QCMS² as a new method for providing insight into peptide fragmentation: The influence of the side‐chain and inter–side‐chain interactions

Abstract

The identification of peptides and proteins from tandem mass spectra is a difficult task and multiple tools have been developed to aid this identification. We present a new method, called Quantum Chemical Mass Spectrometry for Materials Science (QCMS 2 ), which is based on quantum chemical calculations of bond orders, reaction and transition-state energies at the DFT/B3LYP/6-311+G* level of theory. The method was used to describe the fragmentation pathways of five X-His-Ser tripeptides with X = Asn, Asp, Glu, Ser and Trp, thereby focusing on the influence of the side chain and inter-side-chain interaction on the fragmentation. The main features in the mass spectra of the five tripeptides were correctly reproduced and a number of fragments were assigned to fragmentations involving the side chain and the influence of inter-side-chain interactions. Product ion spectra were recorded to evaluate the capabilities and limitations of QCMS 2 and a number of conventional tools.

Quantum chemical mass spectrometry: Ab initio study of b2‐ion formation mechanisms for the singly protonated Gln‐His‐Ser tripeptide

“…As the energetics of the three pathways discussed in section 3.2.2 do not lead to an unambiguous conclusion on the nature of the b 2 ‐ion ( m / z 266), further fragmentations of the lactam (Figure S2e, supporting information), oxazolone (Figure S2d, supporting information), and diketopiperazine b 2 ‐ions (Figure S2b, supporting information) were predicted using the QCMS 2 method 23,24 . This recently developed computational tool for the prediction of mass spectra and the identification of fragmentation routes selects fragmentation pathways based on relative values of bond orders, reaction energies for bond cleavages, and transition‐state energies for rearrangements: the software evaluates the different fragmentations possible for each of the fragments in the “fragmentation tree” in terms of their energetics and follows the lowest‐energy pathways to the final fragments.…”

“…This recently developed computational tool for the prediction of mass spectra and the identification of fragmentation routes selects fragmentation pathways based on relative values of bond orders, reaction energies for bond cleavages, and transition‐state energies for rearrangements: the software evaluates the different fragmentations possible for each of the fragments in the “fragmentation tree” in terms of their energetics and follows the lowest‐energy pathways to the final fragments. It provides no data on peak intensities 23,24 …”

“…Due to the promising results obtained using QCMS 2 to predict the electron ionization (EI) fragmentation routes of a number of organic compounds, 23 it has been used to predict the fragmentation patterns of X‐His‐Y tripeptides under electrospray ionization (ESI) and low‐energy collision‐induced dissociation (CID) conditions, focusing on the fragmentation of the side chain and the influence of inter‐side‐chain (ISC) interactions on the fragmentation, as a number of the fragments in the spectra not predicted by the currently available techniques are known to be due to fragmentations involving the side chains. In one case, 24 the product ion spectra of five X‐His‐Ser tripeptides with X = Asn, Asp, Glu, Ser, Trp (amino acids with the ability to form strong ISC interactions) were recorded and assigned based on the results of the QCMS 2 calculations. Whereas the current tools are all limited by what is already known about the fragmentation of peptides, QCMS 2 produces full fragmentation pathways “from scratch” and provides deeper insight into fragmentation mechanisms.…”

Quantum Chemistry Calculations for Metabolomics

“…Similar to CID fragmentation predictions, classical reaction mechanism theory as well as QM/MM calculations including AIMD can be used to predict ions and their abundances. The QCMS 2 approach uses a pipeline of conformational sampling, protonation, fragmentation rules, and exploration of transition states along the PES. , Formerly developed for EI-MS, it has been modified to work for CID predictions …”

Evaluating the Accuracy of the QCEIMS Approach for Computational Prediction of Electron Ionization Mass Spectra of Purines and Pyrimidines

“…While rule-based [17][18][19] or machine-learning [20,21] approaches have been tested extensively for computational generation of MS libraries, ab initio quantum chemistry approaches have been made available more recently [22][23][24][25]. The Grimme group developed the Quantum Chemical Electron Impact Mass Spectrum (QCEIMS) program that utilizes Born-Oppenheimer molecular dynamics (BOMD) coupled with Boltzmann statistics and isotopic distribution [23,26].…”