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Published on: February 13, 2011
TrIPP: a trajectory iterative pKa predictor
Christos Matsingos1,2, Ka Fu Man1, Arianna Fornili1
1Department of Chemistry, School of Physical and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom.
Summary:
The protonation propensity of ionizable residues in proteins can change in response to changes in the local residue environment. The link between protein dynamics and pKa is particularly important in pH regulation of protein structure and function. Here, we introduce TrIPP (Trajectory Iterative pKa Predictor), a Python tool to track and analyze changes in the pKa of ionizable residues along Molecular Dynamics trajectories of proteins. We show how TrIPP can be used to identify residues with physiologically relevant variations in their predicted pKa 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.
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