Department of Chemistry, University of Copenhagen, Copenhagen, Denmark.
Proteins. 2011 Dec;79(12):3333-45. doi: 10.1002/prot.23113. Epub 2011 Aug 30.
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.
在这项研究中,我们通过预测和比较一系列突变的枯草溶菌素变体中的可离子化基团的 pK(a) 值与实验值,验证和探究了蛋白质内部静电相互作用的描述。这组 pK(a) 值是迄今为止最具挑战性的 pK(a) 值数据,因为可离子化残基已被引入蛋白质内部的疏水区,因此与它们在溶剂中的参考值有很大的偏差。我们发现,使用 PROPKA2(Li 等人,《蛋白质》2005 年;61:704-721)进行真正的盲预测(如果我们重新分配紧密偶联的 Asp19/21 对,则为 1.6),其 rmsd 值接近 2,而使用新开发的 PROPKA3(Olsson 等人,《J. 化学理论计算》2011 年;7:525-537)进行后预测时,其 rmsd 值接近 1。我们还使用空模型的性能,即仅使用参考值进行的预测,来更好地描述 pK(a) 预测中的预期误差,并更一致地比较使用不同的 pK(a) 值子集进行的提交。