title: Blind, one-eyed, or eagle-eyed? pKa calculations during blind predictions with staphylococcal nuclease.
abstract: In the current contribution, the performance of Poisson-Boltzmann-based pK(a) calculations of SNase mutants as part of a blind prediction exercise facilitated by the pK(a) cooperative ("pK(a) _coop") is described. A one parameter setting ("quick&dirty" approach) is used to provide an industry perspective where strong time constraints are frequently encountered. On the one hand, results are analyzed in terms of root mean square deviation performance. Furthermore, the pK(a) calculations are assessed for their ability to properly assign protonation state. For this purpose, a new measure called BIPS (binary protonation state at physiological pH) is introduced. Significant differences were found with both comparison measures based on the class of residues examined. In addition, the performance of PROPKA3 as well as the NULL model is examined on the same data set. Finally, pK(a) calculations on SNase mutants with available structural information have been performed and provide support for our calculation methods. The performance on this subset is better than on the pK(a) cooperative mutation data. In the pK(a) _coop data, no structural information on the generated mutants is available. This suggests the occurrence of a substantial structural rearrangement on the insertion of additional charged groups into SNase, which leads to improved prediction quality.
authors.affiliation: Merck KGaA, NCE Technologies, Computational Chemistry, Darmstadt, Germany. paul.czodrowski@merckgroup.com
authors.forename: Paul
authors.initials: P
authors.lastname: Czodrowski
mesh_terms: D001426:Bacterial Proteins / Q000737:chemistry / Q000378:metabolism; D018360:Crystallography, X-Ray; D006863:Hydrogen-Ion Concentration; D008836:Micrococcal Nuclease / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D008958:Models, Molecular; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D055672:Static Electricity; D013223:Statistics as Topic / Q000379:methods
chemical_list: D001426:Bacterial Proteins; D008836:Micrococcal Nuclease