Extension of protein topologies by ligand information: computation and visualization

<p>The Protein Topology Graph Library (PTGL) is a database of protein topologies that provides a web interface to compare and visualize protein folds based on the super-secondary structure. It uses a graph-based protein model related to earlier work by Koch et al.: the vertices of the protein graph represent the secondary structure elements<br>(SSEs) α-helix and β-sheet while the edges model contacts and spatial relations between these SSEs. Similarity between proteins is defined via common substructures in their protein graphs. In this work, the graph model has been extended to include ligand information and the new software VPLG that computes and visualizes the resulting protein graphs has been developed. VPLG reads and writes protein graphs in a custom text-based format, saves the resulting images in PNG or SVG format and comes with database support.</p

Comparison of protein topology graphs using graphlet-based methods

<p>With the rapidly growing amount of protein structures available in public databases like the RCSB Protein Data Bank, there is a strong need for developing fast and accurate comparison methods for proteins. Detecting functional similarity, evolutionary relationships and/or structural motifs at different description levels of proteins is of major interest for many applications in biology and molecular medicine. Although there already exist different methods for protein structure alignment, the search of protein structure databases is still time consuming and similarity between proteins can be defined in many ways.</p> <p> </p

Additional file 2 of The autophagy interaction network of the aging model Podospora anserina

Nucleotide sequence of the vector pGAD-HA. The sequence is provided as text-based FASTA file. (FASTA 8 kb

<i>In silico</i> knockout matrix.

<p>A row represents a protein knockout and a column the effect of the perturbation on a macromolecular <i>Salmonella</i> complex. A green entry indicates no effect and a red entry a negative effect, i.e., a reduced formation of a macromolecular complex. The numbers in some entries represent the reference literature of experimentally investigated effects: ¹ Huett et al. 2012 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref034" target="_blank">34</a>]; ² Thurston et al. 2012 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref006" target="_blank">6</a>], Li et al. 2013 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref033" target="_blank">33</a>]; ³ Thurston et al. 2012 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref006" target="_blank">6</a>]; ⁴ Cemma et al. 2011 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref038" target="_blank">38</a>]; ⁵ Zheng et al. 2009 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref007" target="_blank">7</a>], Cemma et al. 2011 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref038" target="_blank">38</a>]; ⁶ Wild et al. 2011 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref009" target="_blank">9</a>]; ⁷ Li et al. 2013 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref033" target="_blank">33</a>]; ⁸ Cemma et al. 2011 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref038" target="_blank">38</a>], Thurston et al. 2009 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref008" target="_blank">8</a>]; ⁹ Wild et al. 2011 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref009" target="_blank">9</a>], Radtke et al. 2007 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005200#pcbi.1005200.ref025" target="_blank">25</a>]. The results marked by an asterisk are biologically obvious and need no further experimental investigation. The knockout of the seven places <i>Ap:Gal8, Ap:Gal8:Ub, Ap:Gal8:Ub:N/S, Ap:Ub, Ap:Ub:N/S, Ap:Gal8:Ub:OPTNp, Ap:Ub:OPTNp</i> is experimentally investigated, if the fraction of LC3/GABARAP-positive <i>Salmonella</i> has been observed in the experiments.</p

The concept of Equality Point.

<p>Positive and negative equality points are illustrated respectively in the left and the right charts. The vertical axis <i>t</i> indicates the total time of algorithms and the horizontal axis <i>r</i> shows the number of random networks used for motif detection.</p

Schematic model of <i>Salmonella</i> xenophagy.

<p>Inside lumen of the mammalian small intestine, <i>Salmonella</i> invades epithelial cells and resides within the SCV. A fraction of the bacteria does not persist inside the SCV and enters the host cytosol. Before <i>Salmonella</i> gets cytosolic, <i>Salmonella</i> is inside a damaged SCV and is partially exposed to the cytosol. (A) Galectin-8 can bind to host glycans, which are normally hidden inside the SCV. Galectin-8 can target damaged SCV to the autophagic pathway by binding the autophagy receptor, NDP52. (B) Besides galectin-8, ubiquitin is an important eat-me signal for targeting <i>Salmonella</i> inside a damaged SCV to the autophagy pathway. <i>Salmonella</i> gets ubiquitinated by the E3 ubiquitin ligase, LRSAM1, and other E3 ubiquitin ligases. The autophagy receptors, p62, NDP52, and OPTN, serve as adaptors, which can bind both ubiquitin-chains and LC3/GABARAP molecules on phagophores. The binding affinity of OPTN with LC3 can be enhanced by TBK1 phosphorylation of OPTN. The hypothetical mechanism for TLR4-independent activation of TBK1 is depicted in a detailed view. TBK1 is recruited via the Nap1/Sintbad-NDP52 complex or the Nap1/Sintbad-NDP52 complex and OPTN to ubiquitinated <i>Salmonella</i>. This recruitment induces a high local concentration of TBK1 dimers, resulting in their oligomerization and autophosphorylation. (C) <i>Salmonella</i> that is already fully cytosolic, is only targeted by ubiquitin to the xenophagy pathway and not by galectin-8. (D) Autophagy is induced by intracellular amino acid (AA) starvation at 1–2 hr post infection (p.i.), which is assumed to be triggered by the damage of the SCV. The intracellular AA starvation results in the inhibition of mTOR—a subunit of mTORC1. Under AA starvation conditions, mTORC1 is inactivated and dissociates from the ULK1 complex, recovering the kinase activity of the ULK1 complex. The activated ULK1 complex seems to be required for the phagophore formation. The intracellular AA pool normalizes 3–4 hr p.i., and mTORC1 localizes at the surface of the SCV and gets reactivated.</p

