Poster Presentation
Accelerated Analysis of Structurally Related Components in Complex Samples
Baljit Bains, Marketing Communications Specialist, ACD/Labs
Anne Marie Smith, Alexander Lishchuk, Alexander Sakharov, Baljit Bains
Introduction
Continual improvements in MS instruments’ sensitivity and resolution produce highly complex and detailed data. This data requires expert analysis, which can take a significant amount of time. Identification of components can be challenging for complex samples, whether for stability studies, forced degradation, impurity studies, or other areas. These challenges include component co-elution or lack of resolution in the chromatographic peaks. Current standard practice involves a library search to obtain a confident identification of a component. Here, we show a solution that can be applied to various analysis types to accelerate the identification of related sample components without the use of a library.
Methods
The system automatically selects the data files and a list of predefined chemical structures. Background subtraction is optionally performed to leave substances unique to the sample. If a structure list was provided, structures are associated with found components.
The principle structure is fragmented using in-silico prediction. The top fragments along with common modifications of these fragments (i.e., +/-CH2) are searched across MS2 component spectra. Numerical Markush structures are generated for components that contain common ions of the principle to help elucidate the structure more quickly.
Preliminary Data
The new algorithm uses common ions to identify related components. This helps to identify components that were not part of the provided chemical structure list and gives additional confidence to those that were part of the structure list.
Identification of top in-silico generated principle fragments and their modifications across the MS2 spectra of other components gives the user confidence that the component was related to the principle structure. These components are assigned a numerical Markush, aiding the user in elucidating the component structure. The use of common ions provides the user with insight into the partial component structure and helps to find additional possible components that could otherwise be missed on manual review.
The results are tabulated to summarize all found components, categorizing them as true unknown components (no structure), Markush components (those with a common ion), or confirmed structures (from the structure list). The quality of the structural assignment is based on the presence of common ions, confirmed structure from the structure list, the presence of a confirmed adduct, etc. Users can quickly review components with confidence and focus on true unknowns. All processed data (including mass spectra, chromatograms, and summary tables) is automatically stored in a database and easily retrievable for additional reprocessing. Collaboration and reporting are made easier with multi-user access to the databases and customizable reports.
Novel aspect
- Utilizing common ions between principle structure and related components for accelerated elucidation of unknowns in complex samples