LIPID MAPS online tools for lipid research

Eoin Fahy 1 Manish Sud 1 Dawn Cotter 1 Shankar Subramaniam 0 1 0 Departments of Bioengineering, Chemistry and Biochemistry, University of California , San Diego, La Jolla, CA 92093, USA 1 LIPID MAPS Bioinformatics Core, San Diego Supercomputer Center, University of California , San Diego , 9500 Gilman Drive, La Jolla, CA 92037, USA 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/. - The structures of large and complex lipids are difficult to represent in drawings, which leads to the use of many custom formats that often generate more confusion than clarity among members of the lipid research community. For example, usage of the Simplified Molecular Line Entry Specification (SMILES) (1) (www.daylight.com/ smiles/index.html) format to represent lipid structures, while being very compact and accurate in terms of bond connectivity, valence and chirality, causes problems when the structure is rendered. This is due to the fact that the SMILES format does not include 2D coordinates and hence the orientation of the structure as drawn is quite arbitrary, making visual recognition and comparison of related structures difficult. Members of the lipid community currently draw structures based on their own individual preferences. A given lipid structure may appear quite differently in different lipid databases (2, 3). In summary, consistent structure-drawing tools for lipids are currently not available. The structure-drawing step is typically a most timeconsuming process in creating molecular databases of lipids. However, many classes of lipids lend themselves to automated structure-drawing paradigms, due to their consistent 2D layout. The LIPID MAPS consortium has developed and deployed a suite of structure-drawing tools that greatly increase the efficiency of data entry into lipid structure databases and permit on-demand structure generation in conjunction with a variety of MS prediction tools. We have chosen a consistent format for representing lipid structures (4) where, in the simplest case of the fatty acid derivatives, the acid group (or equivalent) is drawn on the right and the hydrophobic hydrocarbon chain is on the left. Similarly for glycerolipids, glycerophospholipids and sphingolipids, the radyl hydrocarbon chains are drawn to the left and the headgoups are depicted on the right. This approach enables a more consistent, error-free approach to drawing lipid structures and has been used extensively in populating the LIPID MAPS structure database (LMSD), which currently contains over 10 000 molecules (5). We have adopted an approach where core structures such as diacetyl glycerol (glycerolipids) and formic acid (fatty acyls) are represented as text-based MDL molfiles (described under section MDL CTfile Formats at www.mdli.com), and these molfiles are then manipulated to generate a variety of structures in MDL molfile and Structure Data Format (SDF) files containing that core (Figure 1). This manipulation is carried out by commandline or online programs written in the Perl programming language. The structural similarities of many lipid categories also make it feasible to predict structures from MS precursor ion and/or product ion data by creating a database composed of masses of all possible likely combinations of MDLMOL file template Structure drawing tools MDL MOLfile containing structure or SDF structure data file containing structures along with name and ontology data acyl side chains for a given lipid core. One can then use matching algorithms to display possible candidates for given precursor ion/product ion m/z values and then generate corresponding structures. DESCRIPTION AND IMPLEMENTATION The LIPID MAPS website (www.lipidmaps.org/tools/ index.html) currently contains a suite of six structuredrawing tools for the following lipid categories: fatty acyls, glycerolipids, glycerophospholipids, cardiolipins, sphingolipids and sterols. The online layout (Figure 2) consists of a core structure and pull-down menus arranged in locations appropriate for that structure. For example, in the case of the glycerophospholipid-drawing tool, a central glycerol core is surrounded by pull-down menus allowing the end-user to choose from a list of headgroups and sn1 and sn2 acyl side chains. The list of acyl chains represents the more common species found in mammalian cells, and could easily be modified to include additional chains. The selected lipid structure is then generated via a server-side Perl script. The structure is rendered in the web browser as a Java-based MarvinView applet (www.chemaxon.com/marvin/). Additionally, the structure may be viewed online with the Chemdraw ActiveX/Plugin (www.cambridgesoft.com/software/Chem Draw/) by users who have this component installed on their system. Current versions of the fatty-acyl-drawing tools are now capable of drawing chiral centers and ring structures. Molecules with correct stereochemistry are drawn by implementing the following method: (1) usage of the PerlMol (www.perlmol.org/) module to define atoms, bonds and neighbors; (2) a recursive algorithm which applies CahnIngoldPrelog (CIP) (6, 7) rules to a chiral center and (3) a scoring system to estimate substituent priority to assign chirality. LIPID MAPS abbreviation Concurrently, a generalized lipid abbreviation format has been developed which enables structures, systematic names and ontologies to be generated automatically from a single source format (Figure 3). The LIPID MAPS abbreviation format for lipids may consist of up to four different parts: (i) carbon chain length along with any degree of unsaturation; (ii) position and geometry of double and triple bonds; (iii) position, type and stereochemistry of substituents and (iv) position of carbocylic ring junction and stereochemistry. The first part of th (...truncated)