Dataset Information

Homology modeling of human Toll-like receptors TLR7, 8, and 9 ligand-binding domains.

ABSTRACT: Toll-like receptors (TLRs) play a key role in the innate immune system. The TLR7, 8, and 9 compose a family of intracellularly localized TLRs that signal in response to pathogen-derived nucleic acids. So far, there are no crystallographic structures for TLR7, 8, and 9. For this reason, their ligand-binding mechanisms are poorly understood. To enable first predictions of the receptor-ligand interaction sites, we developed three-dimensional structures for the leucine-rich repeat ectodomains of human TLR7, 8, and 9 based on homology modeling. To achieve a high sequence similarity between targets and templates, structural segments from all known TLR ectodomain structures (human TLR1/2/3/4 and mouse TLR3/4) were used as candidate templates for the modeling. The resulting models support previously reported essential ligand-binding residues. They also provide a basis to identify three potential receptor dimerization mechanisms. Additionally, potential ligand-binding residues are identified using combined procedures. We suggest further investigations of these residues through mutation experiments. Our modeling approach can be extended to other members of the TLR family or other repetitive proteins.

SUBMITTER: Wei T

PROVIDER: S-EPMC2776956 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Homology modeling of human Toll-like receptors TLR7, 8, and 9 ligand-binding domains.

Wei Tiandi T Gong Jing J Jamitzky Ferdinand F Heckl Wolfgang M WM Stark Robert W RW Rössle Shaila C SC

Protein science : a publication of the Protein Society 20090801 8

Toll-like receptors (TLRs) play a key role in the innate immune system. The TLR7, 8, and 9 compose a family of intracellularly localized TLRs that signal in response to pathogen-derived nucleic acids. So far, there are no crystallographic structures for TLR7, 8, and 9. For this reason, their ligand-binding mechanisms are poorly understood. To enable first predictions of the receptor-ligand interaction sites, we developed three-dimensional structures for the leucine-rich repeat ectodomains of hum ...[more]

PMID: 19521997

Similar Datasets

Project description:The activated mammalian CAPN-structures, the CAPN/CAST complex in particular, have become an invaluable target model using the structure-based virtual screening of drug candidates from the discovery phase to development for over-activated CAPN linked to several diseases, such as post-ischemic injury and cataract formation. The effect of Ca²?-binding to the enzyme is thought to include activation, as well as the dissociation, aggregation, and autolysis of small regular subunits. Unfortunately, the Ca²?-activated enzyme tends to aggregate when provided as a divalent ion at the high-concentration required for the protease crystallization. This is also makes it very difficult to crystallize the whole-length enzyme itself, as well as the enzyme-inhibitor complex. Several parameters that influence CAPN activity have been investigated to determine its roles in Ca²?-modulation, autoproteolysis, phosphorylation, and intracellular distribution and inhibition by its endogenous inhibitor CAST. CAST binds and inhibits CAPN via its CAPN-inhibitor domains (four repeating domains 1-4; CAST1-4) when CAPN is activated by Ca²?-binding. An important key to understanding CAPN1 inhibition by CAST is to determine how CAST interacts at the molecular level with CAPN1 to inhibit its protease activity. In this study, a 3D structure model of a CAPN1 bound bovine CAST4 complex was built by comparative modeling based on the only known template structure of a rat CAPN2/CAST4 complex. The complex model suggests certain residues of bovine CAST4, notably, the TIPPKYQ motif sequence, and the structural elements of these residues, which are important for CAPN1 inhibition. In particular, as CAST4 docks near the flexible active site of CAPN1, conformational changes at the interaction site after binding could be directly related to CAST4 inhibitory activity. These functional interfaces can serve as a guide to the site-mutagenesis in research on bovine CAPN1 structure-function relationships for the design of small molecules inhibitors to prevent uncontrolled and unspecific degradation in the proteolysis of key protease substrates.

