Isopeptor: a tool for detecting intramolecular isopeptide bonds in protein structures
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Motivation
Intramolecular isopeptide bonds contribute to the structural stability of proteins, and have primarily been identified in domains of bacterial fibrillar adhesins and pili. At present, there is no systematic method available to detect them in newly determined molecular structures. This can result in mis-annotations and incorrect modelling.
Results
Here, we present Isopeptor, a computational tool designed to predict the presence of intramolecular isopeptide bonds in experimentally determined structures. Isopeptor utilizes structure-guided template matching via the Jess software, combined with a logistic regression classifier that incorporates Root Mean Square Deviation (RMSD) and relative solvent accessible area (rASA) as key features. The tool demonstrates a recall of 1.0 and a precision of 0.95 when tested on a Protein Data Bank (PDB) subset of domains known to contain intramolecular isopeptide bonds that have been deposited with incorrectly modelled geometries. Isopeptor’s python-based implementation supports integration into bioinformatics workflows, enabling early detection and prediction of isopeptide bonds during protein structure modelling.
Availability and implementation
Isopeptor is implemented in python and can be accessed via the command line, through a python API or via a Google Colaboratory implementation ( https://colab.research.google.com/github/FranceCosta/Isopeptor_development/blob/main/notebooks/Isopeptide_finder.ipynb ). Source code is hosted on GitHub ( https://github.com/FranceCosta/isopeptor ) and can be installed via the python package installation manager PIP.
