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Membrane protein shaving with thermolysin can be used to evaluate topology predictors
Authors:Maria Bendz  Marcin Skwark  Daniel Nilsson  Viktor Granholm  Susana Cristobal  Lukas Käll  Arne Elofsson
Institution:1. Department of Biochemistry and Biophysics, Science for Life Laboratory, Center for Biomembrane Research, Stockholm University, , Stockholm, Sweden;2. Department of Clinical and Experimental Medicine, Cell Biology, Faculty of Health Science, Link?ping University, , Link?ping, Sweden;3. IKERBASQUE, Basque Foundation for Science, Department of Physiology, Basque Country Medical School, , Bilbao, Spain;4. Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology (KTH), , Solna, Sweden
Abstract:Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large‐scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over‐expressed proteins. Second, we analyzed the peptides from non‐over‐expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors. At the end we suggest that the usage of thermolysin, an enzyme working at the natural pH of the cell for membrane shaving, is superior because: (i) we detect a similar number of peptides and proteins using thermolysin and trypsin; (ii) thermolysin shaving can be run at a natural pH and (iii) the incubation time is quite short. (iv) Fewer detected peptides from thermolysin shaving originate from the transmembrane regions. Using thermolysin shaving we can also provide a clear separation between the best and the less accurate topology predictors, indicating that using data from shaving can provide valuable information when developing new topology predictors.
Keywords:Bioinformatics  Digestion on‐membrane  Mass spectra  Membrane proteins
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