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Table 3 Prediction of isoelectric points for SWISS-2DPAGE and PIP-DB databases

From: IPC – Isoelectric Point Calculator

Method SWISS-2DPAGE Method PIP-DB
RMSD % Outliers RMSD % Outliers
IPC_protein 0.476 0 10 IPC_protein 1.019 0 141
Toseland 0.521 10.9 18 Toseland 1.086 16.7 153
Bjellqvist 0.590 30.0 31 Bjellqvist 1.085 16.3 150
ProMoST 0.597 32.1 29 Dawson 1.081 15.3 161
Dawson 0.599 32.5 37 Wikipedia 1.087 16.9 163
Wikipedia 0.619 39.0 35 Rodwell 1.095 19.1 167
Rodwell 0.628 41.7 37 Grimsley 1.121 26.6 170
Grimsley 0.572 24.5 21 Solomons 1.103 21.4 159
Solomons 0.635 44.2 44 Lehninger 1.102 21.1 161
Lehninger 0.640 45.8 44 ProMOST 1.111 23.5 150
Nozaki 0.679 59.4 43 pIR 1.152 35.8 184
Thurlkill 0.691 63.9 39 Nozaki 1.165 39.9 170
DTASelect 0.677 58.8 35 Thurlkill 1.180 44.9 176
EMBOSS 0.724 76.9 49 DTASelect 1.186 47.1 173
Sillero 0.721 75.5 50 pIPredict 1.195 50.0 182
pIR 0.761 92.4 37 EMBOSS 1.198 51.2 191
pIPredict 0.768 95.9 33 Sillero 1.202 52.4 187
Patrickios 1.600 1227.9 243 Patrickios 2.623 3918 604
Avg_pIa 0.614 37.1 32 Avg_pIa 1.101 20.9 160
  1. aAverage from all pKa sets without the Patrickios (highly simplified pKa set) and IPC sets. Note, that the average pI is calculated on the level of individual protein or peptide
  2. Both SWISS-2DPAGE and PIP-DB were cleaned of outliers (MSE > 3 between experimental pI and average predicted pI) and clustered by CD-HIT with 99 % sequence identity threshold, as described in the Materials and Methods (982 and 1,307 proteins, respectively), but they were not divided into training and testing datasets. Thus, the results for the IPC sets are slightly overestimated, but this is not relevant, as shown by the comparison of Tables 1 and 2
  3. Outliers correspond to the number of predictions for which the difference between the experimental pI and the predicted pI exceeded the threshold of an MSE of 3 for the protein dataset