Abstract
BackgroundStudying the large-scale protein-protein interaction (PPI) network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes.ResultsWe used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively.ConclusionThe results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/).
Highlights
Studying the large-scale protein-protein interaction (PPI) network is important in understanding biological processes
2 Results We predicted a total of 567,441 porcine PPIs using 3 methods and constructed 4 PPI networks: Interolog, DMIST, motif-motif interactions from structural topology (M-MIST), and a combination of the 3 networks
The PPIs under the three methods could lead to many local perturbations in the network, and the global properties of the four networks are not likely to change significantly (Table 2)
Summary
We predicted a total of 567,441 porcine PPIs using 3 methods and constructed 4 PPI networks: Interolog, DMIST, M-MIST, and a combination of the 3 networks. The PPIs under the three methods could lead to many local perturbations in the network, and the global properties of the four networks are not likely to change significantly (Table 2). Connected proteins (hubs) with central roles in the network architecture are more essential in the PPI network than proteins with only a small number of interactions [30]. The probability P(k) of nodes was P(k)≈k-1.004, R2 = 0.559 This finding suggested that the network contained a small number of highly connected proteins and that a large number of proteins possessed only a few connections. In biological networks, this phenomenon is the so-called scale-free property. The betweenness value for each node n was normalized by dividing by the number of node pairs
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