IPC – Isoelectric Point Calculator

Biology Direct

Table 2 Prediction of isoelectric point on the 75 % training datasets

Method	Protein dataset			Method	Peptide dataset
Method	RMSD	%	Outliers	Method	RMSD	%	Outliers
IPC_protein	0.838	0	114	IPC_peptide	0.247	0	635
Toseland	0.898	15.0	131	Solomons	0.251	0.8	638
Bjellqvist	0.922	21.5	149	Lehninger	0.256	2.4	643
Dawson	0.920	20.9	156	EMBOSS	0.322	18.8	1088
Wikipedia	0.930	23.8	157	Wikipedia	0.413	46.3	4280
Rodwell	0.938	26.1	159	Sillero	0.426	50.9	3025
ProMoST	0.938	26.1	140	Toseland	0.427	51.2	3618
Grimsley	0.939	26.2	147	Dawson	0.432	52.9	4192
Solomons	0.947	28.5	159	Thurlkill	0.480	70.8	4017
Lehninger	0.947	28.7	160	Rodwell	0.506	81.2	4061
pIR	1.026	54.2	180	DTASelect	0.541	96.8	4902
Nozaki	1.005	47.1	169	Nozaki	0.599	124.8	4013
Thurlkill	1.018	51.5	173	Grimsley	0.611	130.9	4609
DTASelect	1.017	51.1	167	Bjellqvist	0.661	159.2	4672
pIPredict	1.057	65.9	173	pIPredict	1.024	497.8	8051
EMBOSS	1.040	59.4	189	ProMOST	1.233	867.5	7999
Sillero	1.042	60.1	188	pIR	1.862	4020.9	9921
Patrickios	2.237	2405.1	645	Patrickios	1.977	5266.8	8131
Avg_pI^a	0.940	26.6	151	Avg_pI	0.451	59.7	4600

^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
Protein dataset (IPC_protein trained on 1,743 proteins with 10-fold cross-validation – data in the table above, tested on 581 proteins not used for training – data in Table 1), peptide dataset (IPC trained on 12,662 peptides with 10-fold cross-validation – data in above table, tested on 4,220 peptides not used for training – data in Table 1). Changes in method order in comparison to Table 1 are in bold
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 and an MSE of 0.25 for the peptide dataset

ISSN: 1745-6150