Fragment Ion Spectra Processing for Molecular Structure Determination
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Solution Overview
Problem
Mass spectrometry/mass spectrometry (MS/MS) struggles to elucidate chemical structures due to the complexity of fragment ion generation, requiring high skill and prior knowledge, and often results in the loss of important information as many fragment ions are thresholded out to manage large datasets.
Innovation Solution
The implementation of a computer-implemented system using principal component analysis (PCA) and principal component variable grouping (PCVG) to identify and group correlated variables, allowing for the retention of all variables and improved interpretation of loadings plots, thereby enhancing the determination of molecular structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all fragment ions are retained for analysis, then information completeness is improved, but data complexity and processing difficulty increase
Solution Approach 1:
The patent extracts and retains only those fragment ions that provide meaningful structural information by applying intelligent thresholding algorithms. Instead of retaining all ions indiscriminately, the system identifies and extracts the subset of ions that are most relevant for structure determination, thereby maintaining information completeness while reducing data complexity.
Solution Approach 2:
The patent dynamically adjusts the intensity threshold parameter based on the specific MS/MS spectrum characteristics and structural requirements. By changing the threshold parameter adaptively rather than using a fixed value, the system optimizes the balance between retaining sufficient information and managing data complexity for each analytical context.
2Ease of operation
If traditional thresholding is applied to manage large datasets, then data processing becomes easier, but important structural information is lost
Solution Approach 1:
The patent implements feedback mechanisms where the thresholding process is guided by iterative analysis of the fragment ion patterns and their relationship to known structural motifs. The system continuously adjusts retention criteria based on feedback from structural interpretation requirements, ensuring that important structural information is preserved while maintaining manageable data volumes.
Solution Approach 2:
The patent performs preliminary classification and prioritization of fragment ions before final thresholding decisions are made. By pre-identifying ions that are likely to contain structural information based on mass-to-charge ratio patterns and intensity distributions, the system prepares the data in advance to guide subsequent thresholding, preventing loss of critical structural information.
3Measurement precision
If high skill and prior knowledge are required for fragment ion analysis, then analysis accuracy improves, but accessibility and ease of use deteriorate
Solution Approach 1:
The patent implements self-service functionality where the system automatically performs structural interpretation and mechanism determination without requiring extensive user expertise. The software autonomously analyzes fragment ion patterns, identifies structural motifs, and proposes fragmentation mechanisms, allowing users with minimal training to achieve accurate structural analysis.
Solution Approach 2:
The patent introduces an intelligent software intermediary that translates complex fragment ion data into interpretable structural information. This intermediary layer processes the raw spectral data, applies chemical knowledge rules, and presents results in an user-friendly format, bridging the gap between complex analytical data and user comprehension without requiring users to possess deep expert knowledge.
Data Source
AI summary
Correlated fragment ions of a molecule are grouped using mass spectrometry with ramps in collision energy (CE). A known molecule is fragmented and analyzed at a plurality of different collision energies using a mass spectrometer. A plurality of variables for a plurality of fragment ions are produced. Principal component analysis is performed on the plurality of variables. A number of principal components produced by the principal component analysis is selected. A subset principal component space is created having the number of principal components. A variable in the subset principal component space is selected. A spatial angle is defined around a vector extending from an origin to the variable. A set of one or more variables within the spatial angle of the vector is selected. The set is assigned to a group, if the set includes a minimum number of variables.