title: Predicting aggregation-prone sequences in proteins.
abstract: Owing to its association with a diverse range of human diseases, the determinants of protein aggregation are studied intensively. It is generally accepted that the effective aggregation tendency of a protein depends on many factors such as folding efficiency towards the native state, thermodynamic stability of that conformation, intrinsic aggregation propensity of the polypeptide sequence and its ability to be recognized by the protein quality control system. The intrinsic aggregation propensity of a polypeptide sequence is related to the presence of short APRs (aggregation-prone regions) that self-associate to form intermolecular β-structured assemblies. These are typically short sequence segments (5-15 amino acids) that display high hydrophobicity, low net charge and a high tendency to form β-structures. As the presence of such APRs is a prerequisite for aggregation, a plethora of methods have been developed to identify APRs in amino acid sequences. In the present chapter, the methodological basis of these approaches is discussed, as well as some practical applications.
authors.forename: Greet
authors.initials: G
authors.lastname: De Baets
authors.forename: Joost
authors.initials: J
authors.lastname: Schymkowitz
authors.forename: Frederic
authors.initials: F
authors.lastname: Rousseau
mesh_terms: D000595:Amino Acid Sequence; D000682:Amyloid / Q000737:chemistry*; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D066263:Protein Aggregation, Pathological / Q000378:metabolism; D011487:Protein Conformation; D017510:Protein Folding; D020539:Sequence Analysis, Protein
chemical_list: D000682:Amyloid