Protein electrostatics and pKa blind predictions; contribution from empirical predictions of internal ionizable residues

TY - JOUR

T1 - Protein electrostatics and pKa blind predictions; contribution from empirical predictions of internal ionizable residues

AU - Olsson, Mats H. M.

PY - 2011/12

Y1 - 2011/12

N2 - In this study, we validate and probe the description of electrostatic interactions within proteins by predicting and comparing pK a values of ionizable groups in a series of mutated staphylococcal nuclease variants with experiments. This set of pK a values is found to be the most challenging pK a data to date, because ionizable residues have been introduced in hydrophobic patches in the protein interior and are therefore significantly shifted from their reference solvated values. We find that using PROPKA2 (Li et al., Proteins 2005;61:704-721) results in an rmsd value close to 2 for true blind predictions (1.6 if we reassign the tightly coupled Asp19/21 pair) and close to 1 for postpredictions with the newly developed PROPKA3 (Olsson et al., J. Chem. Theor. Comp. 2011;7:525-537). We also use the performance of the Null-model, predictions made with the reference value only, to provide a better description of the expected errors in pK a predictions and to compare submissions made using different subsets of the pK a data more consistently.

AB - In this study, we validate and probe the description of electrostatic interactions within proteins by predicting and comparing pK a values of ionizable groups in a series of mutated staphylococcal nuclease variants with experiments. This set of pK a values is found to be the most challenging pK a data to date, because ionizable residues have been introduced in hydrophobic patches in the protein interior and are therefore significantly shifted from their reference solvated values. We find that using PROPKA2 (Li et al., Proteins 2005;61:704-721) results in an rmsd value close to 2 for true blind predictions (1.6 if we reassign the tightly coupled Asp19/21 pair) and close to 1 for postpredictions with the newly developed PROPKA3 (Olsson et al., J. Chem. Theor. Comp. 2011;7:525-537). We also use the performance of the Null-model, predictions made with the reference value only, to provide a better description of the expected errors in pK a predictions and to compare submissions made using different subsets of the pK a data more consistently.

U2 - 10.1002/prot.23113

DO - 10.1002/prot.23113

M3 - Journal article

C2 - 22072518

SN - 0887-3585

VL - 79

SP - 3333

EP - 3345

JO - Proteins: Structure, Function, and Bioinformatics

JF - Proteins: Structure, Function, and Bioinformatics

IS - 12

ER -