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Features

Why should you use PypKa?

Electrostatic-driven pK_a estimations

Inspect the source code and hack it as you see fit.

Include background charges in your calculations.

Exploit the linear scaling of pypka by deploying it in your computational cluster.

Integrate it with your own software or scripts.

All parameters used in the calculations are tweackable in the input data.

Are you using PypKa in your research? Please cite:
Reis et al. J Chem Inf Model. 2020
DOI: 10.1021/acs.jcim.0c00718

Statistics

Easily calculate pK_a values in your protein of interest with our server.

Force Field Choices

40s

Calculation on a 50 residue Protein

0.3

Average Error in a 500 residue dataset

Pypka is open source! It's developed and maintained on GitHub so that you can make it your own.