A Data-Mining Scheme for Identifying Peptide Structural Motifs Responsible for Different MS/MS Fragmentation Intensity Patterns

Abstract

Although tandem mass spectrometry (MS/MS) has become an integral part of proteomics, intensity patterns in MS/MS spectra are rarely weighted heavily in most widely used algorithms because they are not yet fully understood. Here a knowledge mining approach is demonstrated to discover fragmentation intensity patterns and elucidate the chemical factors behind such patterns. Fragmentation intensity information from 28 330 ion trap peptide MS/MS spectra of different charge states and sequences went through unsupervised clustering using a penalized K-means algorithm. Without any prior chemistry assumptions, four clusters with distinctive fragmentation patterns were obtained. A decision tree was generated to investigate peptide sequence motif and charge state status that caused these fragmentation patterns. This data-mining scheme is generally applicable for any large data sets. It bypasses the common prior knowledge constraints and reports on the overall peptide fragmentation behavior. It improves the understanding of gas-phase peptide dissociation and provides a foundation for new or improved protein identification algorithms.

Defining Gas-Phase Fragmentation Propensities of Intact Proteins During Native Top-Down Mass Spectrometry

“…This model describes fragmentation of peptides in the gas phase with considerations for residue composition [23, 26–28], gas-phase basicity [23, 28–30], secondary structure [30], relative location of the basic residue [31, 32], and the theoretical mobility of the proton (e.g., sequestered vs. mobile) [23, 32]. For instance, following ionization, a peptide that has a greater number of charges than the number of residues with high gas-phase basicity ( e.g., arginine [33]) will have protons readily mobilize to amide bonds to induce backbone fragmentation [23].…”

“…In contrast, if the peptide has fewer charges than the number of basic residues, the proton(s) is sequestered to the basic residue(s) and the activation energy needed to mobilize the proton and induce backbone fragmentation is increased substantially [23, 28–30, 34]. The conventional fragmentation pathways that are best described by the mobile proton model are grouped into four major clusters, including fragmentation occurring (i) N-terminal to proline (X|P), (ii) C-terminal to isoleucine, leucine, or valine (I/L/V|X), (iii) C-terminal to aspartic acid or glutamic acid (D/E|X), and (iv) “b&y” fragmentation [31, 32]. This “b&y” fragmentation pathway generally includes ions with arginine near the N-terminus ( e.g., in the case of missed tryptic cleavages) or internal fragment ions (ions that form by re-fragmentation of a b - or y -type ion) [31, 32, 35].…”

“…The conventional fragmentation pathways that are best described by the mobile proton model are grouped into four major clusters, including fragmentation occurring (i) N-terminal to proline (X|P), (ii) C-terminal to isoleucine, leucine, or valine (I/L/V|X), (iii) C-terminal to aspartic acid or glutamic acid (D/E|X), and (iv) “b&y” fragmentation [31, 32]. This “b&y” fragmentation pathway generally includes ions with arginine near the N-terminus ( e.g., in the case of missed tryptic cleavages) or internal fragment ions (ions that form by re-fragmentation of a b - or y -type ion) [31, 32, 35]. Fragmentation through these four major channels has also been investigated for intact proteins analyzed under denaturing conditions [35].…”

Mobile protons versus mobile radicals: Gas-phase unimolecular chemistry of radical cations of cysteine-containing peptides

“…While there is still some debate on the structures of b-ions [7], the lowenergy fragmentation reactions of protonated peptides that result in the formation of both sequence and non-sequence ions are fairly well understood and have been the subject of several reviews [5][6][7][8][9][10][11]. This is due to the world-wide research efforts of many groups who have either conducted experimental and theoretical studies on small model peptides [5][6][7][8][9][10] or used statistical methods to interrogate large, curated libraries of MS/MS spectra of "real world" peptides, typically formed via tryptic digestion of proteins [12][13][14][15][16][17][18][19][20][21][22]. While more refined fragmentation models such as Paizs and Suhai's "pathways in competition (PIC)" have been developed [10], the "mobile proton" has remained center stage.…”

Gas-phase conformations of small polyprolines and their fragment ions by IRMPD spectroscopy

“…Complex and sophisticated sequencing algorithms have been developed relating fragmentation patterns to parent ion sequence. However, much of the backbone fragmentation following non-standard pathways remains poorly modeled and the data resulting from these pathways is often not completely utilized [1], possibly resulting in reduced sequence information and less reliable identification. In order to more completely exploit the information contained in protein/peptide MS n experiments, incorporation of a more comprehensive description of peptide fragmentation mechanisms, including not only models of non-standard fragmentation pathways, but also relative fragment-ion intensity information, is required [2].…”