Using protein-protein interaction network information to predict the subcellular locations of proteins in budding yeast

The information of protein subcellular localization is vitally important for in-depth understanding the intricate pathways that regulate biological processes at the cellular level. with the rapidly increasing number of newly found protein sequence in the post-genomic age,many automated methods have been developed attempting to help annotate their subcellular locations in a timely manner. however,very few of them were developed using the protein-protein interaction (ppi) network information. in this paper,we have introduced a new concept called tethering potential' by which the ppi information can be effectively fused into the formulation for protein samples. based on such a network frame,a new predictor called yeast-ploc has been developed for identifying budding yeast proteins among their 19 subcellular location sites. meanwhile,a purely sequence-based approach,called the hybrid-property' method,is integrated into yeast-ploc as a fall-back to deal with those proteins without sufficient ppi information. the overall success rate by the jackknife test on the 4,683 yeast proteins in the training dataset was 70.25%. furthermore,it was shown that the success rate by yeast- ploc on an independent dataset was remarkably higher than those by some other existing predictors,indicating that the current approach by incorporating the ppi information is quite promising. as a user-friendly web-server,yeast-ploc is freely accessible at http://yeastloc.biosino.org/. © 2012 bentham science publishers.