Mass Spectral Matching for Unknown Molecule Source Identification
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Solution Overview
Problem
Conventional mass spectrometry systems require pre-identified molecules in spectral libraries to identify unknown molecules, limiting the ability to determine the source of molecules based on their mass spectra.
Innovation Solution
A method using hardware processors to search for similarity scores between query mass spectra and reference mass spectra without relying on molecular identities, generating context information from metadata to identify the source of unknown molecules, and clustering reference spectra to improve search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional spectral library matching is used to identify unknown molecules, then molecular identity can be determined for known compounds, but the system cannot identify sources of unknown molecules that are not in the library
Solution Approach 1:
The patent introduces spectrum embeddings as an intermediary representation that bridges unknown molecules and their potential sources. Instead of directly matching unknown molecule spectra to source identities, the system embeds spectra into a vector space where similarity calculations can infer source context without requiring prior molecular identification
Solution Approach 2:
The system transforms spectral data from traditional peak-intensity representation into embedding vector representations, adding a new dimensional space for comparison. This dimensional transformation enables the system to capture source-related information that is not accessible through conventional spectral matching approaches
2Measurement precision
If spectral libraries contain only pre-identified molecules, then identification accuracy is maintained, but the scope of searchable information is limited
Solution Approach 1:
The patent changes the parameter of spectral representation from traditional peak-based formats to embedding vectors. This parameter change allows the system to process and compare spectra without requiring molecular identification, dramatically expanding the searchable spectrum library while maintaining meaningful comparison capabilities through the embedding space
3Reliability
If the system searches all reference spectra in the repository, then comprehensive source identification is achieved, but search time increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-computing embedding vectors for all reference spectra and organizing them in an efficient search structure before actual queries are made. This preliminary embedding generation enables rapid similarity searches without requiring full spectral comparisons during query processing
Solution Approach 2:
The patent replaces the mechanical spectral comparison process (direct peak-by-peak matching) with an embedding-based similarity calculation. This substitution dramatically reduces computational complexity, allowing comprehensive searches of large spectral repositories to be completed in fraction of the original time
Data Source
AI summary
Source identification for unknown molecules using mass spectral matching. In an embodiment, a representation of a query mass spectrum is received in a spectrum query. A repository is searched for the query mass spectrum by, for each of a plurality of reference mass spectra, generating a similarity score between the representation of the query mass spectrum and the representation of the reference mass spectrum, when the similarity score exceeds a predetermined threshold value, without utilizing a molecular identity of a molecule represented by the reference mass spectrum, retrieving metadata associated with the reference mass spectrum, and derive context information from the retrieved metadata, and adding the context information to consensus metadata associated with the query mass spectrum, wherein the context information indicates a source of the reference mass spectrum. The consensus metadata is then returned in response to the spectrum query.