Improved p<I>K</I><SUB><FONT SIZE='-1'>a</FONT></SUB> prediction: Combining empirical and semimicroscopic methods

@article{citeulike:2937782, abstract = {Using three different methods we tried to compute 171 experimentally known pKa values of ionizable residues from 15 different proteins and compared the accuracies of computed pKa values in terms of the root mean square deviation (RMSD) from experiment. One method is based on a continuum electrostatic model of the protein including conformational flexibility (KBPLUS). The others are empirical approaches with PROPKA deploying physically motivated energy terms with adjustable parameters and PKAcal using an empirical function with no physical basis. PROPKA reproduced the pKa values with highest overall accuracy. Differentiating the data set into weakly and strongly shifted experimental pKa values, however, we found that PROPKA's accuracy is better if the pKa values are weakly shifted but on equal footing with that of KBPLUS for more strongly shifted values. On the other hand, PKAcal reproduces strongly shifted pKa values badly but weakly shifted values with the same accuracy as PROPKA. We tested different consensus approaches combining data from all three methods to find a general procedure for most accurate pKa predictions. In most of the cases we found that the consensus approach reproduced experimental data with better accuracy than any of the individual methods alone. {\copyright} 2008 Wiley Periodicals, Inc. J Comput Chem 2008}, address = {Freie Universit\"{a}t Berlin, Institute of Chemistry and Biochemistry, Fabeckstr. 36a, Berlin 14195, Germany}, author = {Kieseritzky, Gernot and Knapp, E. W. }, citeulike-article-id = {2937782}, doi = {10.1002/jcc.20999}, journal = {Journal of Computational Chemistry}, keywords = {pka}, number = {9999}, pages = {NA+}, posted-at = {2008-07-15 02:47:26}, priority = {2}, title = {Improved p<I>K</I><SUB><FONT SIZE='-1'>a</FONT></SUB> prediction: Combining empirical and semimicroscopic methods}, url = {http://dx.doi.org/10.1002/jcc.20999}, volume = {9999}, year = {2008} }

TY - JOUR ID - citeulike:2937782 L3 - citeulike-article-id:2937782 TI - Improved p<I>K</I><SUB><FONT SIZE='-1'>a</FONT></SUB> prediction: Combining empirical and semimicroscopic methods JF - Journal of Computational Chemistry VL - 9999 IS - 9999 SP - NA AD - Freie Universität Berlin, Institute of Chemistry and Biochemistry, Fabeckstr. 36a, Berlin 14195, Germany N2 - Using three different methods we tried to compute 171 experimentally known pKa values of ionizable residues from 15 different proteins and compared the accuracies of computed pKa values in terms of the root mean square deviation (RMSD) from experiment. One method is based on a continuum electrostatic model of the protein including conformational flexibility (KBPLUS). The others are empirical approaches with PROPKA deploying physically motivated energy terms with adjustable parameters and PKAcal using an empirical function with no physical basis. PROPKA reproduced the pKa values with highest overall accuracy. Differentiating the data set into weakly and strongly shifted experimental pKa values, however, we found that PROPKA's accuracy is better if the pKa values are weakly shifted but on equal footing with that of KBPLUS for more strongly shifted values. On the other hand, PKAcal reproduces strongly shifted pKa values badly but weakly shifted values with the same accuracy as PROPKA. We tested different consensus approaches combining data from all three methods to find a general procedure for most accurate pKa predictions. In most of the cases we found that the consensus approach reproduced experimental data with better accuracy than any of the individual methods alone. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008 KW - pka AU - Kieseritzky, Gernot AU - Knapp, EW PY - 2008/// UR - http://dx.doi.org/10.1002/jcc.20999 ER -