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Improved Ranking of Putative Candidates Through a Hybrid In Silico / Real Fragmentation Technique

Reputable Mentor II
Reputable Mentor II
Tim Stratton1, Michal Raab2, Jakub Mezey2, Ioanna Ntai1, Ralf Tautenhahn1, Robert Mistrik2
ASMS 2018
Purpose: To demonstrate an algorithmic approach to rank putative chemical database candidates for unknown compounds by utilizing reference spectral library data. Methods: HRAM MS/MS and MSn data on a series of compounds not present in the reference spectral library was acquired. This data was processed using an algorithm (mzLogic™) that performed, broadly, three steps consisting of chemical database search (ChemSpider™) to obtain putative structures followed by spectral library similarity search (mzCloud™) and a ranking of putative structures based on the common substructure explained by fragments observed in the reference library.

1. Thermo Fisher Scientific, Austin TX, USA 2. HighChem LLC, Bratislava, Slovakia
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Last update:
‎10-15-2021 11:20 AM
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