Deconvolving Product Ion Spectra for Accurate Peptide Identification
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Solution Overview
Problem
The identification of proteins or peptides from peptide fragments is adversely affected by mixed or convolved product ion spectra in Information Dependent Analysis (IDA) methods, where product ions from multiple precursor ions are present in a single spectrum, leading to unsuccessful database matches.
Innovation Solution
A system and method that separates product ions from convolved precursor ions by collecting and comparing product ion spectra at multiple times across a chromatographic peak, identifying patterns in product ion intensity changes, grouping product ions with similar patterns, and combining peaks to generate new spectra that include only ions from each group, thereby reducing spectral convolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If product ion spectra are collected at multiple times across a chromatographic peak in IDA method, then the quantity of spectral data increases, but spectral convolution increases leading to mixed product ions from multiple precursor ions
Solution Approach 1:
The patent segments the convolved spectral data by dividing product ions into different groups based on their intensity patterns across multiple spectra. This segmentation separates product ions from different precursor ions that would otherwise be mixed in a single convolved spectrum, allowing individual spectral reconstruction for each precursor ion group.
Solution Approach 2:
Instead of trying to prevent spectral convolution during data collection, the patent inverts the approach by collecting convolved spectra and then mathematically deconvolving them post-acquisition. The method uses intensity pattern analysis to reverse the convolution process and separate mixed signals, achieving the opposite effect of what traditionally occurs during IDA acquisition.
2Productivity
If conventional IDA methods compare product ion spectra directly from the mass spectrometer, then the process is simple and fast, but identification accuracy decreases due to mixed product ions
Solution Approach 1:
The patent performs preliminary analysis by collecting multiple product ion spectra at different times across the chromatographic peak before final identification. This preliminary data collection and pattern analysis enables subsequent deconvolution and spectral reconstruction, improving identification accuracy while maintaining computational efficiency through automated processing.
Solution Approach 2:
The patent introduces an intermediary processing step between raw spectral collection and database comparison. This intermediary deconvolution process uses intensity pattern matching and mathematical reconstruction to produce cleaned, non-convolved spectra that bridge the gap between raw data and accurate identification, enhancing both precision and reliability.
3Object-affected harmful factors
If evidence of multiple precursor ions is used to include fragmentation of precursor ions within 2-3 amu, then spectral convolution is addressed, but device complexity and method complexity increase
Solution Approach 1:
The patent enables the system to self-correct spectral convolution through automated pattern recognition and intensity-based grouping algorithms. The method uses the inherent information in the spectral data itself (intensity variations across multiple scans) to identify and separate convolved ions without requiring additional hardware or complex manual intervention, making the system self-sufficient in addressing convolution.
Solution Approach 2:
The patent changes the approach from modifying acquisition parameters (like precursor isolation width) to changing data processing parameters. By analyzing intensity patterns across multiple spectra and adjusting grouping thresholds, the method dynamically adapts to separate convolved ions without requiring hardware modifications or complex method setup, reducing overall system complexity.
Data Source
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AI summary
Two or more product ion spectra collected at two or more times across a peak profile of a compound separating over time are received. Intensities of product ions present in each spectrum of the two or more product ion spectra are compared across the two or more product ion spectra. At least two different patterns are identified that describe the change in product ion intensity across the two or more product ion spectra. The product ions present in each spectrum of the two or more product ion spectra are grouped into at least two different groups according to the at least two different patterns. The peaks of product ions from each group are combined, producing a combined product ion spectrum for each group of the at least two different groups that includes only peaks of product ions from each group.