogen bond and essential dynamics analyses to identify the important residues involved in polar interactions and conformational structural variations, respectively. Furthermore, betweenness centrality network analysis was carried out to identify key residues for intramolecular signaling. The differences observed in the intramolecular signal flow between apo, agonist- and antagonist-bound forms of PPAR-&#945; will be useful for calculating maps of information flow and identifying key residues crucial for signal transductions. The predictions derived from our analysis will be of great help to medicinal chemists in the design of effective PPAR-&#945; modulators and additionally in understanding their regulation and signal transductions