Gene Ontology-driven inference of protein-protein interactions using inducers

Motivation: Protein-protein interactions (PPI) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectively, leading to superior prediction accuracies.

Results: An inducer (ULCA) in combination with a Random Forest classifier compares favorably to several sequenced-based methods, semantic similarity measures and multi-kernel approaches. On a newly created set of high-quality interaction data, the proposed method achieves high cross-species prediction accuracies (AUC ≤ 0.88), rendering it a valuable companion to sequence-based methods.

Availability: Software and datasets are available athttp://bioinformatics.org.au/go2ppi/

Roche´s xCELLigence RTCA HT System: Fully-automated Measurement of Therapeutic Targets` Cellular Activity

"Label-free technologies have entered the stage of cellular drug discovery and high-throughput screening (HTS). For the measurement of G protein-coupled receptor (GPCR) activation electrical impedance represents an excellent universal readout technology, since different signaling pathways can be measured in one assay format using recombinant as well as primary cells. The recently developed xCELLigence RTCA HT Instrument from Roche Applied Science now allows to perform fully-automated impedance screens for GPCRs and other targets in the 384-well high-throughput format.
In a recent case study, Urs Lüthi and John Gatfield from Actelion Pharmaceuticals Ltd., Allschwil, Switzerland, integrated 2 RTCA HT (real-time cell analyzer for high-throughput) Instruments on an automated high-throughput screening platform from Agilent Technologies (Santa Clara, US). 263 antagonist hits of the orexin type 1 (Ox1) GPCR that had been identified in a classical calcium flux (FLIPR) HTS were screened for Ox1 inhibition in fully-automated RTCA HT assays. The overall performance, the quality of E-Plates 384 and intra- and inter-assay reproducibility were evaluated. 65% of the 263 antagonist hits were confirmed to be Ox1 receptor antagonists after impedance measurements. According to the researchers, the RTCA HT Instrument could be readily integrated into automated workflows and delivered a highly reproducible data set, making the RTCA HT Instrument a powerful screening technology. 

Compared to standard readout technologies one of the major advantages of label-free technologies is that cellular processes are measured in real-time kinetics in a non-invasive manner. The xCELLigence System uses gold electrodes at the bottom surface of microplate wells as sensors to which an alternating current is applied. Cells that are grown as adherent monolayers on top of such electrodes influence the alternating current at the electrodes by changing the electrical resistance (impedance). The degree of this change is primarily determined by the number of cells, strength of the cell-cell interactions, interactions of the cells with the microelectrodes and by the overall morphology of the cells."

Xlink-Identifier: An Automated Data Analysis Platform for Confident Identifications of Chemically Cross-Linked Peptides Using Tandem Mass Spectrometry

Chemical cross-linking combined with mass spectrometry provides a powerful method for identifying protein−protein interactions and probing the structure of protein complexes. A number of strategies have been reported that take advantage of the high sensitivity and high resolution of modern mass spectrometers. Approaches typically include synthesis of novel cross-linking compounds, and/or isotopic labeling of the cross-linking reagent and/or protein, and label-free methods. We report Xlink-Identifier, a comprehensive data analysis platform that has been developed to support label-free analyses. It can identify interpeptide, intrapeptide, and deadend cross-links as well as underivatized peptides. The software streamlines data preprocessing, peptide scoring, and visualization and provides an overall data analysis strategy for studying protein−protein interactions and protein structure using mass spectrometry. The software has been evaluated using a custom synthesized cross-linking reagent that features an enrichment tag. Xlink-Identifier offers the potential to perform large-scale identifications of protein−protein interactions using tandem mass spectrometry.
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Cytoscape

"Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and integrating with gene expression profiles and other state data. Additional features are available as plugins. Plugins are available for network and molecular profiling analyses, new layouts, additional file format support and connection with databases and searching in large networks. Plugins may be developed using the Cytoscape open Java software architecture by anyone and plugin community development is encouraged"


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Identification of functional modules in a ppi network by bounded diameter clustering.

Dense subgraphs of Protein-Protein Interaction (PPI) graphs are assumed to be potential functional modules and play an important role in inferring the functional behavior of proteins. Increasing amount of available PPI data implies a fast, accurate approach of biological complex identification. Therefore, there are different models and algorithms in identifying functional modules. This paper describes a new graph theoretic clustering algorithm that detects densely connected regions in a large PPI graph. The method is based on finding bounded diameter subgraphs around a seed node. The algorithm has the advantage of being very simple and efficient when compared with other graph clustering methods. This algorithm is tested on the yeast PPI graph and the results are compared with MCL, Core-Attachment, and MCODE algorithms.

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