Shh pathway affects lung fibroblast migration, invasion and collagen synthesis.

<p>(<b>A</b>) Accumulated distance of migration of primary human lung fibroblasts treated with Shh (500 ng/ml) or cyclopamine (10 µM) and monitored by live cell microscopy for 48 hours. The accumulated distance of migration of each cell was determined using ImageJ. ***p<0,01. (<b>B</b>) Scratch wound assay was performed in lung fibroblasts CCL206 treated or not with Shh at the doses indicated or with 10 µM cyclopamine (cyclop) for up to 48 hours. Migration of the cells was recorded using live cell microscopy and representative pictures at 1,5, 12,5 and 26 hours are shown. The colored lines indicate the border of cell migration in each case. (<b>C</b>) The area of the wound was quantified after 26 hours and the percentage of wound closure, relative to the initial area of scratch for each case, was determined. (<b>D</b>) Transmembrane invasion assay was performed in lung fibroblasts treated with Shh (500 ng/ml) or with cyclopamine (10 µM). (<b>E</b>) RT-qPCR was performed to assess MMP2 and MMP9 expression in fibroblasts treated or not with Shh (500 ng/ml) for 48hr. Results are presented as fold of mRNA levels in treated cells compared with non-treated cells. *p<0,1. (<b>F</b>) The total collagen content of lung fibroblasts treated with Shh (500 ng/ml) or TGF-ß1 (5 ng/ml) for the indicated times was quantified using the Sircol collagen assay. *p<0,1, **p<0,05.</p

<i>In silico</i> knockout matrix and the corresponding PN.

<p>(A) A small PN, consisting of three places, protein <i>A</i>, protein <i>B</i>, and a protein complex <i>AB</i>, and four transitions, <i>SynA</i>, <i>SynB</i>, <i>Bin</i>, and <i>Out</i>, which describe the synthesis of <i>A</i>, the synthesis of <i>B</i>, the binding of both proteins, and the outflow of the complex to the environment, respectively. (B) The <i>in silico</i> knockout matrix of the PN shown in part A. The matrix has a row for each input transition, <i>SynA</i> and <i>SynB</i>, and columns for each substance, <i>A</i>, <i>B</i>, and <i>AB</i>. The binary values of an entry are color-coded by either a red or a green circle. An entry becomes red, if the corresponding place is not the outgoing place of a transition that is part of a still functional T-invariant. The entry is green, if the corresponding place is still the output place of a transition that is part of a T-invariant. For the PN in part A, the knockout of either <i>SynA</i> or <i>SynB</i> is sufficient to have a negative effect on all substances, <i>A</i>, <i>B</i>, and <i>AB</i>. Consequently, all entries in the matrix are red. (C) The PN is modified by adding the output transitions, <i>DegA</i> and <i>DegB</i>. Now, the knockout analysis becomes more specific. The knockout of <i>SynA</i> blocks the production of <i>A</i> and complex <i>AB</i>, but <i>B</i> is not affected. Vice versa, the knockout of <i>SynB</i> leaves <i>A</i> unaffected. (D) The corresponding <i>in silico</i> knockout matrix of the modified PN shown in part C.</p

Sensitivity matrix of the <i>in silico</i> knockout analysis.

<p>The rows and the columns indicate the proteins knocked out. Thus, the diagonal of the matrix shows the results of the single knockouts and the other entries of the double knockouts. The numbers represent the percentage of T-invariants that are affected by a knockout. The colors indicate the impact on the xenophagy pathway (red = high, green = low).</p

QuateXelero (QX) vs. G-Tries in undirected networks.

<p>10 random networks were used in all experiments. To save the time, we use less than 100 random networks here. This does not deteriorate the validity of results, because (1) undirected networks are not sensitive to the number of random networks as are the directed networks (please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068073#pone-0068073-g008" target="_blank">figure 8</a>) and (2) we do not base our analysis and comparison on the reported total time, but on the equality points and average random census times, which are independent of the total time.</p