Protein-sol pKa: prediction of electrostatic frustration, with application to coronaviruses.

Max Hebditch,Jim Warwicker,Arne Elofsson

doi:10.1093/bioinformatics/btaa646

Max Hebditch, Jim Warwicker + Show 1 more

Open Access

https://doi.org/10.1093/bioinformatics/btaa646

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Abstract

MotivationEvolution couples differences in ambient pH to biological function through protonatable groups, in particular, those that switch from buried to exposed and alter protonation state in doing so. We present a tool focusing on structure-based discovery and display of these groups.ResultsSince prediction of buried group pKas is computationally intensive, solvent accessibility of ionizable groups is displayed, from which the user can iteratively select pKa calculation centers. Results are color-coded, with emphasis on buried groups. Utility is demonstrated with benchmarking against known pH sensing sites in influenza virus hemagglutinin and in variants of murine hepatitis virus, a coronavirus. A pair of histidine residues, which are conserved in coronavirus spike proteins, are predicted to be electrostatically frustrated at acidic pH in both pre- and post-fusion conformations. We suggest that an intermediate expanded conformation at endosomal pH could relax the frustration, allowing histidine protonation and facilitating conformational conversion of coronavirus spike protein.Availability and implementationThis tool is available at http://www.protein-sol.manchester.ac.uk/pka/.

Highlights

Since pKas underlie pH-dependent phenomena in biology, their prediction has received significant attention, largely through continuum electrostatics methods (Alexov et al, 2011)
Conformational change often depends on the electrostatic frustration that develops when a buried group cannot ionize at a pH where it would in a more solvent accessible conformation (Narayan and Naganathan, 2018)
The server is demonstrated with coronaviruses, some of which use the endocytotic pathway for membrane fusion, whereas others fuse at the plasma membrane

Summary

Introduction

Since pKas underlie pH-dependent phenomena in biology, their prediction has received significant attention, largely through continuum electrostatics methods (Alexov et al, 2011). Conformational change often depends on the electrostatic frustration (destabilization) that develops when a buried group cannot ionize at a pH where it would in a more solvent accessible conformation (Narayan and Naganathan, 2018). We reasoned that a web tool focusing on buried ionizable groups would be useful for studying pH-dependent conformational change, and have adapted our existing mixed finite difference Poisson-Boltzmann (FDPB) and DH model.

Results

Conclusion