Implicit and explicit interactions in video mediated collaboration

In this paper we report the results of a study comparing implicit-only and explicit-only interactions in a collaborative, video-mediated task with shared content. Expanding on earlier work which has typically only evaluated how implicit interaction can augment primarily explicit systems, we report issues surrounding control, anxiousness and negotiation in the context of video mediated collaboration. We conclude that implicit interaction has the potential to improve collaborative work, but that there are a multitude of issues that must first be negotiated.

From mundane to smart: Exploring interactions with ‘smart' design objects

In addition to functional and technological features, the role of augmented objects should also be seen in terms of how effectively they fit into the everyday practices of users and how they enhance users' experiences. In this article, the authors introduce a low-tech, internet-of-things technology called CAM (Cooperative Artefact Memory) that is used as a collaborative tool in design studio environments. CAM works as an object memory technology and allows industrial and product designers to collaboratively store relevant information onto their physical design objects, such as sketches, collages, storyboards, and physical mock-ups in the form of messages, annotations and external web links. In the context of this study, CAM serves as an important probing device to understand designers' interaction and experiences with augmented design objects, in their natural environment. The authors carried out a small-scale field trial of CAM in an academic design studio, over three student design projects. In this article, they discuss the findings of their field trial and show how CAM was used by the participants, how it was integrated into the design process and how it was appropriated for different purposes. The authors also found that CAM supported coordination and awareness within the design teams, yet its serendipitous and asynchronous nature facilitated creative and playful interactions between team members. In general, the results show how CAM transformed mundane design objects into “smart” objects that made the creative and playful side of cooperative design visible.

Platelet endothelial cell adhesion molecule 1 (PECAM-1) and its interactions with glycosaminoglycans: 2. Biochemical analyses

Platelet endothelial cell adhesion molecule 1 (PECAM-1) (CD31), a member of the immunoglobulin (Ig) superfamily of cell adhesion molecules with six Ig-like domains, has a range of functions, notably its contributions to leukocyte extravasation during inflammation and in maintaining vascular endothelial integrity. Although PECAM-1 is known to mediate cell adhesion by homophilic binding via domain 1, a number of PECAM-1 heterophilic ligands have been proposed. Here, the possibility that heparin and heparan sulfate (HS) are ligands for PECAM-1 was reinvestigated. The extracellular domain of PECAM-1 was expressed first as a fusion protein with the Fc region of human IgG1 fused to domain 6 and second with an N-terminal Flag tag on domain 1 (Flag-PECAM-1). Both proteins bound heparin immobilized on a biosensor chip in surface plasmon resonance (SPR) binding experiments. Binding was pH-sensitive but is easily measured at slightly acidic pH. A series of PECAM-1 domain deletions, prepared in both expression systems, were tested for heparin binding. This revealed that the main heparin-binding site required both domains 2 and 3. Flag-PECAM-1 and a Flag protein containing domains 1-3 bound HS on melanoma cell surfaces, but a Flag protein containing domains 1-2 did not. Heparin oligosaccharides inhibited Flag-PECAM-1 from binding immobilized heparin, with certain structures having greater inhibitory activity than others. Molecular modeling similarly identified the junction of domains 2 and 3 as the heparin-binding site and further revealed the importance of the iduronic acid conformation for binding. PECAM-1 does bind heparin/HS but by a site that is distinct from that required for homophilic binding.

Platelet endothelial cell adhesion molecule 1 (PECAM-1) and its interactions with glycosaminoglycans: 1. Molecular modeling studies

Platelet endothelial cell adhesion molecule 1 (PECAM-1) has many functions, including its roles in leukocyte extravasation as part of the inflammatory response and in the maintenance of vascular integrity through its contribution to endothelial cell−cell adhesion. PECAM-1 has been shown to mediate cell−cell adhesion through homophilic binding events that involve interactions between domain 1 of PECAM-1 molecules on adjacent cells. However, various heterophilic ligands of PECAM-1 have also been proposed. The possible interaction of PECAM-1 with glycosaminoglycans (GAGs) is the focus of this study. The three-dimensional structure of the extracellular immunoglobulin (Ig) domains of PECAM-1 were constructed using homology modeling and threading methods. Potential heparin/heparan sulfate-binding sites were predicted on the basis of their amino acid consensus sequences and a comparison with known structures of sulfate-binding proteins. Heparin and other GAG fragments have been docked to investigate the structural determinants of their protein-binding specificity and selectivity. The modeling has predicted two regions in PECAM-1 that appear to bind heparin oligosaccharides. A high-affinity binding site was located in Ig domains 2 and 3, and evidence for a low-affinity site in Ig domains 5 and 6 was obtained. These GAG-binding regions were distinct from regions involved in PECAM-1 homophilic interactions.

