Characterization of heparin-binding site of tissue transglutaminase:its importance in cell surface targeting, matrix deposition, and cell signaling

Tissue transglutaminase (TG2) is a multifunctional Ca2+ activated protein crosslinking enzyme secreted into the extracellular matrix (ECM), where it is involved in wound healing and scarring, tissue fibrosis, celiac disease and metastatic cancer. Extracellular TG2 can also facilitate cell adhesion important in wound healing through a non-transamidating mechanism via its association with fibronectin (FN), heparan sulphates (HS) and integrins. Regulating the mechanism how TG2 is translocated into the ECM therefore provides a strategy for modulating these physiological and pathological functions of the enzyme. Here, through molecular modelling and mutagenesis we have identified the HS binding site of TG2 202KFLKNAGRDCSRRSSPVYVGR222. We demonstrate the requirement of this binding site for translocation of TG2 into the ECM through a mechanism involving cell surface shedding of HS. By synthesizing a peptide NPKFLKNAGRDCSRRSS corresponding to the HS binding site within TG2, we also demonstrate how this mimicking peptide can in isolation compensate the RGD-induced loss of cell adhesion on FN via binding to syndecan-4, leading to activation of PKCa, pFAK-397 and ERK1/2 and the subsequent formation of focal adhesions and actin cytoskeleton organization. A novel regulatory mechanism for TG2 translocation into the extracellular compartment that depends upon TG2 conformation and the binding of HS is proposed.

PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0:a quantitative molecular docking study

Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.

Characterization of metal ion-induced [3H]inositol hexakisphosphate binding to rat cerebellar membranes

The binding of [3H]inositol hexakisphosphate ([3H] InsP6) to rat cerebellar membranes has been characterized with the objective of establishing the role, if any, of a membrane protein receptor. In the presence of EDTA, we have previously identified an InsP6-binding site with a capacity of approximately 20 pmol/mg protein (Hawkins, P. T., Reynolds, D. J. M., Poyner, D. R., and Hanley, M. R. (1990) Biochem. Biophys. Res. Commun. 167, 819-827). However, in the presence of 1 mM Mg2+, the capacity of [3H]InsP6 binding to membranes was increased approximately 9-fold. This enhancing effect of Mg2+ was reversed by addition of 10 microM of several cation chelators, suggesting that the increased binding required trace quantities of other metal cations. This is supported by experiments where it was possible to saturate binding by addition of excess membranes, despite not significantly depleting radioligand, pointing to removal of some other factor. Removal of endogenous cations from the binding assay by pretreatment with chelex resin also prevents the Mg(2+)-induced potentiation. Consideration of the specificity of the chelators able to abolish this potentiation suggested involvement of Fe3+ or Al3+. Both these ions (but not several others) were able to increase [3H]InsP6 binding to chelex-pretreated membranes at concentrations of 1 microM. It is possible to demonstrate synergy between Fe3+ and Mg2+ under these conditions. We propose that [3H]InsP6 may interact with membranes through non-protein recognition possibly via phospholipids, in a manner dependent upon trace metals. The implications of this for InsP6 biology are considered.

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

Behavioural and neurochemical correlates of drugs acting at imidazoline and a2-adrenoceptor binding sites

A number of agents with differing selectivity profiles for the non-a2 adrenoceptor binding site (NAIBS), imidazoline preferring receptor (IPR) and a2-adrenoceptor were employed in a series of behavioural and neurochemical experiments to determine a functional role for the former two sites. The highly selective NAIBS ligand RX801 077 produced an increase in rat brain extracellular noradrenaline (NA) levels, as determined by the technique of in vivo microdialysis, which may underlie its ability to produce a discriminable cue in the same species. This increase in NA may be due to a suggested link between the NAIBS and the monoamine oxidase inhibitor (MAOI) activity of RX801 077. For instance, the RX801 077 cue was substituted for by the MAOI drugs pargyline and moclobemide, which themselves down regulate NAIBS when administered chronically. RX811 059 substituted for the RX801 077 cue which may be due its ability to stimulate NA release via its activity as a highly selective a2-adrenoceptor antagonist. An effect upon NA output may also explain the ability of RX801 077 to 'mimic' the anti-immobility effect of the antidepressant drug desmethylimipramine (DMJ) in the forced swimming test. Further studies are therefore required to examine a possible role for the NAIBS in the treatment of depression. Discriminable cues were also produced by RX811 059 and the a2- adrenoceptor agonist clonidine, probably as a consequence of their respective ability to stimulate and inhibit NA output via their opposing activity at a2-adrenoceptors. The IPR has been suggested to play a role in mediating the hypotensive effect of clonidine, although a precise role was unable to be established for this site in the present studies due to the unavailability of highly selective IPA agents.

