Table 1.
Comparison of the performance of cNLS Mapper with those of other prediction methods
| Predictor | NLS class | Prediction performance, % |
||
|---|---|---|---|---|
| Sens | Spec | Accur | ||
| cNLS Mapper | Class 1/2 | 99 | 94 | 98 |
| Class 3 | 100 | 100 | 100 | |
| Class 4 | 87 | 97 | 92 | |
| Bipartite | 87 | 82 | 85 | |
| PSORT II | Class 1/2 | 76 | 33 | 65 |
| Class 3 | 0 | 100 | 9 | |
| Class 4 | 39 | 79 | 62 | |
| Bipartite | 71 | 48 | 63 | |
| PredictNLS | Class 1/2 | 4 | 94 | 27 |
| Class 3 | 0 | 100 | 9 | |
| Class 4 | 0 | 100 | 56 | |
| Bipartite | 0 | 100 | 33 | |
The prediction accuracies of the cNLS Mapper, PSORT II (http://psort.nibb.ac.jp/form2.html), and PredictNLS (http://cubic.bioc.columbia.edu/predictNLS/) programs were determined by using test peptide sequences derived from synthetic NLS mutants (see Figs. S2, S5, and S6), in which at least 3 flanking residues were simultaneously mutated, and bipartite NLSs screened from biXs libraries (5). The test sequences were divided into 2 fractions, positive and negative sequences, based on the NLS activity determined in yeast: The former has a high or medium level of NLS activity, corresponding to scores of 6–10 (or GFP localization phenotypes N and Nc), and the latter has little NLS activity, corresponding to scores of 1 or 2 (or a phenotype C). Sequences with scores of 3–5 (or an NC phenotype) were omitted. We note that many of our negative sequences for class 2 and bipartite NLSs contain classical consensus sequences. The total number of positive and negative test sequences was 138 and 48 for class 1/2 NLSs, respectively, 51 and 5 for class 3 NLSs, 23 and 29 for class 4 NLSs, and 388 and 195 for bipartite NLSs. To increase the length of the test sequences, additional sequences comprising 6–9 residues, which were derived from the pTUE-GFP cloning site, were added to both termini of the test sequences. Both the prediction sensitivity (Sens) and specificity (Spec) achieved with cNLS Mapper were calculated as the percentages of true positives with calculated scores of >4 in the positive NLS fraction and true negatives with calculated scores of ≤4 in the negative NLS fraction. Prediction accuracy (Accur) was calculated as the percentage of the sum of true positives and true negatives.