Managing Biotransformation Data

In support of these investigations, a well-structured yet flexible data model is required. Metabolic pathways are a way of describing molecular entities and their interrelationships. From a data management point of view, a container for chemical structures has to be established that meets several requirements  

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METEOR S biotransformation rules are generic reaction descriptors, and the versatile structural representation used in the system allows each atom or bond to have specific physicochemical properties. This approach provides more details than simple hard-coded functional group descriptors (313), but this flexibility also can give rise to an avalanche of data. METEOR manages the amount of data by predicting which metabolites are to be formed rather than all the possible outcomes (310,312,314,315). At high certainty levels, when chosen, only the more likely biotransformations are requested. At lower likelihood levels, the more common metabolites are also selected for examination. Currently, METEOR knowledge-based biotransformations are exclusively for mammalian biotransformations (phase I and phase II) (314,315). 

Automated software algorithms such as Waters MetaboLynx Application-Manager detects putative biotransformations for expected and unexpected putative metabolites (Nassar and Adams, 2003 Mortishire-Smith et al., 2005). The Application-Manager automatically runs samples scheduled for analysis by LC-MS and processes the resulting data (Fig. 4.12). Results are reported via a data browser that enables the chromatographic and mass spectrometric evidence that supports each automated metabolic assignment. 

Meteor can be interfaced with the MetaboLynx mass spectrometer software from Waters Corporation to integrate mass spectrometry data from metabolism studies directly. MetaboLynx is part of the Waters MassLynx Application Managers, a suite of mass spectrometry instrument software [16]. It is designed for automated metabolism studies with data from LC/MS or LC/MS/MS time-of-flight (TOP) experiments. MetaboLynx is able to detect peaks in an LC/MS data file resulting from in vitro or in vivo biotransformation and provides a list of elemental formulae for unidentified components in a mass spectrum. Meteor uses these data to filter the list of predicted metabolites. System requirements are similar to DEREK for Windows. 

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