Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection
Andrés F. Flórez,Daeui Park,Jong Bhak,Byoung Chul Kim,Allan Kuchinsky,John H. Morris,Jairo Espinosa,Carlos Muskus +7 more
TLDR
In this paper, the protein interaction network of Leishmaniasis major was predicted by using three validated methods: PSIMAP, PEIMAP and iPfam, and calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions.Abstract:
Background: Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease. Results: We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets. Conclusion: We have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources.read more
Citations
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Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review
Peter Csermely,Tamas Korcsmaros,Tamas Korcsmaros,Huba Kiss,Gábor London,Ruth Nussinov,Ruth Nussinov +6 more
TL;DR: It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates and an optimized protocol of network-aided drug development is suggested, and a list of systems-level hallmarks of drug quality is provided.
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Drug repositioning for orphan diseases
TL;DR: This study will review some of the issues and the current methodologies adopted or proposed to overcome them and translate chemical and biological discoveries into safe and effective orphan disease therapeutics.
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The organisational structure of protein networks: revisiting the centrality–lethality hypothesis
TL;DR: The centrality–lethality hypothesis holds goods for a large number of organisms, with certain limitations, and it is observed that essential nodes in a network have a significantly higher average degree and betweenness centrality, compared to the network average.
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Gene network analysis reveals the association of important functional partners involved in antibiotic resistance: A report on an important pathogenic bacterium Staphylococcus aureus.
TL;DR: A model based on protein/gene network is proposed to identify genes/proteins associated with drug resistance in S. aureus and reveals many associated antibiotic resistant genes and proteins and their role in resistance mechanisms.
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Prediction and Analysis of the Protein Interactome in Pseudomonas aeruginosa to Enable Network-Based Drug Target Selection
TL;DR: The predicted interactome network from this study is the first large-scale PPI network in PA with significant coverage and high accuracy, and subsequent analysis, including validations based on existing small-scalePPI data and the network structure comparison with other model organisms, shows the validity of the predicted P PI network.
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