Mass Spectrometry Data Analysis for Unknown Substance Structure Estimation
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Solution Overview
Problem
Current mass spectrometry data analysis methods struggle to accurately estimate the structure of unknown substances that have undergone partial structural changes, especially when these changes are not pre-registered in databases, such as those occurring during metabolism, leading to difficulties in identifying substances like drug metabolites.
Innovation Solution
A method and system that utilize MSn spectrum data to estimate the structure of unknown substances by obtaining additional partial structure information, estimating post-elimination structural formulas, and determining product ion structures through coincidence of combined masses, allowing for the identification of unknown substances even without pre-registered structural change patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a database search method is used to identify unknown substances, then identification speed is improved, but identification accuracy deteriorates when structural change patterns are not pre-registered
Solution Approach 1:
The system performs preliminary action by pre-calculating and storing structural change patterns (addition, elimination, replacement of partial structures) in the database before actual analysis. When an unknown substance is analyzed, these pre-prepared patterns enable rapid matching and accurate identification even for metabolites or derivatives not previously in the database, resolving the contradiction between speed and accuracy.
2Reliability
If the database stores all possible compounds including metabolites and derivatives, then identification accuracy is improved, but database size and complexity increase
Solution Approach 1:
The system segments the identification process into two parts: storing only base compound structures in the database, and separately storing structural change patterns (addition, elimination, replacement rules). During analysis, the system combines base structures with change patterns to generate and identify metabolites/derivatives. This segmentation keeps the database compact while maintaining high identification accuracy for unknown substances.
Solution Approach 2:
The system introduces structural change patterns as an intermediary between the stored base compound database and the actual unknown substance identification. These patterns act as transformation rules that generate possible metabolite structures from parent compounds, enabling accurate identification without storing every possible derivative in the database.
3Loss of time
If MSn spectrum data is analyzed using conventional methods, then analysis time is reduced, but structural estimation accuracy deteriorates for substances with partial structural changes
Solution Approach 1:
The system implements feedback by iteratively comparing observed MSn spectrum data with spectra calculated from estimated structures, then refining the structural estimation based on the comparison results. This iterative feedback process maintains rapid analysis while significantly improving structural estimation accuracy for substances undergoing partial structural changes like metabolism.
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
Enables efficient and reliable estimation of structural formulas for unknown substances produced through partial structural changes, such as metabolism, even when the structural change patterns are not pre-registered, by separating the prediction of added and eliminated partial structures and utilizing multiple MSn spectra under different conditions.
Implementation Method 1
when an ion originating from a substance of interest contained in a sample is dissociated by collision induced dissociation (CID), a molecular bond is broken at a specific site depending on the bond energy or other factors, and various product ions and neutral losses are produced
Implementation Method 2
in a mass spectrometer equipped with an ion source by electron ionization (EI) or the like, a peak of a product ion or peaks of product ions fragmented from an ion originating from a sample component can be obtained in an MS1 spectrum by a method called in-source decay
Data Source
AI summary
In estimating a structural formula of an unknown substance produced through partial structural change of an original substance having a known structure caused by metabolism or the like, structural change is considered in two stages, the elimination of a partial structure and the addition of another partial structure. First, an additional partial structure is collected as known information in addition to an MSn spectrum of the unknown substance and a structural formula of the original substance. A structural formula at the time when a partial structure is eliminated from the original substance is estimated, and a structural formula of each of product ions is estimated. The structural formula of the unknown substance is determined by estimating a structure that can produce the candidates for structural formulas of the product ions by dissociation.