pKD
From Protein Analysis and Design Group
The pKD program is designed to find mutations that will change the pKa value of a (set of) protein titratable group(s) in a given direction.
pKD is written by Jens Erik Nielsen with help from Barbara Tynan-Connolly.
You can use pKD via the pKD server or by running a local copy of pKD.
pKD is freely available to for non-profit research and non-profit teaching insitutions, whereas for-profit organisations should contact [Jens] to arrange for a commercial license.
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Getting started
To get started with pKD you will need to prepare a PDB file for use with pKD. The preparation procedure involves calculating pKa values for all the titratable groups in the PDB file and calculating mutant phimaps using either the WHAT IF pKa calculation suite or pdb2pka. The preparation procedure differs slightly for the two programs, and please note that the accuracy of the pdb2pka results is unknown since we're developing this package at the moment.
All functionalities of pKD are available both via the pKD server and via the the commandline tool. Throughout this documentation you will find separate sections for issuing commands to pKD using both interfaces.
Once you have prepared a PDB file then you should proceed with your type of calculation:
- Re-Design
- Mutation effects
Re-Designing a pKa value
Design_pKa.py -pdb 2lzt.pdb -pKas :0035:GLU=+2.0 -MC -max_mutations 6 -min_target_dist 10
This command will attempt to find a set of maximum 6 mutations that will elevate the pKa value of Glu 35 in 2lzt.pdb by 2.0 units. All mutations who have one or more atoms closer than 10 Angstrom to Glu 35 are excluded.
The -MC flag indicates that the Monte Carlo dpKa calculation algorithm should be used for calculating titration curves and pKa values.
Other flags:
- -use_titration_curves: Do not calculate pKa values, but always integrate titration curves to estimate the effects of mutations (experimental)
- -recalc_intpka: Include the effect of a mutation on the intrinsic pKa of the target residue (experimental)
- -recalc_intpka_dist: Ignore effects on intrinsic pKa for mutations further away than this distance
Calculating the effect of a mutation
pKD can be used to calculate the effect of a point mutation, or set of point mutations, on a set of target pKa values. You can use this functionality both on the webserver and on with the commandline tool:
The delta pKa functionality is invoked by specifying two flags {{{-calc_dpka and -mutations [list of mutations] }}} in addition to all the flags you normally would issue for a design calculation. So, if your design calculation statement normally would be
> Design_pKa.py -pdb 2lzt.pdb -pKas :0035:GLU=+2.0 -MC -max_mutations 6 -min_target_dist 10
then your dpKa calculation command would be
> Design_pKa.py -pdb 2lzt.pdb -pKas :0035:GLU=+2.0 -MC -max_mutations 6 -min_target_dist 10 -calc_dpka -mutations :0052:ALA,:0015:ALA
to calculate the effect of the mutations D52A+H15A on the pKa value of Glu 35.
Citing pKD
You can read about the pKD algoritm in
- pKD: Re-Designing protein pKa values
Tynan-Connolly BM, Nielsen JE
Nucleic Acids Research 2006 Jul 1;34(Web Server issue):W48-51.
- Redesigning protein pKa values
Tynan-Connolly BM, Nielsen JE
Protein Science 2007 Feb;16(2):239-49. Epub 2006 Dec 22.
If you use the pKD algorithm in your research then please remember to cite the articles above.
Applications of the pKD algorithm
- Computational design-based molecular engineering of the glycosyl hydrolase family 11 B. subtilis XynA endoxylanase improves its acid stability
Tim Belien, Iris J. Joye, Jan A. Delcour, and Christophe M. Courtin
Protein Engineering, Design and Selection 2009 22: 587-596; doi:10.1093/protein/gzp024.
