ASMS Conference on Mass Spectrometry 2006

Seattle, WA, USA
May 28 - June 1, 2006

Visit us in Booth #74 and Hospitality Suite: Olympic during show hours and view the Agenda for our Seminar to be held on Sunday, May 28, 2006.

ACD/Labs' Talk Schedule
Title:	What and how much information can we really extract in an automated manner from LC/MS data?
Authors:	Robyn A. Rourick1; John P. Walsh1; Bayliss Mark23; Vitaly Lashin23 1Kalypsys, Inc., San Diego, CA; 2Advanced Chemistry Development, Toronto, Canada; 3Advanced Chemistry Development, Moscow, Russia
Session:	Metabolite Identification using Hyphenated MS Techniques
Code:	TOA am
Time Slot/   Poster Number:	11:55
Introduction:	Extraction and identification of potential metabolites has historically relied on a combination of instruments and methodological approaches. For example a systematic LC/MS approach to metabolite identification was reported by Clarke (1) et al which detailed a strategy involving a series of LC/MS platforms including a quadrupole ion trap, time of flight and a triple quadrupole. The triple quadrupole allowing access to potentially related compounds via precursor. The ion trap for successive understanding of the fragmentation and an ability to perform data driven experiments to acquire fragmental evidence for potentially related species. The final combination of time of flight technology and increased accurate mass capabilities completes the ability to probe potential empirical formulas in support of compound extraction and confirmation.
Methods:	In each of these approaches a significant amount of data results, requiring manual evaluation, assessment and cross correlation with supporting data from the other instrumentation types. Our laboratory is focused on metabolism, impurity and degradation studies in support of our pipeline, with major bottlenecks in data reduction, information extraction and collation of findings across a range of instrument types.
Preliminary   Results:	Using a self modeling approach to chromatographic peak extraction and automated identification of molecular ion, isotopic clusters, neutral loss , fragment ion presence, accurate mass, mass deviation from parent knowledge and direct access to a structural library, we are able to leverage complimentary and orthogonal aspects of the data to extract related components from a dataset. The test data was made using a time of flight mass spectrometer, set to acquire in accurate mass mode and with the application of source CID. This all-in-one approach provides for extremely rapid data reduction to the minimum of information elements from which to extract and identify related components. 1. Clarke, Nigel, J., et al, Analytical Chemistry, August 1, 2001; 430A-439A
ACD/Labs' Poster Schedule
Title:	Why is Automating the Determination of Molecular Ions Using Automated Approaches so Hard and How Might it be Used?
Authors:	Mark A. Bayliss1; Vitaly Lashin2 1Advanced Chemistry Development Inc, Toronto, ON; 2Advanced Chemistry Development, Moscow, Russia
Session:	Computer Applications
Code:	WP04
Time Slot/   Poster Number:	070
Introduction:	Molecular ion identification is the corner stone of all MS1 data analyses that are undertaken and which forms a major time allocation when it comes to data reduction and primary assessment by all manner of scientists across all sectors of mass spectrometry disciplines. A number of highly accomplished algorithms have been created over the years using chemometric approaches applicable in the reduction or removal of low frequency noise. Such examples including CODA from Windig et al, MEND from Karger et al., however these algorithms can be classified as extremely sensitive peak extraction algorithms as the output requires a scientist to analyze the contributing ions as a particular rention time solving for molecular weight and key information.
Methods:	Using CODA as a specific peak extraction algorithm, a novel approach to retention time grouping was developed to overcome the limitations imposed by the inherent noisy nature of the MS1 data. To limit the amount of optimization that has to be carried on a per data set basis, a self-modeling approach to data filtration and selection had to be developed. To determine the molecular ion for each eluting component, it was necessary to determine all ions contributing to a single ion cluster within a particular retention time region. The determination of molecular weight was made possible using as much of the contributing ion clusters as possible, solving for classical adducts, multimers and ion losses from the molecular ion 12C.
Preliminary   Results:	Solving for molecular ion, the goal of this project represents a major challenge both mathematically and from a mass spectrometry point of view. Often, even in electrospray the presence of radical cations and peak artifacts can cause miss-assignment of the 12C on which the determination of the molecular ion is key. The presence of competing ion clusters in the component spectrum in many cases may be as simple as a single molecular ion, however in more complex spectral scenarios, adducts and labile fragment ions challenged our ability to correctly deconvolve the spectral elements. A challenge which faces all scientists today is how to differentiate real peaks from noise and noise clusters that appear as peaks either naturally or because of the necessary processing actions such that it appears somewhat peak like. Our approach using multiple data elements to provide a component analysis has helped to overcome some of these challenging and what may turn out to be impossible challenges to overcome with total confidence. During our investigations, we have found that once all algorithms were brought together into a cohesive series of actions, that it is technically possible to apply this approach to a wide number of samples from a wide number of application areas. In one approach that has been investigated, the combination of LC/MS on a time of flight, operating in accurate mass mode, with source induced dissociation applied and with applied mass delta knowledge, fractional mass filters, and empirical formula generation as function of every extracted 12C ion in the dataset, we were able to demonstrate extensive coverage of chemical space for related chemical species. Coupling the accurate mass analysis with automated structure and fragment searching provides a rapid means of screening complex datasets for related and specific compounds of interest.