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TrIPP: a Trajectory Iterative pKa Predictor

Christos MatsingosiD, Ka Fu Man, Arianna ForniliiD

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Abstract

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 pKa is particularly important in pH regulation of protein structure and function. Here, we introduce TrIPP (Trajectory Iterative pKa Predictor), a Python tool to monitor and analyse changes in the pKa of ionisable residues during Molecular Dynamics simulations 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. TrIPP is available at https://github.com/fornililab/TrIPP.

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