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[This corrects the article DOI: 10.1371/journal.pone.0162407.].

The integration of data and knowledge from heterogeneous sources can be a key success factor in drug design, drug repurposing and multi-target therapies. In this context, biological networks provide a useful instrument to highlight the relationships and to model the phenomena underlying therapeutic action in cancer. In our work, we applied network-based modeling within a novel bioinformatics pipeline to identify promising multi-target drugs. Given a certain tumor type/subtype, we derive a disease-specific Protein-Protein Interaction (PPI) network by combining different data-bases and knowledge repositories. Next, the application of suitable graph-based algorithms allows selecting a set of potentially interesting combinations of drug targets. A list of drug candidates is then extracted by applying a recent data fusion approach based on matrix tri-factorization. Available knowledge about selected drugs mechanisms of action is finally exploited to identify the most promising candidates for planning in vitro studies. We applied this approach to the case of Triple Negative Breast Cancer (TNBC), a subtype of breast cancer whose biology is poorly understood and that lacks of specific molecular targets. Our "in-silico" findings have been confirmed by a number of in vitro experiments, whose results demonstrated the ability of the method to select candidates for drug repurposing.

Background: HaloTag is a modified bacterial enzyme that binds rapidly and irreversibly to an array of synthetic ligands, including chemical dyes. When expressed in live cells in conjunction with a protein of interest, HaloTag can be used to study protein trafficking, synthesis, and degradation. For instance, sequential HaloTag labeling with spectrally separable dyes can be used to separate preexisting protein pools from proteins newly synthesized following experimental manipulations or the passage of time. Unfortunately, incomplete labeling by the first dye, or labeling by residual, trapped dye pools can confound interpretation. Methods: Labeling specificity of newly synthesized proteins could be improved by blocking residual binding sites. To that end, we synthesized a non-fluorescent, cell permeable blocker (1-chloro-6-(2-propoxyethoxy)hexane; CPXH), essentially the HaloTag ligand backbone without the reactive amine used to attach fluorescent groups. Results: High-content imaging was used to quantify the ability of CPXH to block HaloTag ligand binding in live HEK cells expressing a fusion protein of mTurquoise2 and HaloTag. Full saturation was observed at CPXH concentrations of 5-10 µM at 30 min. No overt effects on cell viability were observed at any concentration or treatment duration. The ability of CPXH to improve the reliability of newly synthesized protein detection was then demonstrated in live cortical neurons expressing the mTurquoise2-HaloTag fusion protein, in both single and dual labeling time lapse experiments. Practically no labeling was observed after blocking HaloTag binding sites with CPXH when protein synthesis was suppressed with cycloheximide, confirming the identification of newly synthesized protein copies as such, while providing estimates of protein synthesis suppression in these experiments. Conclusions: CPXH is a reliable (and inexpensive) non-fluorescent ligand for improving assessment of protein-of-interest metabolism in live cells using HaloTag technology.

Background: HaloTag is a modified bacterial enzyme that binds rapidly and irreversibly to an array of synthetic ligands, including chemical dyes. When expressed in live cells in conjunction with a protein of interest, HaloTag can be used to study protein trafficking, synthesis, and degradation. For instance, sequential HaloTag labeling with spectrally separable dyes can be used to separate preexisting protein pools from proteins newly synthesized following experimental manipulations or the passage of time. Unfortunately, incomplete labeling by the first dye, or labeling by residual, trapped dye pools can confound interpretation. Methods: Labeling specificity of newly synthesized proteins could be improved by blocking residual binding sites. To that end, we synthesized a non-fluorescent, cell permeable blocker (1-chloro-6-(2-propoxyethoxy)hexane; CPXH), essentially the HaloTag ligand backbone without the reactive amine used to attach fluorescent groups. Results: High-content imaging was used to quantify the ability of CPXH to block HaloTag ligand binding in live HEK cells expressing a fusion protein of mTurquoise2 and HaloTag. Full saturation was observed at CPXH concentrations of 5-10 µM at 30 min. No overt effects on cell viability were observed at any concentration or treatment duration. The ability of CPXH to improve the reliability of newly synthesized protein detection was then demonstrated in live cortical neurons expressing the mTurquoise2-HaloTag fusion protein, in both single and dual labeling time lapse experiments. Practically no labeling was observed after blocking HaloTag binding sites with CPXH when protein synthesis was suppressed with cycloheximide, confirming the identification of newly synthesized protein copies as such, while providing estimates of protein synthesis suppression in these experiments. Conclusions: CPXH is a reliable (and inexpensive) non-fluorescent ligand for improving assessment of protein-of-interest metabolism in live cells using HaloTag technology.

Maintaining synaptic integrity and function depends on the continuous removal and degradation of aged or damaged proteins. Synaptic protein degradation has received considerable attention in the context of synaptic plasticity and growing interest in relation to neurodegenerative and other disorders. Conversely, less attention has been given to constitutive, ongoing synaptic protein degradation and the roles canonical degradation pathways play in these processes. Here we briefly review recent progress on this topic and new experimental approaches which have expedited such progress and highlight several emerging principles. These include the realization that synaptic proteins typically have unusually long lifetimes, as might be expected from the remote locations of most synaptic sites; the possibility that degradation pathways can change with time from synthesis, cellular context, and physiological input; and that degradation pathways, other than ubiquitin-proteasomal-mediated degradation, might play key roles in constitutive protein degradation at synaptic sites. Finally, we point to the importance of careful experimental design and sufficiently sensitive techniques for studying synaptic protein degradation, which bring into account their slow turnover rates and complex life cycles.