# TrIPP: a trajectory iterative pKa predictor

## TL;DR

TrIPP is a new tool that tracks how the protonation tendencies of protein residues change during simulations, helping to understand protein behavior at different pH levels.

## Contribution

TrIPP introduces a novel method to analyze pKa changes in ionizable residues along molecular dynamics trajectories.

## Key findings

- TrIPP identifies residues with physiologically relevant pKa variations during simulations.
- The tool links pKa changes to local and global environmental shifts in proteins.
- TrIPP is available as an open-source Python tool for molecular dynamics analysis.

## Abstract

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.

TrIPP is available at https://github.com/fornililab/TrIPP.