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Dataset Information

Benchmarking pK(a) prediction.


ABSTRACT:

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 tende

SUBMITTER: Davies MN 

PROVIDER: S-EPMC1513386 | biostudies-literature | 2006 Jun

REPOSITORIES: biostudies-literature