Computational analyses of the catalytic and heparin-binding sites and their interactions with glycosaminoglycans in glycoside hydrolase family 79 endo-d-glucuronidase (heparanase)

Mammalian heparanase is an endo-β-glucuronidase associated with cell invasion in cancer metastasis, angiogenesis and inflammation. Heparanase cleaves heparan sulfate proteoglycans in the extracellular matrix and basement membrane, releasing heparin/heparan sulfate oligosaccharides of appreciable size. This in turn causes the release of growth factors, which accelerate tumor growth and metastasis. Heparanase has two glycosaminoglycan-binding domains; however, no three-dimensional structure information is available for human heparanase that can provide insights into how the two domains interact to degrade heparin fragments. We have constructed a new homology model of heparanase that takes into account the most recent structural and bioinformatics data available. Heparin analogs and glycosaminoglycan mimetics were computationally docked into the active site with energetically stable ring conformations and their interaction energies were compared. The resulting docked structures were used to propose a model for substrates and conformer selectivity based on the dimensions of the active site. The docking of substrates and inhibitors indicates the existence of a large binding site extending at least two saccharide units beyond the cleavage site (toward the nonreducing end) and at least three saccharides toward the reducing end (toward heparin-binding site 2). The docking of substrates suggests that heparanase recognizes the N-sulfated and O-sulfated glucosamines at subsite +1 and glucuronic acid at the cleavage site, whereas in the absence of 6-O-sulfation in glucosamine, glucuronic acid is docked at subsite +2. These findings will help us to focus on the rational design of heparanase-inhibiting molecules for anticancer drug development by targeting the two heparin/heparan sulfate recognition domains.

The structure of glycosaminoglycans and their interactions with proteins

Glycosaminoglycans (GAGs) are important complex carbohydrates that participate in many biological processes through the regulation of their various protein partners. Biochemical, structural biology and molecular modelling approaches have assisted in understanding the molecular basis of such interactions, creating an opportunity to capitalize on the large structural diversity of GAGs in the discovery of new drugs. The complexity of GAG–protein interactions is in part due to the conformational flexibility and underlying sulphation patterns of GAGs, the role of metal ions and the effect of pH on the affinity of binding. Current understanding of the structure of GAGs and their interactions with proteins is here reviewed: the basic structures and functions of GAGs and their proteoglycans, their clinical significance, the three-dimensional features of GAGs, their interactions with proteins and the molecular modelling of heparin binding sites and GAG–protein interactions. This review focuses on some key aspects of GAG structure–function relationships using classical examples that illustrate the specificity of GAG–protein interactions, such as growth factors, anti-thrombin, cytokines and cell adhesion molecules. New approaches to the development of GAG mimetics as possible new glycotherapeutics are also briefly covered.

Computational methods for the prediction of the structure and interactions of coiled-coil peptides

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

Free energy calculations of glycosaminoglycan - Protein interactions

Glycosaminoglycans (GAGs) are complex highly charged linear polysaccharides that have a variety of roles in biological processes. We report the first use of molecular dynamics (MD) free energy calculations using the MM/PBSA method to investigate the binding of GAGs to protein molecules, namely the platelet endothelial cell adhesion molecule 1 (PECAM-1) and annexin A2. Calculations of the free energy of the binding of heparin fragments of different sizes reveal the existence of a region of low GAG-binding affinity in domains 5-6 of PECAM-1 and a region of high affinity in domains 2-3, consistent with experimental data and ligand-protein docking studies. A conformational hinge movement between domains 2 and 3 was observed, which allows the binding of heparin fragments of increasing size (pentasaccharides to octasaccharides) with an increasingly higher binding affinity. Similar simulations of the binding of a heparin fragment to annexin A2 reveal the optimization of electrostatic and hydrogen bonding interactions with the protein and protein-bound calcium ions. In general, these free energy calculations reveal that the binding of heparin to protein surfaces is dominated by strong electrostatic interactions for longer fragments, with equally important contributions from van der Waals interactions and vibrational entropy changes, against a large unfavorable desolvation penalty due to the high charge density of these molecules.

Molecular dynamics simulations of CXCL-8 and its interactions with a receptor peptide, heparin fragments, and sulfated linked cyclitols

