Interaction of sulphur-containing aroma compounds with proteins in both model systems and real food systems

Irreversible binding of key flavour disulphides to ovalbumin has been shown previously to occur in model systems. The extent of binding is determined by the availability of the sulphydryl groups to participate in disulphide exchange, influenced either by pH, or the state of the protein (native or heat-denatured). In this study, two further proteins, one with sulphydryl groups available in the native state (beta-lactoglobulin) and one with no sulphydryl groups in the native state (lysozyme) were used to confirm this hypothesis. When the investigation was extended to real food systems, a similar effect was shown when a commercial meat flavouring containing disulphides was added to heat-denatured ovalbumin. Furthermore, comparison of the volatiles generated from onions, cooked either alone, or in the presence of meat, showed a significant reduction of key onion-derived disulphides when cooked in the presence of meat, and an even greater reduction of trisulphides. These findings may have implications for consumer acceptance of food products; where these compounds are used as flavourings or where they occur naturally.

Molecular dynamics simulations of proteins: can the explicit water model be varied?

In molecular mechanics simulations of biological systems, the solvation water is typically represented by a default water model which is an integral part of the force field. Indeed, protein nonbonding parameters are chosen in order to obtain a balance between water-water and protein-water interactions and hence a reliable description of protein solvation. However, less attention has been paid to the question of whether the water model provides a reliable description of the water properties under the chosen simulation conditions, for which more accurate water models often exist. Here we consider the case of the CHARMM protein force field, which was parametrized for use with a modified TIP3P model. Using quantum mechanical and molecular mechanical calculations, we investigate whether the CHARMM force field can be used with other water models: TIP4P and TIP5P. Solvation properties of N-methylacetamide (NMA), other small solute molecules, and a small protein are examined. The results indicate differences in binding energies and minimum energy geometries, especially for TIP5P, but the overall description of solvation is found to be similar for all models tested. The results provide an indication that molecular mechanics simulations with the CHARMM force field can be performed with water models other than TIP3P, thus enabling an improved description of the solvent water properties.

Selected wheat seed defense proteins exhibit competitive binding to model microbial lipid interfaces

Puroindolines (Pins) and purothionins (Pths) are basic, amphiphilic, cysteine-rich wheat proteins that play a role in plant defense against microbial pathogens. We have examined the co-adsorption and sequential addition of Pins (Pin-a, Pin-b and a mutant form of Pin-b with Trp-44 to Arg-44 substitution) and β-purothionin (β-Pth) model anionic lipid layers, using a combination of surface pressure measurements, external reflection FTIR spectroscopy and neutron reflectometry. Results highlighted differences in the protein binding mechanisms, and in the competitive binding and penetration of lipid layers between respective Pins and β-Pth. Pin-a formed a blanket-like layer of protein below the lipid surface that resulted in the reduction or inhibition of β-Pth penetration of the lipid layer. Wild-type Pin-b participated in co-operative binding with β-Pth, whereas the mutant Pin-b did not bind to the lipid layer in the presence of β-Pth. The results provide further insight into the role of hydrophobic and cationic amino acid residues in antimicrobial activity.

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments

MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

Functional genomics in zebrafish permits rapid characterization of novel platelet membrane proteins

In this study, we demonstrate the suitability of the vertebrate Danio rerio (zebrafish) for functional screening of novel platelet genes in vivo by reverse genetics. Comparative transcript analysis of platelets and their precursor cell, the megakaryocyte, together with nucleated blood cell elements, endothelial cells, and erythroblasts, identified novel platelet membrane proteins with hitherto unknown roles in thrombus formation. We determined the phenotype induced by antisense morpholino oligonucleotide (MO)–based knockdown of 5 of these genes in a laser-induced arterial thrombosis model. To validate the model, the genes for platelet glycoprotein (GP) IIb and the coagulation protein factor VIII were targeted. MO-injected fish showed normal thrombus initiation but severely impaired thrombus growth, consistent with the mouse knockout phenotypes, and concomitant knockdown of both resulted in spontaneous bleeding. Knockdown of 4 of the 5 novel platelet proteins altered arterial thrombosis, as demonstrated by modified kinetics of thrombus initiation and/or development. We identified a putative role for BAMBI and LRRC32 in promotion and DCBLD2 and ESAM in inhibition of thrombus formation. We conclude that phenotypic analysis of MO-injected zebrafish is a fast and powerful method for initial screening of novel platelet proteins for function in thrombosis.

