Mass Spectral Fragmentation Pattern Screening for Natural Product Identification
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Solution Overview
Problem
Current methods for natural product drug discovery are hindered by the complexity of natural product mixtures, requiring time-consuming isolation and structural analysis, and often rely on bioactivity-based navigation that pre-selects abundant compounds, missing 'known unknown' molecules with potential therapeutic value.
Innovation Solution
An informatic search program that merges chemoinformatic and bioinformatic methodologies to create chemical fragmentation or 'barcode' libraries, allowing for the identification of small molecule compounds through mass spectral analysis without explicit isolation, using calculated structures and fragmentation patterns to dereplicate knowns and detect novel compounds based on genomic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bioactivity based navigation is used to screen natural products, then abundant compounds are pre-selected, but 'known unknown' molecules with low concentration are missed
Solution Approach 1:
The patent replaces traditional bioactivity-based mechanical screening with mass spectrometry-based analytical detection. Instead of relying on biological assays that require sufficient compound concentration to observe activity, the system uses MS to directly detect and identify molecular structures regardless of abundance, substituting a biological detection mechanism with a physical-chemical one that is sensitive to trace quantities.
Solution Approach 2:
The patent introduces mass spectral fragmentation patterns as an intermediary identifier. Rather than directly observing bioactivity which requires abundant compounds, the system uses characteristic fragmentation patterns as a mediator to identify compounds present at very low concentrations, enabling detection of 'known unknown' molecules that would otherwise be missed.
2Measurement precision
If traditional isolation and structural analysis methods are used, then compound identification is achieved, but the process is time-consuming and low-throughput
Solution Approach 1:
The patent extracts only the essential identifying feature - the mass spectral fragmentation pattern - from the complete structural analysis process. Instead of performing time-consuming isolation and full structural characterization for each compound, the system extracts and compares fragmentation patterns, which contain sufficient information for identification while dramatically reducing analysis time and increasing throughput.
Solution Approach 2:
The patent creates computational copies of expected fragmentation patterns from known compound structures and compares these against experimental spectra. This copying approach allows rapid virtual screening of compound databases without physical isolation or detailed structural analysis, maintaining identification accuracy while enabling high-throughput processing of numerous samples.
3Loss of information
If comprehensive structural characterization is performed on all compounds, then complete chemical understanding is achieved, but costs and time requirements increase significantly
Solution Approach 1:
The patent applies partial action by performing only the essential measurement needed for identification - mass spectral fragmentation analysis - rather than comprehensive structural characterization including NMR, IR, and extensive isolation procedures. This partial approach captures the critical information required to distinguish compounds and identify their structures while avoiding unnecessary time-consuming steps that would not add value to the screening objective.
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
This approach enables rapid identification and characterization of small molecule compounds, including minor variants, with reduced costs and increased throughput, facilitating the detection of desired pharmacophores and expanding the exploration of natural product chemical space.
Implementation Method 1
mass spectral analysis
Implementation Method 2
mass spectrum of the mixture
Implementation Method 3
comparing a mass spectrum of the mixture with a library comprising calculated structures and corresponding calculated mass spectral fragmentation patterns
Data Source
AI summary
The present application is directed to methods and systems for identifying small molecule compounds in mixtures using a library comprising calculated structures and corresponding calculated mass spectral fragmentation patterns of known and/or hypothetical small molecule compounds that may be in the mixture and screening of a mass spectrum of the mixture using the library to identify matching fragmentation patterns. If a mass spectral fragmentation pattern present in the mass spectrum of the mixture matches a calculated fragmentation pattern of one of the known or hypothetical compounds this confirms the identity of a compound in the mixture as the known or hypothetical compound. The method represents a platform method that can be used for a multitude of purposes related to the screening and identification of compounds in mixtures. Therefore the methods and systems of the present application represent an approach that is uniquely capable of navigating chemical space and providing a understanding of desired families and pharmacophores.