Role of GSH in estrone sulfate binding and translocation by the multidrug resistance protein 1 (MRP1/ABCC1)

Multidrug resistance protein 1 (MRP1/ABCC1) is an ATP-dependent efflux pump that can confer resistance to multiple anticancer drugs and transport conjugated organic anions. Unusually, transport of several MRP1 substrates requires glutathione (GSH). For example, estrone sulfate transport by MRP1 is stimulated by GSH, vincristine is co-transported with GSH, or GSH can be transported alone. In the present study, radioligand binding assays were developed to investigate the mechanistic details of GSH-stimulated transport of estrone sulfate by MRP1. We have established that estrone sulfate binding to MRP1 requires GSH, or its non-reducing analogue S-methyl GSH (S-mGSH), and further that the affinity (Kd) of MRP1 for estrone sulfate is 2.5-fold higher in the presence of S-mGSH than GSH itself. Association kinetics show that GSH binds to MRP1 first, and we propose that GSH binding induces a conformational change, which makes the estrone sulfate binding site accessible. Binding of non-hydrolyzable ATP analogues to MRP1 decreases the affinity for estrone sulfate. However, GSH (or S-mGSH) is still required for estrone sulfate binding, and the affinity for GSH is unchanged. Estrone sulfate affinity remains low following hydrolysis of ATP. The affinity for GSH also appears to decrease in the post-hydrolytic state. Our results indicate ATP binding is sufficient for reconfiguration of the estrone sulfate binding site to lower affinity and argue for the presence of a modulatory GSH binding site not associated with transport of this tripeptide. A model for the mechanism of GSH-stimulated estrone sulfate transport is proposed.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Cortical oscillatory dynamics and benzodiazepine-site modulation of tonic inhibition in fast spiking interneurons

Tonic conductance mediated by extrasynaptic GABAA receptors has been implicated in the modulation of network oscillatory activity. Using an in vitro brain slice to produce oscillatory activity and a kinetic model of GABAA receptor dynamics, we show that changes in tonic inhibitory input to fast spiking interneurons underlie benzodiazepine-site mediated modulation of neuronal network synchrony in rat primary motor cortex. We found that low concentrations (10 nM) of the benzodiazepine site agonist, zolpidem, reduced the power of pharmacologically-induced beta-frequency (15–30 Hz) oscillatory activity. By contrast, higher doses augmented beta power. Application of the antagonist, flumazenil, also increased beta power suggesting endogenous modulation of the benzodiazepine binding site. Voltage-clamp experiments revealed that pharmacologically-induced rhythmic inhibitory postsynaptic currents were reduced by 10 nM zolpidem, suggesting an action on inhibitory interneurons. Further voltage -clamp studies of fast spiking cells showed that 10 nM zolpidem augmented a tonic inhibitory GABAA receptor mediated current in fast spiking cells whilst higher concentrations of zolpidem reduced the tonic current. A kinetic model of zolpidem-sensitive GABAA receptors suggested that incubation with 10 nM zolpidem resulted in a high proportion of GABAA receptors locked in a kinetically slow desensitized state whilst 30 nM zolpidem favoured rapid transition into and out of desensitized states. This was confirmed experimentally using a challenge with saturating concentrations of GABA. Selective modulation of an interneuron-specific tonic current may underlie the reversal of cognitive and motor deficits afforded by low-dose zolpidem in neuropathological states.

MHC class II binding prediction by molecular docking

Proteins of the Major Histocompatibility Complex (MHC) bind self and nonself peptide antigens or epitopes within the cell and present them at the cell surface for recognition by T cells. All T-cell epitopes are MHC binders but not all MCH binders are T-cell epitopes. The MHC class II proteins are extremely polymorphic. Polymorphic residues cluster in the peptide-binding region and largely determine the MHC's peptide selectivity. The peptide binding site on MHC class II proteins consist of five binding pockets. Using molecular docking, we have modelled the interactions between peptide and MHC class II proteins from locus DRB1. A combinatorial peptide library was generated by mutation of residues at peptide positions which correspond to binding pockets (so called anchor positions). The binding affinities were assessed using different scoring functions. The normalized scoring functions for each amino acid at each anchor position were used to construct quantitative matrices (QM) for MHC class II binding prediction. Models were validated by external test sets comprising 4540 known binders. Eighty percent of the known binders are identified in the best predicted 15% of all overlapping peptides, originating from one protein. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.