Protein-protein interactions play key roles in cells. Lots of experimental approaches and in silico methods have been developed to identify and predict large-scale pro- tein-protein interactions. However, compared with the tradi- tionally experimental results, the high-throughput pro- tein-protein interaction data often contain the false positives in high probability. In order to fully utilize the large-scale data, it is necessary to develop bioinformatic methods for systematically evaluating those data in order to further im- prove the data reliability and mine biological information. This review summarizes the methodologies of analysis and application of high-throughput protein-protein interaction data, including the evaluation methods, the relationship be- tween protein-protein interaction data and other protein biological information, and their applications in biological study. In addition, this paper also suggests some interesting topics on mining high-throughput protein-protein interaction data.
Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions. We then constructed a chloroplast protein interaction network primarily based on these core protein interactions. The network had 22 925 protein interaction pairs which involved 2 214 proteins. A total of 160 previously uncharacterized proteins were annotated in this network. The subunits of the photosynthetic complexes were modularized, and the functional relationships among photosystem Ⅰ （PSI）, photosystem Ⅱ （PSII）, light harvesting complex of photosystem Ⅰ （LHC Ⅰ） and light harvesting complex of photosystem Ⅰ （LHC Ⅱ） could be deduced from the predicted protein interactions in this network. We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis. Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.
