pKa values have a significant impact on the structure and function of biomolecules, influencing many physicochemical and ADME properties. Thus, the calculation of pKa values is widely used in different scientific communities, including bioinformatics, structural biology and medicinal chemistry. We have implemented a flexible tool to predict Poisson-Boltzmann-based pKa values of biomolecules. This is a free and open source project that provides a simple, reusable and extensible python API for pKa calculations with a valuable trade-off between fast and accurate predictions. With PypKa one can enable pKa calculations, including optional proton tautomerism, within existing protocols by adding two extra lines of code. PypKa supports CPU parallel computing on anisotropic (membrane) and isotropic (protein) systems, and allows the user to find a balance between accuracy and speed. Due to its open source nature, there is an opportunity to continually evolve a user-friendly, reliable and flexible API that has applicability across a wide range of fields.
We acknowledge financial support from FCT through grant SFRH/BPD/110491/2015 and projects PTDC/QEQCOM/5904/2014, UID/MULTI/00612/2013 and UID/MULTI/04046/2013.