Apical leaf necrosis and leaf nitrogen dynamics in diseased leaves: a model study

Apical leaf necrosis is a physiological process related to nitrogen (N) dynamics in the leaf. Pathogens use leaf nutrients and can thus accelerate this physiological apical necrosis. This process differs from necrosis occurring around pathogen lesions (lesion-induced necrosis), which is a direct result of the interaction between pathogen hyphae and leaf cells. This paper primarily concentrates on apical necrosis, only incorporating lesion-induced necrosis by necessity. The relationship between pathogen dynamics and physiological apical leaf necrosis is modelled through leaf nitrogen dynamics. The specific case of Puccinia triticina infections on Triticum aestivum flag leaves is studied. In the model, conversion of indirectly available N in the form of, for example, leaf cell proteins (N-2(t)) into directly available N (N-1(t), i.e. the form of N that can directly be used by either pathogen or plant sinks) results in apical necrosis. The model reproduces observed trends of disease severity, apical necrosis and green leaf area (GLA) and leaf N dynamics of uninfected and infected leaves. Decreasing the initial amount of directly available N results in earlier necrosis onset and longer necrosis duration. Decreasing the initial amount of indirectly available N, has no effect on necrosis onset and shortens necrosis duration. The model could be used to develop hypotheses on how the disease-GLA relation affects yield loss, which can be tested experimentally. Upon incorporation into crop simulation models, the model might provide a tool to more accurately estimate crop yield and effects of disease management strategies in crops sensitive to fungal pathogens.

Selective separation of the major whey proteins using ion exchange membranes

Synthetic microporous membranes with functional groups covalently attached were used to selectively separate beta-lactoglobulin, BSA, and alpha-lactalbumin from rennet whey. The selectivity and membrane performance of strong (quaternary ammonium) and weak (diethylamine) ion-exchange membranes were studied using breakthrough curves, measurement of binding capacity, and protein composition of the elution fraction to determine the binding behavior of each membrane. When the weak and strong anion exchange membranes were saturated with whey, they were both selective primarily for beta-lactoglobulin with less than 1% of the eluate consisting of alpha-lactalbumin or BSA. The binding capacity of a pure alpha-lactoglobulin solution was in excess of 1.5 mg/cm(2) of membrane. This binding capacity was reduced to approximately 1.2 mg/cm(2) when using a rennet whey solution (pH 6.4). This reduction in protein binding capacity can be explained by both the competitive effects of other whey proteins and the effect of ions present in whey. Using binary solution breakthrough curves and rennet whey breakthrough curves, it was shown that alpha-lactalbumin and BSA were displaced from the strong and weak anion exchange membranes by beta-lactoglobulin. Finally, the effect of ionic strength on the binding capacity of individual proteins for each membrane was determined by comparing model protein solutions in milk permeate (pH 6.4) and a 10 mM sodium phosphate buffer (pH 6.4). Binding capacities of beta-lactoglobulin, alpha-lactalbumin, and BSA in milk permeate were reduced by as much as 50%. This reduction in capacity coupled with the low binding capacity of current ion exchange membranes are 2 serious considerations for selectively separating complex and concentrated protein solutions.

A novel technique for differentiation of proteins in the development of acid gel structure from control and heat treated milk using confocal scanning laser microscopy

The incorporation of caseins and whey proteins into acid gels produced from unheated and heat treated skimmed milk was studied by confocal scanning laser microscopy (CSLM) using fluorescent labelled proteins. Bovine casein micelles were labelled using Alexa Fluor 594, while whey proteins were labelled using Alexa Fluor 488. Samples of the labelled protein solutions were introduced into aliquots of pasteurised skim milk, and skim milk heated to 90 degrees C for 2 min and 95 degrees C for 8 min. The milk was acidified at 40 degrees C to a final pH of 4.4 using 20 g gluconodelta-lactone/l (GDL). The formation of gels was observed with CSLM at two wavelengths (488 nm and 594 nm), and also by visual and rheological methods. In the control milk, as pH decreased distinct casein aggregates appeared, and as further pH reduction occurred, the whey proteins could be seen to coat the casein aggregates. With the heated milks, the gel structure was formed of continuous strands consisting of both casein and whey protein. The formation of the gel network was correlated with an increase in the elastic modulus for all three treatments, in relation to the severity of heat treatment. This model system allows the separate observation of the caseins and whey proteins, and the study of the interactions between the two protein fractions during the formation of the acid gel structure, on a real-time basis. The system could therefore be a valuable tool in the study of structure formation in yoghurt and other dairy protein systems.

