Protein Subcellular Location: The Gap Between Prediction and Experimentation

Newly synthesized proteins in eukaryotic cells can only function well after they are accurately transported to specific organelles. The establishment of protein databases and the development of programs have accelerated the study of protein subcellular locations, but their comparisons and evaluations of the prediction accuracy of subcellular location programs in plants are lacking. In this study, we built a random test set of maize proteins to evaluate the accuracy of six commonly used programs of subcellular locations: iLoc-Plant, Plant-mPLoc, CELLO, WoLF PSORT, SherLoc2, and Predotar. Our results showed that the accuracy of prediction varied greatly depending on the programs and subcellular locations involved. The programs using homology search methods (iLoc-Plant and Plant-mPLoc) performed better than those using feature search methods (CELLO, WoLF PSORT, SherLoc2, and Predotar). In particular, iLoc-Plant achieved an 84.9% accuracy for proteins whose subcellular locations have been experimentally determined and a 74.3 % accuracy for all of the proteins in the test set. Regarding locations, the highest prediction accuracies for subcellular locations were obtained for the nucleus, followed by the cytoplasm, mitochondria, plastids, endoplasmic reticulum, and vacuoles, while the lowest were obtained for cell membrane, secreted, and multiple-location proteins. We discussed the accuracy of the six programs in this article. This study will assist plant biologists in choosing appropriate programs to predict the location of proteins and provide clues regarding their function, especially for hypothetical or novel proteins.