Tripartite network of drugs and complexes connected to Parkinson disease.

<p>Links between the disease node and protein complexes represent associations between genes involved in these complexes and the named disease, as specified by the Disease Ontology. Links between protein complexes and drugs are the same as in our bipartite network, meaning that a drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The disease node is represented by a yellow circle. The size of nodes is proportional to the degree of each node; a size scale is displayed on the right-hand side of the figure.</p

Top drug and complex hubs in the bipartite protein complex – drug network.

<p>Top drug and complex hubs in the bipartite protein complex – drug network.</p

Bipartite network of protein complexes and drugs, and associated modules.

<p>A drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. Drugs and protein complexes are labeled by their DrugBank and CORUM identifier, respectively; mappings between these database identifiers and common names are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030028#pone.0030028.s002" target="_blank">Information S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030028#pone.0030028.s003" target="_blank">S3</a>.</p

Example of bipartite and projected networks.

<p>(a) A bipartite sub-network extracted from the complex-drug network. (b) The drug and protein complex projected networks. Drugs are denoted by diamonds and complexes by circles.</p

Tripartite network of drugs and protein complexes connected to Leigh disease.

<p>Links between the disease node and protein complexes represent associations between genes involved in these complexes and the named disease, as specified by the Disease Ontology. Links between protein complexes and drugs are the same as in our bipartite network, meaning that a drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The disease node is represented by a yellow circle. The size of nodes is proportional to the degree of each node; a size scale is displayed on the right-hand side of the figure.</p

Projected network of drug modules.

<p>Each module of the protein complex – drug bipartite network was shrunk into a node and the drug projection of the resulting network is represented. Modules are named according to a representative drug hub inside the module. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The size of nodes is proportional to the number of drugs in each module; a size scale is displayed on the right-hand side of the figure. To assign names to condensed nodes, we chose a representative member of each module by selecting the complex with the highest degree inside the module. In the case of protein complex names formed by association of numerous protein names, we selected the protein occurring most frequently in complexes connected to the complex of highest degree.</p

Network metrics in projected networks of modules.

<p>Top panels are from the drug projection and bottom panels from the complex projection. Left side panels represent betweenness centrality and right side panels closeness centrality.</p

Additional file 1: of Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis

List of primers used for qPCR analyses of the expression of the DUSP mRNAs examined in this study. Description: All sequences are of human origin except for beta actin, which is from mouse. (DOCX 198 kb

<i>In silico</i> node knockouts predict a Sos1/Ras/Raf/MEK1/2/ERK1/2/p90RSK negative feedback loop affects Rac1 and RhoA dynamics via the Rac1 activation Sos1-Eps8-Abi1 complex.

<p><b>A.</b> Effect of individual <i>in silico</i> node knockout of every non-output node in the model on RhoA/Rac1 output dynamics. Node knockouts were performed by removing all inward edges for each node individually such that the knocked out node remained OFF for all time, except for inhibitory nodes with no input edges PTEN, Ship2 and PP2a which were set to ON. Note ‘Rac1 to RhoA switch’ output corresponds to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004909#pcbi.1004909.g001" target="_blank">Fig 1B and 1E</a> and cyclic output corresponds to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004909#pcbi.1004909.g001" target="_blank">Fig 1C and 1F</a>. <b>B-C.</b> Selected steady-state node activity for the Sos1E > pRacGAP1 > RalbP1, Vav2 cyclic activity inducing hierarchy for proteins affecting Rac1 and RhoA dynamics given knockout of <b>B</b> MEK1/2 and <b>C</b> Eps8. MEK1/2 is a critical node in the Sos1/Ras/Raf/MEK1/2/ERK1/2/p90RSK negative feedback loop, whereby removal of MEK1/2 keeps ERK1/2 and p90RSK inactive, which removes the inhibition of Sos1 keeping the Sos1-Eps8-Abi1 complex active which keeps Rac1 active and RhoA inactive and abrogates the pro-invasive Rac1 to RhoA switch. Eps8 removal prevents formation of the Sos1-Eps8-Abi1complex which prevents activation of Rac1 regardless of activity state of Sos1/Ras/Raf/MEK1/2/ERK1/2/p90RSK negative feedback loop nodes. <b>D-E.</b> Western blots showing steady state endogenous levels of phosphorylated p44 and p42 MAP Kinase (Erk1 and Erk2) and total levels of ERK2 (for loading) for cells treated with a single MEK1/2 inhibitor, PD184352 or AZD6244, or DMSO for vehicle for different cell types: <b>D.</b> H1299s, a non-small lung cell carcinoma, either stably expressing mutant p53 (right) or with an empty for p53 (left); <b>E.</b> A2780s, an epithelial ovarian cancer cell line, with (right) and without (left) stimulation with cRGDfV. Numbers below each band denote the intensity level normalised to the corresponding DMSO control. <b>F-J.</b> Effects of MEK1/2 inhibition on 2-D cell migration in >10 hour scratch wound experiments. <b>F.</b> Average speed of tracked H1299 cells over the time taken for wounds to close or 16 hours (whichever comes first). Cells expressing mutant p53 or with an empty vector for p53 were treated with DMSO or MEK1/2 inhibitors ~1 hour prior to imaging. <b>G.</b> Average persistence of the same tracked cells as in F. persistence is the measure of the distance between the cells first time-point position and last time-point position divided by the total distance travelled by cell between every time point position. <b>H.</b> Average speed of tracked A2780s cells for the same conditions as in F, cells were treated with cRGDfV at the same time as DMSO/MEK1/2 inhibitors ~1 hour prior to imaging. <b>I.</b> Average persistence for same tracked A2780 cells. Data are representative of 3 experiments, and 90 cells were tracked per condition. Graphs are Tukey boxplots where + represents the mean of each condition. **** indicates one way ANOVA with post-hoc Tukey HSD with p-value < 0.0001, * indicates p-value < 0.05 <b>J.</b> Representative images of H1299 cells in a sub-domain of an image at t = 0 (the initial frame) and the same sub-domain at t = 5 hours (30 10 minute frames later), for cells without/with mutant p53 expression and treated with DMSO or MEK1/2 inhibitor AZD6244. Yellow arrow heads indicate lamellipodial leading edge actin, while red arrow heads indicate more spike-like protrusions. The same cell is highlighted with arrow heads at t = 0 and t = 5 hours for each different condition.</p

