Abstract
Membrane proteins are estimated to constitute a quarter of all proteins encoded in plant genomes, yet only a limited number have been experimentally characterized. This is mainly due to the large variation in particular physical properties coupled with purification difficulties. Computational methods are therefore very helpful for the initial characterization of a candidate membrane protein. Individual prediction tools can, with varying levels of success, predict the occurrence of transmembrane spans, the subcellular location, and lipid posttranslational modifications. Since it can be tedious to consult each prediction tool separately, ARAMEMNON has been designed to compile various computational predictions for plant membrane proteins and to present the results via a user-friendly web interface. This protocol describes how to use ARAMEMNON to identify and characterize plant membrane proteins.
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Acknowledgments
The authors would like to thank Marie Bolger for proofreading the manuscript.
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Schwacke, R., Flügge, UI. (2018). Identification and Characterization of Plant Membrane Proteins Using ARAMEMNON. In: Mock, HP., Matros, A., Witzel, K. (eds) Plant Membrane Proteomics. Methods in Molecular Biology, vol 1696. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7411-5_17
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DOI: https://doi.org/10.1007/978-1-4939-7411-5_17
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