As seen in the installation page, PypKa is easilly installed from the command line.
The basic example provided can be effortlessly adjusted to your system. Although many parameters can be modified by an advanced user, simple users can confidently use the default values.
Every interface has its pros and cons. With PypKa you can choose to run you calculations via a python API or from the command-line. In the future we will present a webserver interface as well.
As a Poisson-Boltzmann-based pKa predictor, PypKa provides an interesting trade-off between speed and accuracy. You can also manually set some input parameters such as :pyconvergence
, :pygsize
or :pysites
, to adjust the balance between accuracy and speed as you please. Further speed gains can be achieved by taking advantage of the highly scalable multiprocessing capabilities (:pyncpus
).
PypKa supports both the Protein Data Bank and GROMACS input format and the most popular atomistic force-fields (AMBER, CHARMM & GROMOS) as well as experimentally determined structures. These structures are preprocessed using a modified version of PDB2PQR according to the defined :pyffinput
.
It is possible to run calculations on membrane proteins, and in the future, on lipids. Currently only some lipids are supported (DMPC, POPC, POPE and cholesterol) but more will be added. To use this feature the user is required to name the lipids in their structures according to the PypKa definition.
Example POPC file
Example POPE file
Example DMPC file