Project description:BACKGROUND:The EP4 prostanoid receptor is one of four GPCRs that mediate the diverse actions of prostaglandin E2 (PGE2). Novel selective EP4 receptor agonists would assist to further elucidate receptor sub-type function and promote development of therapeutics for bone healing, heart failure, and other receptor associated conditions. The rat EP4 (rEP4) receptor has been used as a surrogate for the human EP4 (hEP4) receptor in multiple SAR studies. To better understand the validity of this traditional approach, homology models were generated by threading for both receptors using the RaptorX server. These models were fit to an implicit membrane using the PPM server and OPM database with refinement of intra and extracellular loops by Prime (Schrödinger). To understand the interaction between the receptors and known agonists, induced-fit docking experiments were performed using Glide and Prime (Schrödinger), with both endogenous agonists and receptor sub-type selective, small-molecule agonists. The docking scores and observed interactions were compared with radioligand displacement experiments and receptor (rat & human) activation assays monitoring cAMP. RESULTS:Rank-ordering of in silico compound docking scores aligned well with in vitro activity assay EC50 and radioligand binding Ki. We observed variations between rat and human EP4 binding pockets that have implications in future small-molecule receptor-modulator design and SAR, specifically a S103G mutation within the rEP4 receptor. Additionally, these models helped identify key interactions between the EP4 receptor and ligands including PGE2 and several known sub-type selective agonists while serving as a marked improvement over the previously reported models. CONCLUSIONS:This work has generated a set of novel homology models of the rEP4 and hEP4 receptors. The homology models provide an improvement upon the previously reported model, largely due to improved solvation. The hEP4 docking scores correlates best with the cAMP activation data, where both data sets rank order Rivenprost>CAY10684?>?PGE1???PGE2?>?11-deoxy-PGE1???11-dexoy-PGE2?>?8-aza-11-deoxy-PGE1. This rank-ordering matches closely with the rEP4 receptor as well. Species-specific differences were noted for the weak agonists Sulprostone and Misoprostol, which appear to dock more readily within human receptor versus rat receptor.

Project description:The ABCB1 transporter also known as P-glycoprotein (P-gp) is a transmembrane protein belonging to the ATP binding cassette super-family of transporters; it is a xenobiotic efflux pump that limits intracellular drug accumulation by pumping the compounds out of cells. P-gp contributes to a decrease of toxicity and possesses broad substrate specificity. It is involved in the failure of numerous anticancer and antiviral chemotherapies due to the multidrug resistance (MDR) phenomenon, where it removes the chemotherapeutics out of the targeted cells. Understanding the details of the ligand-P-gp interaction is therefore crucial for the development of drugs that might overcome the MRD phenomenon and for obtaining a more effective prediction of the toxicity of certain compounds. In this work, an in silico modeling was performed using homology modeling and molecular docking methods with the aim of better understanding the ligand-P-gp interactions. Based on different mouse P-gp structural templates from the PDB repository, a 3D model of the human P-gp (hP-gp) was constructed by means of protein homology modeling. The homology model was then used to perform molecular docking calculations on a set of thirteen compounds, including some well-known compounds that interact with P-gp as substrates, inhibitors, or both. The sum of ranking differences (SRD) was employed for the comparison of the different scoring functions used in the docking calculations. A consensus-ranking scheme was employed for the selection of the top-ranked pose for each docked ligand. The docking results showed that a high number of π interactions, mainly π-sigma, π-alkyl, and π-π type of interactions, together with the simultaneous presence of hydrogen bond interactions contribute to the stability of the ligand-protein complex in the binding site. It was also observed that some interacting residues in hP-gp are the same when compared to those observed in a co-crystallized ligand (PBDE-100) with mouse P-gp (PDB ID: 4XWK). Our in silico approach is consistent with available experimental results regarding P-gp efflux transport assay; therefore it could be useful in the prediction of the role of new compounds in systemic toxicity.

Dataset Information

Homology modeling of human Toll-like receptors TLR7, 8, and 9 ligand-binding domains.

Publications

Homology modeling of human Toll-like receptors TLR7, 8, and 9 ligand-binding domains.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets