title: Memoir: template-based structure prediction for membrane proteins.
abstract: Membrane proteins are estimated to be the targets of 50% of drugs that are currently in development, yet we have few membrane protein crystal structures. As a result, for a membrane protein of interest, the much-needed structural information usually comes from a homology model. Current homology modelling software is optimized for globular proteins, and ignores the constraints that the membrane is known to place on protein structure. Our Memoir server produces homology models using alignment and coordinate generation software that has been designed specifically for transmembrane proteins. Memoir is easy to use, with the only inputs being a structural template and the sequence that is to be modelled. We provide a video tutorial and a guide to assessing model quality. Supporting data aid manual refinement of the models. These data include a set of alternative conformations for each modelled loop, and a multiple sequence alignment that incorporates the query and template. Memoir works with both α-helical and β-barrel types of membrane proteins and is freely available at http://opig.stats.ox.ac.uk/webapps/memoir.
authors: Department of Statistics, Oxford University, Oxford, OX1 3TG, UK.
authors: Jean-Paul
authors: JP
authors: Ebejer
authors: Jamie R
authors: JR
authors: Hill
authors: Sebastian
authors: S
authors: Kelm
authors: Jiye
authors: J
authors: Shi
authors: Charlotte M
authors: CM
authors: Deane
mesh_terms: D020407:Internet; D008565:Membrane Proteins / Q000737:chemistry*; D008958:Models, Molecular; D012984:Software; D040681:Structural Homology, Protein
chemical_list: D008565:Membrane Proteins
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