Logical simulation of integrin-driven cell migration.

<p><b>A.</b> Reconstructed network describing signalling events leading to GTPase activity. The model consists of one input node, EGF, two nominated output nodes, Rac1 and RhoA, and 38 intermediate nodes. Reactions included in the model are activation or inhibition, where some reactions need cooperation of two or more upstream nodes via AND gates. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004909#pcbi.1004909.s012" target="_blank">S1 Table</a> for references to all reactions included in the model. <b>B, C.</b> Time-course simulation outputs for the first 50 time increments of the model for different Rac1 activator/inhibitor hierarchies, where the outputs of interest Rac1 and RhoA (yellow box) and the dominant Rac1 activator/inhibitor (green box) are highlighted: <b>B.</b> pRacGAP1 dominates Rac1 activity above all Rac1 activator. As pRacGAP1 activity is ‘switched’ ON, Rac1 activity is ‘switched’ OFF after one time increment, RhoA activity is ‘switched’ ON a further time increment later and Rac1/RhoA remain OFF/ON respectively as t → ∞; <b>C.</b> Sos1E dominates Rac1 activity over pRacGAP1 which in turn dominates Rac1 activity over Vav2 and RalbP1. Initially pRacGAP1 activation switches OFF Rac1 which switches on RhoA later as before, however when Sos1E is ‘switched’ ON (green box), Rac1 is ‘switched’ ON after one time increment and then RhoA is ‘switched’ OFF after one further time increment. When Sos1E is later ‘switched’ OFF, Rac1 and subsequently RhoA are switched OFF/ON respectively, leading to cyclic activity of Rac1 nd RhoA as t → ∞. <b>D-F.</b> Steady-state outputs of the model for simulations with example different Rac1 activator/inhibitor hierarchies (full list of hierarchies in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004909#pcbi.1004909.s014" target="_blank">S3 Table</a>), where activator/inhibitor dominance is visualised by reaction arrow thickness: <b>D.</b> All Rac1 activators Vav2, RalbP1 and Sos1E (Sos1-Eps8-Abi1 complex) (thick black arrows) dominate Rac1 activity over the Rac1 inhibitor pRacGAP1 (thin red arrow); <b>E.</b> pRacGAP1 (thick red arrow) dominates Rac1 activity over Vav2, RalbP1 and Sos1E (thin black arrows); <b>F.</b> Sos1E (thick black arrow) dominates Rac1 activity over pRacGAP1 (medium red arrow) which in turn dominates Rac1 activity over Vav2 and RalbP1 (thin black arrows). Note steady-state outputs in the Boolean simulations can only be stable activity where the node is ON for all time as t → ∞ (green), stable inactivity where the node is OFF for all time as t → ∞ (red) and cyclic activity where the node is encapsulated in a stable limit cycle and cycles regularly between ON and OFF activity as t → ∞ (yellow). All simulations performed in CellNetAnalyzer.</p