XL-MS Spectrum Scoring for Uneven Cross-Linked Peptide Fragmentation
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Solution Overview
Problem
Cross-linking mass spectrometry (XL-MS) faces challenges with uneven fragmentation efficiency of cross-linked peptide pairs during collision-induced dissociation, leading to incomplete or absent fragmentation of peptides, which compromises sensitivity and the identifiability of MS2 spectra.
Innovation Solution
A system and method that includes a mass spectrometer for generating MS1 and MS2 spectra, a precursor mass refinement module for forming complete isotope clusters, an MS2 spectrum scoring module for matching spectra with scoring functions, and a protein score database to identify peptide candidates and determine protein-protein interactions, enhancing sensitivity and accuracy by leveraging protein-peptide associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If collision-induced dissociation (CID) is used for fragmentation of cross-linked peptides, then the fragmentation process can be performed, but uneven fragmentation efficiency occurs leading to incomplete or absent fragmentation of one of the cross-linked peptides
Solution Approach 1:
The patent introduces an intermediary scoring function that acts as a mediator between the experimental MS2 spectrum and the theoretical cross-linked peptide spectra. This scoring function evaluates the match quality and enables identification even when direct fragmentation fails, effectively mediating the identification process for unevenly fragmented cross-linked peptides.
Solution Approach 2:
The patent implements a feedback mechanism where the scoring function continuously evaluates the match between experimental and theoretical spectra, and this information feeds back into the identification process. The system uses the scoring results to refine peptide candidate selection and improve identification accuracy for cross-linked peptides with uneven fragmentation.
2Reliability
If existing strategies (ETD, stepped-HCD, MS3) are used to address imbalanced fragmentation, then some sensitivity improvement can be achieved, but the application development remains limited with sensitivity typically ranging from 20% to 50%
Solution Approach 1:
The patent replaces the reliance on complex hardware features (ETD, stepped-HCD, MS3) with a computational scoring function approach. Instead of using sophisticated mass spectrometry hardware configurations to achieve better fragmentation, the invention uses software-based scoring to evaluate and identify cross-linked peptides, thereby substituting mechanical/hardware complexity with computational methodology.
3Device complexity
If cleavable cross-linkers are used to generate reporter ions, then computational complexity is reduced, but the same uneven fragmentation problem persists as with non-cleavable cross-linkers
Solution Approach 1:
The patent changes the parameters used for evaluation from relying solely on fragmentation patterns to using a comprehensive scoring function that considers multiple parameters including mass accuracy, fragment ion matching, and spectral quality. This parameter change allows the system to effectively analyze both cleavable and non-cleavable cross-linker data types without being limited by uneven fragmentation efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system significantly improves the sensitivity and accuracy of identifying cleavable and non-cleavable cross-linking peptides, achieving higher sensitivity compared to existing techniques, with a three-fold improvement in sensitivity for non-cleavable and cleavable cross-linking data analysis.
Implementation Method 1
a mass spectrometer for producing precursor ions and generating MS1 spectrum
Implementation Method 2
processing at least one precursor ion to undergo a fragmentation treatment to generate an interested MS2 spectrum
Data Source
AI summary
This system presents a comprehensive approach for detecting protein-protein interactions and exploring protein structures. It encompasses various components, including a receptacle for receiving cross-linked precursor peptides, a mass spectrometer for generating MS1 and MS2 spectra, and modules for precursor mass refinement, MS2 spectrum scoring, protein score database construction, and feedback mechanism processing. Through the integration of these elements, the system facilitates the identification of peptide interactions and protein structures, leveraging a cross-linking dataset obtained from proteins cross-linked with cleavable or non-cleavable crosslinking reagents.