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. 2007 Jul;35(Web Server issue):W606-12.
doi: 10.1093/nar/gkm324. Epub 2007 Jun 21.

LIPID MAPS online tools for lipid research

Eoin Fahy  1 , Manish Sud, Dawn Cotter, Shankar Subramaniam
Affiliations

LIPID MAPS online tools for lipid research

Eoin Fahy et al. Nucleic Acids Res. 2007 Jul.

Abstract

The LIPID MAPS consortium has developed a number of online tools for performing tasks such as drawing lipid structures and predicting possible structures from mass spectrometry (MS) data. A simple online interface has been developed to enable an end-user to rapidly generate a variety of lipid chemical structures, along with corresponding systematic names and ontological information. The structure-drawing tools are available for six categories of lipids: (i) fatty acyls, (ii) glycerolipids, (iii) glycerophospholipids, (iv) cardiolipins, (v) sphingolipids and (vi) sterols. Within each category, the structure-drawing tools support the specification of various parameters such as chain lengths at a specific sn position, head groups, double bond positions and stereochemistry to generate a specific lipid structure. The structure-drawing tools have also been integrated with a second set of online tools which predict possible lipid structures from precursor-ion and product-ion MS experimental data. The MS prediction tools are available for three categories of lipids: (i) mono/di/triacylglycerols, (ii) glycerophospholipids and (iii) cardiolipins. The LIPID MAPS online tools are publicly available at www.lipidmaps.org/tools/.

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Figures

Figure 1.
Figure 1.
Schematic demonstrating the principle of using molfile templates and a list of lipid abbreviations as input for structure-drawing tools.
Figure 2.
Figure 2.
Online structure-drawing tool for glycerophospholipids.
Figure 3.
Figure 3.
Flowchart showing structure/name/ontology generation from an abbreviation of a lipid. This example demonstrates the conversion of a text abbreviation for a prostaglandin into a dataset containing structure (MDL Molfile), systematic name, classification and various molecular attributes such as formula, molecular weight, number of functional groups, double bonds and rings.
Figure 4.
Figure 4.
Online MS prediction tools for glycerophospholipids.
See this image and copyright information in PMC

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