CXCL-8 (Interleukin 8) is a CXC chemokine with a central role in the human immune response. We have undertaken extensive in silico analyses to elucidate the interactions of CXCL-8 with its various binding partners, which are crucial for its biological function. Sequence and structure analyses showed that residues in the thirdq β-sheet and basic residues in the heparin binding site are highly variable, while residues in the second β-sheet are highly conserved. Molecular dynamics simulations in aqueous solution of dimeric CXCL-8 have been performed with starting geometries from both X-ray and NMR structures showed shearing movements between the two antiparallel C-terminal helices. Dynamic conservation analyses of these simulations agreed with experimental data indicating that structural differences between the two structures at quaternary level arise from changes in the secondary structure of the N-terminal loop, the 310-helix, the 30s, 40s, and 50s loops and the third β-sheet, resulting in a different interhelical separation. Nevertheless, the observation of these different states indicates that CXCL-8 has the potential to undergo conformational changes, and it seems likely that this feature is relevant to the mode of binding of glycosaminoglycan (GAG) mimetics such as cyclitols. Simulations of the receptor peptide fragment−CXCL-8 complex identified several specific interactions of the receptor peptide with CXCL-8 that could be exploited in the structure-based design of competitive peptides and nonpeptidic molecules targeting CXCL-8 for combating inflammatory diseases. Simulations of the CXCL-8 dimer complexed with a 24-mer heparin fragment and of the CXCL-8−receptor peptide complex revealed that Arg60, Lys64, and Arg68 in the dimer bind to cyclitols in a horseshoe pattern, defining a region which is spatially distinct from the receptor binding site. There appears to be an optimum number of sulfates and an optimum length of alkyl spacers required for the interaction of cyclitol inhibitors with the dimeric form of CXCL-8. Calculation of the binding affinities of cyclitol inhibitors reflected satisfactorily the ranking of experimentally determined inhibitory potencies. The findings of these molecular modeling studies will help in the search for inhibitors which can modulate various CXCL-8 biological activities and serve as an excellent model system to study CXC-inhibitor interactions.

Free energy calculations of the interactions of c-Jun-based synthetic peptides with the c-Fos protein

The c-Fos–c-Jun complex forms the activator protein 1 transcription factor, a therapeutic target in the treatment of cancer. Various synthetic peptides have been designed to try to selectively disrupt the interaction between c-Fos and c-Jun at its leucine zipper domain. To evaluate the binding affinity between these synthetic peptides and c-Fos, polarizable and nonpolarizable molecular dynamics (MD) simulations were conducted, and the resulting conformations were analyzed using the molecular mechanics generalized Born surface area (MM/GBSA) method to compute free energies of binding. In contrast to empirical and semiempirical approaches, the estimation of free energies of binding using a combination of MD simulations and the MM/GBSA approach takes into account dynamical properties such as conformational changes, as well as solvation effects and hydrophobic and hydrophilic interactions. The predicted binding affinities of the series of c-Jun-based peptides targeting the c-Fos peptide show good correlation with experimental melting temperatures. This provides the basis for the rational design of peptides based on internal, van der Waals, and electrostatic interactions.

3D extracellular matrix interactions modulate tumour cell growth, invasion and angiogenesis in engineered tumour microenvironments

Interactions between tumour cells and extracellular matrix proteins of the tumour microenvironment play crucial roles in cancer progression. So far, however, there are only a few experimental platforms available that allow us to study these interactions systematically in a mechanically defined three-dimensional (3D) context. Here, we have studied the effect of integrin binding motifs found within common extracellular matrix (ECM) proteins on 3D breast (MCF-7) and prostate (PC-3, LNCaP) cancer cell cultures, and co-cultures with endothelial and mesenchymal stromal cells. For this purpose, matrix metalloproteinase-degradable biohybrid poly(ethylene) glycol-heparin hydrogels were decorated with the peptide motifs RGD, GFOGER (collagen I), or IKVAV (laminin-111). Over 14 days, cancer spheroids of 100-200µm formed. While the morphology of poorly invasive MCF-7 and LNCaP cells was not modulated by any of the peptide motifs, the aggressive PC-3 cells exhibited an invasive morphology when cultured in hydrogels comprising IKVAV and GFOGER motifs compared to RGD motifs or nonfunctionalised controls. PC-3 (but not MCF-7 and LNCaP) cell growth and endothelial cell infiltration were also significantly enhanced in IKVAV and GFOGER presenting gels. Taken together, we have established a 3D culture model that allows for dissecting the effect of biochemical cues on processes relevant to early cancer progression. These findings provide a basis for more mechanistic studies that may further advance our understanding of how ECM modulates cancer cell invasion and how to ultimately interfere with this process.

A generic individual-based spatially explicit model as a novel tool for investigating insect-plant interactions: A case study of the behavioural ecology of frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Investigating the interactions of road users and pedestrians in a dynamic rail level crossing environment

There are 23,500 level crossings in Australia. In these types of environments it is important to understand what human factor issues are present and how road users and pedestrians engage with crossings. A series of on-site observations were performed over a 2-day period at a 3-track active crossing. This was followed by 52 interviews with local business owners and members of the public. Data were captured using a manual-coding scheme for recording and categorising violations. Over 700 separate road user and pedestrian violations were recorded, with representations in multiple categories. Time stamping revealed that the crossing was active for 59% of the time in some morning periods. Further, trains could take up to 4-min to arrive following its first activation. Many pedestrians jaywalked under side rails and around active boom gates. In numerous cases pedestrians put themselves at risk in order to beat or catch the approaching train, ignored signs to stop walking when the lights were flashing. Analysis of interview data identified themes associated with congestion, safety, and violations. This work offers insight into context specific issues associated with active level crossing protection.