CIDer-p

CIDer-p is a sophisticated software tool that bridges a significant gap in the field of proteomics, particularly in the area of peptide detection through mass spectrometry. The tool emerges from recognizing the powerful capabilities of library searching in detecting peptides, which can be performed using either data-independent acquisition (DIA) or data-dependent acquisition (DDA) techniques. A notable focus within the field has been beam-type collision-induced dissociation (CID) fragmentation, specifically higher-energy collisional dissociation (HCD), which has garnered attention from large-scale spectrum library curators and those employing deep-learning prediction approaches. Despite this, resonance CID fragmentation continues to hold its ground as a widely used method in the proteomics community.

CIDer-p addresses the need to effectively model the differences between HCD and CID spectra. It achieves this by presenting a novel approach that acknowledges these differences and provides a practical solution for converting libraries between the two fragmentation methods. This conversion is critical, as it allows researchers to utilize existing spectral libraries more flexibly and efficiently, regardless of the fragmentation technique initially used to generate the spectra.

One of the achievements of CIDer-p is its ability to explain up to 43% of the variation between ions fragmented by HCD and CID across various collision energy settings, accomplished by using simple linear models combined with fundamental principles of peptide fragmentation. Such a level of explanation is significant, considering the complexity and variability inherent in mass spectrometry data.