title: Prediction of "hot spots" of aggregation in disease-linked polypeptides.
abstract: BACKGROUND
  The polypeptides involved in amyloidogenesis may be globular proteins with a defined 3D-structure or natively unfolded proteins. The first class includes polypeptides such as beta2-microglobulin, lysozyme, transthyretin or the prion protein, whereas beta-amyloid peptide, amylin or alpha-synuclein all belong to the second class. Recent studies suggest that specific regions in the proteins act as "hot spots" driving aggregation. This should be especially relevant for natively unfolded proteins or unfolded states of globular proteins as they lack significant secondary and tertiary structure and specific intra-chain interactions that can mask these aggregation-prone regions. Prediction of such sequence stretches is important since they are potential therapeutic targets.
  
  
  RESULTS
  In this study we exploited the experimental data obtained in an in vivo system using beta-amyloid peptide as a model to derive the individual aggregation propensities of natural amino acids. These data are used to generate aggregation profiles for different disease-related polypeptides. The approach detects the presence of "hot spots" which have been already validated experimentally in the literature and provides insights into the effect of disease-linked mutations in these polypeptides.
  
  
  CONCLUSIONS
  The proposed method might become a useful tool for the future development of sequence-targeted anti-aggregation pharmaceuticals.
authors.affiliation: Departament de Bioquímica i Biologia Molecular, Facultat de Ciències, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Spain. Natalia.Sanchezd@campus.uab.es
authors.forename: Natalia
authors.initials: N
authors.lastname: Sánchez de Groot
authors.forename: Irantzu
authors.initials: I
authors.lastname: Pallarés
authors.forename: Francesc X
authors.initials: FX
authors.lastname: Avilés
authors.forename: Josep
authors.initials: J
authors.lastname: Vendrell
authors.forename: Salvador
authors.initials: S
authors.lastname: Ventura
mesh_terms: D016229:Amyloid beta-Peptides / Q000737:chemistry; D006801:Humans; D007328:Insulin / Q000737:chemistry; D008958:Models, Molecular; D009113:Muramidase / Q000737:chemistry; D009154:Mutation; D019636:Neurodegenerative Diseases / Q000378:metabolism; D010455:Peptides / Q000737:chemistry*; D011228:Prealbumin / Q000737:chemistry; D011328:Prions / Q000737:chemistry; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry; D051844:alpha-Synuclein / Q000737:chemistry; D001613:beta 2-Microglobulin / Q000737:chemistry
chemical_list: D016229:Amyloid beta-Peptides; D007328:Insulin; D010455:Peptides; D011228:Prealbumin; D011328:Prions; D011506:Proteins; D051844:alpha-Synuclein; D001613:beta 2-Microglobulin; D009113:Muramidase