ArticleBMC proceedings2013
Highly precise protein-protein interaction prediction based on consensus between template-based and de novo docking methods.
Article in BMC proceedings, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Computational Network Inference for Bacterial Interactomics.mSystems · 2022Review
- A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level.BioMed research international · 2022Review
- From complete cross-docking to partners identification and binding sites predictions.PLoS computational biology · 2022Article
- Bag-1 stimulates Bad phosphorylation through activation of Akt and Raf kinases to mediate cell survival in breast cancer.BMC cancer · 2019Article
- Attention mechanism enhanced LSTM with residual architecture and its application for protein-protein interaction residue pairs prediction.BMC bioinformatics · 2019Article
- Article
- MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.BMC bioinformatics · 2018Article
- Building protein-protein interaction networks for Leishmania species through protein structural information.BMC bioinformatics · 2018Article
- A proximity-based graph clustering method for the identification and application of transcription factor clusters.BMC bioinformatics · 2017Article
- Aurora kinase A regulates Survivin stability through targeting FBXL7 in gastric cancer drug resistance and prognosis.Oncogenesis · 2017Article
- Non-interacting proteins may resemble interacting proteins: prevalence and implications.Scientific reports · 2017Article
- Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundElucidation of protein-protein interaction (PPI) networks is important for understanding disease mechanisms and for drug discovery. Tertiary-structure-based in silico PPI prediction methods have been developed with two typical approaches: a method based on template matching with known protein structures and a method based on de novo protein docking. However, the template-based method has a narrow applicable range because of its use of template information, and the de novo docking based method does not have good prediction performance. In addition, both of these in silico prediction methods have insufficient precision, and require validation of the predicted PPIs by biological experiments, leading to considerable expenditure; therefore, PPI prediction methods with greater precision are needed.
resultsWe have proposed a new structure-based PPI prediction method by combining template-based prediction and de novo docking prediction. When we applied the method to the human apoptosis signaling pathway, we obtained a precision value of 0.333, which is higher than that achieved using conventional methods (0.231 for PRISM, a template-based method, and 0.145 for MEGADOCK, a non-template-based method), while maintaining an F-measure value (0.285) comparable to that obtained using conventional methods (0.296 for PRISM, and 0.220 for MEGADOCK).
conclusionsOur consensus method successfully predicted a PPI network with greater precision than conventional template/non-template methods, which may thus reduce the cost of validation by laboratory experiments for confirming novel PPIs from predicted PPIs. Therefore, our method may serve as an aid for promoting interactome analysis.
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