Abstract Summary The protonation propensity of ionisable residues in proteins can change in response to changes in the local residue environment. The link between protein dynamics and pK a is particularly important in pH regulation of protein structure and function. Here, we introduce TrIPP (Trajectory Iterative pK a Predictor), a Python tool to track and analyse changes in the pK a of ionisable residues along Molecular Dynamics trajectories of proteins. We show how TrIPP can be used to identify residues with physiologically relevant variations in their predicted pK a values during the simulations, and link them to changes in the local and global environment. Availability and implementation TrIPP is available at https://github.com/fornililab/TrIPP Supplementary information Supplementary data are available at Bioinformatics online.
Matsingos et al. (Wed,) studied this question.