Benchmarking pKa prediction
Davies, M.N. and Toseland, C.P. and Moss, David S. and Flower, D.R. (2006) Benchmarking pKa prediction. BMC Biochemistry 7 (articl), ISSN 1471-2091.
Background: pKa values are a measure of the protonation of ionizable groups in proteins. Ionizable groups are involved in intra-protein, protein-solvent and protein-ligand interactions as well as solubility, protein folding and catalytic activity. The pKa shift of a group from its intrinsic value is determined by the perturbation of the residue by the environment and can be calculated from three-dimensional structural data. Results: Here we use a large dataset of experimentally-determined pKas to analyse the performance of different prediction techniques. Our work provides a benchmark of available software implementations: MCCE, MEAD, PROPKA and UHBD. Combinatorial and regression analysis is also used in an attempt to find a consensus approach towards pKa prediction. The tendency of individual programs to over- or underpredict the pKa value is related to the underlying methodology of the individual programs. Conclusion: Overall, PROPKA is more accurate than the other three programs. Key to developing accurate predictive software will be a complete sampling of conformations accessible to protein structures.
|Additional Information:||© 2006 Davies et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0) ,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The electronic version of this article is the complete one and can be found online at http://www.biomedcentral.com/1471-2091/7/18|
|School:||Birkbeck Schools and Departments > School of Science > Biological Sciences|
|Research Centre:||Structural Molecular Biology, Institute of (ISMB)|
|Depositing User:||Sandra Plummer|
|Date Deposited:||24 Jul 2007|
|Last Modified:||06 Dec 2016 10:43|
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