Benchmarking pKa prediction

Matthew N Davies,Darren R Flower,Christopher P Toseland,David S Moss

doi:10.1186/1471-2091-7-18

Matthew N Davies, Darren R Flower + Show 2 more

Open Access

https://doi.org/10.1186/1471-2091-7-18

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Abstract

BackgroundpKa 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.ResultsHere 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.ConclusionOverall, 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.

Highlights

PKa values are a measure of the protonation of ionizable groups in proteins
Ionizable groups may be divided into acidic, which
PROPKA is the most accurate method for all residues except Glu and His, where it is narrowly surpassed by UHBD and MCCE, respectively

Summary

Introduction

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. If the pKa of a particular group is known one can determine its protonation state at a given pH, helping to determine several important properties including protein solubility, protein folding and catalytic activity. The pKa value is -log10(Ka) where Ka, is the ionization constant, a measure of a titratable group's ability to donate a proton: Ka = [H+ ][A−] [HA] (1). Ionizable groups may be divided into acidic, which (page number not for citation purposes)

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