title: Consensus prediction of amyloidogenic determinants in amyloid fibril-forming proteins.
abstract: We combine the results of three prediction algorithms on a test set of 21 amyloidogenic proteins to predict amyloidogenic determinants. Two prediction algorithms are recently developed prediction algorithms of amyloidogenic stretches in protein sequences, whereas the third is a secondary structure prediction algorithm capable of identifying 'conformational switches' (regions that have both the propensity for alpha-helix and beta-sheet). Surprisingly, the results of prediction agree well and also agree with experimentally investigated amyloidogenic regions. Furthermore, they suggest several previously not identified amino acid stretches as potential amyloidogenic determinants. Most predicted (and experimentally observed) amyloidogenic determinants reside on the protein surface of relevant solved crystal structures. It appears that a consensus prediction algorithm is more objective than individual prediction methods alone.
authors.affiliation: Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, Greece. shamodr@biol.uoa.gr
authors.forename: Stavros J
authors.initials: SJ
authors.lastname: Hamodrakas
authors.forename: Christina
authors.initials: C
authors.lastname: Liappa
authors.forename: Vassiliki A
authors.initials: VA
authors.lastname: Iconomidou
mesh_terms: D000465:Algorithms; D000682:Amyloid / Q000737:chemistry*; D000818:Animals; D030562:Databases, Protein; D006801:Humans; D011237:Predictive Value of Tests; D017433:Protein Structure, Secondary; D020539:Sequence Analysis, Protein
chemical_list: D000682:Amyloid