Matching unknown empirical formulas to chemical structure using LC/MS TOF accurate mass and database searching: example of unknown pesticides on tomato skins

Abstract

Traditionally, the screening of unknown pesticides in food has been accomplished by GC/MS methods using conventional library searching routines. However, many of the new polar and thermally labile pesticides and their degradates are more readily and easily analyzed by LC/MS methods and no searchable libraries currently exist (with the exception of some user libraries, which are limited). Therefore, there is a need for LC/MS approaches to detect unknown non-target pesticides in food. This report develops an identification scheme using a combination of LC/MS time-of-flight (accurate mass) and LC/MS ion trap MS (MS/MS) with searching of empirical formulas generated through accurate mass and a ChemIndex database or Merck Index database. The approach is different than conventional library searching of fragment ions. The concept here consists of four parts. First is the initial detection of a possible unknown pesticide in actual market-place vegetable extracts (tomato skins) using accurate mass and generating empirical formulas. Second is searching either the Merck Index database on CD (10,000 compounds) or the ChemIndex (77,000 compounds) for possible structures. Third is MS/MS of the unknown pesticide in the tomato-skin extract followed by fragment ion identification using chemical drawing software and comparison with accurate-mass ion fragments. Fourth is the verification with authentic standards, if available. Three examples of unknown, non-target pesticides are shown using a tomato-skin extract from an actual market place sample. Limitations of the approach are discussed including the use of A + 2 isotope signatures, extended databases, lack of authentic standards, and natural product unknowns in food extracts.