Adsorption of frog foam nest proteins at the air-water interface

The surfactant properties of aqueous protein mixtures ( ranaspumins) from the foam nests of the tropical frog Physalaemus pustulosus have been investigated by surface tension, two-photon excitation. uorescence microscopy, specular neutron reflection, and related biophysical techniques. Ranaspumins lower the surface tension of water more rapidly and more effectively than standard globular proteins under similar conditions. Two- photon excitation. uorescence microscopy of nest foams treated with fluorescent marker ( anilinonaphthalene sulfonic acid) shows partitioning of hydrophobic proteins into the air-water interface and allows imaging of the foam structure. The surface excess of the adsorbed protein layers, determined from measurements of neutron reflection from the surface of water utilizing H2O/D2O mixtures, shows a persistent increase of surface excess and layer thickness with bulk concentration. At the highest concentration studied ( 0.5 mg ml(-1)), the adsorbed layer is characterized by three distinct regions: a protruding top layer of similar to20 Angstrom, a middle layer of similar to30 Angstrom, and a more diffuse submerged layer projecting some 25 Angstrom into bulk solution. This suggests a model involving self-assembly of protein aggregates at the air-water interface in which initial foam formation is facilitated by specific surfactant proteins in the mixture, further stabilized by subsequent aggregation and cross-linking into a multilayer surface complex.

Binding of pentagalloyl glucose to two globular proteins occurs via multiple surface sites

The interaction between pentagalloyl glucose (PGG) and two globular proteins, bovine serum albumin (BSA) and ribulose-1,5-bisphosphate carboxylase oxygenase (rubisco), was investigated by isothermal titration calorimetry (ITC). ITC data fit to a binding model consisting of two sets of multiple binding sites, which reveal similarities in the mode of binding of PGG to BSA and rubisco. In both cases, the interaction is characterized by a high number of binding sites, which suggests that binding occurs by a surface adsorption mechanism that leads to coating of the protein surface, which promotes aggregation and precipitation of the PGG-protein complex. This model was confirmed by turbidimetry analysis of the PGG-BSA interaction. Analysis of tryptophan fluorescence quenching during the interaction of PGG with BSA suggests that binding of PGG leads to some conformational changes that are energetically closer to the unfolded state of the BSA structure, because small red shifts in the resulting emission spectra were observed.

c-Jun N-terminal kinase (JNK)-mediated modulation of brain mitochondria function: new target proteins for JNK signalling in mitochondrion-dependent apoptosis

The molecular mechanisms underlying the initiation and control of the release of cytochrome c during mitochondrion-dependent apoptosis are thought to involve the phosphorylation of mitochondrial Bcl-2 and Bcl-x(L). Although the c-Jun N-terminal kinase (JNK) has been proposed to mediate the phosphorylation of Bcl-2/Bcl-x(L) the mechanisms linking the modification of these proteins and the release of cytochrome c remain to be elucidated. This study was aimed at establishing interdependency between JNK signalling and mitochondrial apoptosis. Using an experimental model consisting of isolated, bioenergetically competent rat brain mitochondria, these studies show that (i) JNK catalysed the phosphorylation of Bcl-2 and Bcl-x(L) as well as other mitochondrial proteins, as shown by two-dimensional isoelectric focusing/SDS/PAGE; (ii) JNK-induced cytochrome c release, in a process independent of the permeability transition of the inner mitochondrial membrane (imPT) and insensitive to cyclosporin A; (iii) JNK mediated a partial collapse of the mitochondrial inner-membrane potential (Deltapsim) in an imPT- and cyclosporin A-independent manner; and (iv) JNK was unable to induce imPT/swelling and did not act as a co-inducer, but as an inhibitor of Ca-induced imPT. The results are discussed with regard to the functional link between the Deltapsim and factors influencing the permeability transition of the inner and outer mitochondrial membranes. Taken together, JNK-dependent phosphorylation of mitochondrial proteins including, but not limited to, Bcl-2/Bcl-x(L) may represent a potential of the modulation of mitochondrial function during apoptosis.

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.