im2deep 1.2.0

Framework for prediction of collisional cross-section of peptides.

IM2Deep

Collisional cross-section prediction for (modified) peptides.

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Introduction

IM2Deep is a CCS predictor for (modified) peptides. It is able to accurately predict CCS for modified peptides, even if the modification wasn't observed during training.

Installation

Install with pip:

pip install im2deep

If you want to use the multi-output model for CCS prediction of multiconformational peptide ions, use the following installation command:

pip install 'im2deep[er]'

Usage

Basic CLI usage:

im2deep <path/to/peptide_file.csv>

If you want to calibrate your predictions (HIGHLY recommended), please provide a calibration file:

im2deep <path/to/peptide_file.csv> --calibration-file <path/to/peptide_file_with_CCS.csv>

To use the multi-output prediction model on top of the original model, provide the -e flag (make sure you have the optional dependencies installed!):

im2deep <path/to/peptide_file.csv> --calibration-file <path/to/peptide_file_with_CCS.csv> -e

For an overview of all CLI arguments, run im2deep --help.

Input files

Both peptide and calibration files are expected to be comma-separated values (CSV) with the following columns:

• seq: unmodified peptide sequence
• modifications: every modifications should be listed as location|name, separated by a pipe character (|) between the location, the name, and other modifications. location is an integer counted starting at 1 for the first AA. 0 is reserved for N-terminal modifications, -1 for C-terminal modifications. name has to correspond to a Unimod (PSI-MS) name.
• charge: peptide precursor charge
• CCS: collisional cross-section (only for calibration file)

For example:

seq,modifications,charge,CCS
VVDDFADITTPLK,,2,422.9984309464991
GVEVLSLTPSFMDIPEK,12|Oxidation,2,464.6568644356109
SYSGREFDDLSPTEQK,,2,468.9863221739147
SYSQSILLDLTDNR,,2,460.9340710819608
DEELIHLDGK,,2,383.8693416055445
IPQEKCILQTDVK,5|Butyryl|6|Carbamidomethyl,3,516.2079366048176

Citing

If you use IM2Deep within the context of (TI)MS²Rescore, please cite the following:

TIMS²Rescore: A DDA-PASEF optimized data-driven rescoring pipeline based on MS²Rescore. Arthur Declercq*, Robbe Devreese*, Jonas Scheid, Caroline Jachmann, Tim Van Den Bossche, Annica Preikschat, David Gomez-Zepeda, Jeewan Babu Rijal, Aurélie Hirschler, Jonathan R Krieger, Tharan Srikumar, George Rosenberger, Dennis Trede, Christine Carapito, Stefan Tenzer, Juliane S Walz, Sven Degroeve, Robbin Bouwmeester, Lennart Martens, and Ralf Gabriels. Journal of Proteome Research (2025) doi:10.1021/acs.jproteome.4c00609

In other cases, please cite the following:

Collisional cross-section prediction for multiconformational peptide ions with IM2Deep. Robbe Devreese, Alireza Nameni, Arthur Declercq, Emmy Terryn, Ralf Gabriels, Francis Impens, Kris Gevaert, Lennart Martens, Robbin Bouwmeester. Anal. Chem. (2025) doi:10.1021/acs.analchem.5c01142