title: From the Evolution of Protein Sequences Able to Resist Self-Assembly to the Prediction of Aggregation Propensity.
abstract: Folding of polypeptide chains into biologically active entities is an astonishingly complex process, determined by the nature and the sequence of residues emerging from ribosomes. While it has been long believed that evolution has pressed genomes so that specific sequences could adopt unique, functional three-dimensional folds, it is now clear that complex protein machineries act as quality control system and supervise folding. Notwithstanding that, events such as erroneous folding, partial folding, or misfolding are frequent during the life of a cell or a whole organism, and they can escape controls. One of the possible outcomes of this misbehavior is cross-β aggregation, a super secondary structure which represents the hallmark of self-assembled, well organized, and extremely ordered structures termed amyloid fibrils. What if evolution would have not taken into account such possibilities? Twenty years of research point toward the idea that, in fact, evolution has constantly supervised the risk of errors and minimized their impact. In this review we tried to survey the major findings in the amyloid field, trying to describe what the real pitfalls of protein folding are-from an evolutionary perspective-and how sequence and structural features have evolved to balance the need for perfect, dynamic, functionally efficient structures, and the detrimental effects implicit in the dangerous process of folding. We will discuss how the knowledge obtained from these studies has been employed to produce computational methods able to assess, predict, and discriminate the aggregation properties of protein sequences.
authors.affiliation: Università degli Studi di Firenze, Firenze, Italy. Electronic address: francesco.bemporad@unifi.it.
authors.forename: F
authors.initials: F
authors.lastname: Bemporad
authors.affiliation: Università degli Studi di Firenze, Firenze, Italy. Electronic address: matteo.ramazzotti@unifi.it.
authors.forename: M
authors.initials: M
authors.lastname: Ramazzotti
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000682:Amyloid / Q000737:chemistry / Q000378:metabolism; D000818:Animals; D019143:Evolution, Molecular; D006801:Humans; D066329:Protein Aggregates; D011506:Proteins / Q000737:chemistry*
chemical_list: D000682:Amyloid; D066329:Protein Aggregates; D011506:Proteins
keywords: Amyloid; Amyloid predictor; Neurodegeneration; Protein misfolding; Self-assembly